8.6.3.2 Domain Adaption for Semantic Segmentation

Chapter Contents (Back)
Semantic Segmentation. Domain Adaption.
See also Domain Adaptation.
See also Weakly Supervised, Self Supervised Semantic Segmentation.

Li, R.[Rui], Cao, W.M.[Wen-Ming], Jiao, Q.F.[Qian-Fen], Wu, S.[Si], Wong, H.S.[Hau-San],
Simplified unsupervised image translation for semantic segmentation adaptation,
PR(105), 2020, pp. 107343.
Elsevier DOI 2006
Domain adaptation, Image segmentation, Image translation BibRef

Vu, T., Jain, H., Bucher, M., Cord, M., Pérez, P.P.,
DADA: Depth-Aware Domain Adaptation in Semantic Segmentation,
ICCV19(7363-7372)
IEEE DOI 2004
data models, image segmentation, DADA, depth-aware domain adaptation, unsupervised domain adaptation, Benchmark testing BibRef

Li, G.R.[Guang-Rui], Kang, G.L.[Guo-Liang], Liu, W.[Wu], Wei, Y.C.[Yun-Chao], Yang, Y.[Yi],
Content-consistent Matching for Domain Adaptive Semantic Segmentation,
ECCV20(XIV:440-456).
Springer DOI 2011
BibRef

Xu, H.Q.[Han-Qing], Yang, M.[Ming], Deng, L.Y.[Liu-Yuan], Qian, Y.Q.[Ye-Qiang], Wang, C.X.[Chun-Xiang],
Neutral Cross-Entropy Loss Based Unsupervised Domain Adaptation for Semantic Segmentation,
IP(30), 2021, pp. 4516-4525.
IEEE DOI 2105
Entropy, Semantics, Image segmentation, Minimization, Training, Perturbation methods, Optimization, Semantic segmentation, gradient neutralization BibRef

Yan, W.H.[Wei-Hao], Qian, Y.Q.[Ye-Qiang], Wang, C.X.[Chun-Xiang], Yang, M.[Ming],
Threshold-Adaptive Unsupervised Focal Loss for Domain Adaptation of Semantic Segmentation,
ITS(24), No. 1, January 2023, pp. 752-763.
IEEE DOI 2301
Training, Entropy, Semantics, Adaptation models, Real-time systems, Urban areas, Predictive models, Semantic segmentation, focal loss BibRef

Bucher, M.[Maxime], Vu, T.H.[Tuan-Hung], Cord, M.[Matthieu], Pérez, P.[Patrick],
Handling new target classes in semantic segmentation with domain adaptation,
CVIU(212), 2021, pp. 103258.
Elsevier DOI 2110
Boundless unsupervised domain adaptation, Generalized zero-shot learning, Self-training, Semantic segmentation BibRef

Tian, H.T.[Hai-Tao], Qu, S.[Shiru], Payeur, P.[Pierre],
A Prototypical Knowledge Oriented Adaptation Framework for Semantic Segmentation,
IP(31), 2022, pp. 149-163.
IEEE DOI 2112
Image segmentation, Semantics, Task analysis, Adaptation models, Training, Visualization, Image classification, Domain adaptation, transfer learning BibRef

Jian, Y.R.[Yi-Ren], Gao, C.Y.[Chong-Yang],
MetaPix: Domain transfer for semantic segmentation by meta pixel weighting,
IVC(116), 2021, pp. 104334.
Elsevier DOI 2112
Meta learning, Domain transfer learning, Semantic segmentation, Street view semantic segmentation BibRef

Guo, X.Q.[Xiao-Qing], Liu, J.[Jie], Yuan, Y.X.[Yi-Xuan],
Semantic-Oriented Labeled-to-Unlabeled Distribution Translation for Image Segmentation,
MedImg(41), No. 2, February 2022, pp. 434-445.
IEEE DOI 2202
Code, Segmentation.
WWW Link. Image segmentation, Semantics, Feature extraction, Data models, Task analysis, Semisupervised learning, few sample segmentation BibRef

Guo, X.Q.[Xiao-Qing], Yang, C.[Chen], Li, B.[Baopu], Yuan, Y.X.[Yi-Xuan],
MetaCorrection: Domain-aware Meta Loss Correction for Unsupervised Domain Adaptation in Semantic Segmentation,
CVPR21(3926-3935)
IEEE DOI 2111
Bridges, Adaptation models, Computational modeling, Semantics, Estimation, Metadata BibRef

Shah, K.[Kunjal], Bhat, G.[Gururaj],
Exploring semantic segmentation of related subclasses from a superset of classes,
PR(124), 2022, pp. 108509.
Elsevier DOI 2203
Image segmentation, Stuff classes, Deeplab BibRef

Zhang, B.[Bo], Chen, T.[Tao], Wang, B.[Bin], Wu, X.F.[Xiao-Feng], Zhang, L.M.[Li-Ming], Fan, J.Y.[Jia-Yuan],
Densely Semantic Enhancement for Domain Adaptive Region-Free Detectors,
CirSysVideo(32), No. 3, March 2022, pp. 1339-1352.
IEEE DOI 2203
Detectors, Feature extraction, Semantics, Object detection, Proposals, Adaptation models, Task analysis, adaptive region-free detectors BibRef

Yuan, B.[Bo], Zhao, D.[Danpei], Shao, S.[Shuai], Yuan, Z.H.[Ze-Huan], Wang, C.H.[Chang-Hu],
Birds of a Feather Flock Together: Category-Divergence Guidance for Domain Adaptive Segmentation,
IP(31), No. 2022, pp. 2878-2892.
IEEE DOI 2204
Image segmentation, Semantics, Adaptation models, Feature extraction, Training, Generative adversarial networks, intra-class aggregation BibRef

Rao, X.[Xiya], Lu, T.[Tao], Wang, Z.Y.[Zhong-Yuan], Zhang, Y.D.[Yan-Duo],
Few-Shot Semantic Segmentation via Frequency Guided Neural Network,
SPLetters(29), 2022, pp. 1092-1096.
IEEE DOI 2205
Semantics, Prototypes, Feature extraction, Image segmentation, Training, Testing, Merging, Semantic segmentation, frequency separation BibRef

Shenaj, D.[Donald], Barbato, F.[Francesco], Michieli, U.[Umberto], Zanuttigh, P.[Pietro],
Continual coarse-to-fine domain adaptation in semantic segmentation,
IVC(121), 2022, pp. 104426.
Elsevier DOI 2205
Coarse-to-fine learning, Unsupervised domain adaptation, Semantic segmentation, Continual learning, Deep learning BibRef

Nguyen-Meidine, L.T.[Le Thanh], Kiran, M.[Madhu], Pedersoli, M.[Marco], Dolz, J.[Jose], Blais-Morin, L.A.[Louis-Antoine], Granger, E.[Eric],
Incremental multi-target domain adaptation for object detection with efficient domain transfer,
PR(129), 2022, pp. 108771.
Elsevier DOI 2206
Deep learning, Convolutional NNs, Object detection, Unsupervised domain adaptation, Incremental learning BibRef

Tian, Y.J.[Ying-Jie], Zhu, S.[Siyu],
Partial Domain Adaptation on Semantic Segmentation,
CirSysVideo(32), No. 6, June 2022, pp. 3798-3809.
IEEE DOI 2206
Semantics, Image segmentation, Task analysis, Training, Annotations, Adaptation models, Feature extraction, Semantic segmentation, partial adaptation BibRef

Zhou, Q.Y.[Qian-Yu], Feng, Z.Y.[Zheng-Yang], Gu, Q.Q.[Qi-Qi], Cheng, G.L.[Guang-Liang], Lu, X.Q.[Xue-Quan], Shi, J.P.[Jian-Ping], Ma, L.Z.[Li-Zhuang],
Uncertainty-aware consistency regularization for cross-domain semantic segmentation,
CVIU(221), 2022, pp. 103448.
Elsevier DOI 2206
Domain adaptation, Semantic segmentation, Transfer learning, Consistency regularization BibRef

Wu, A.[Aming], Han, Y.[Yahong], Zhu, L.C.[Lin-Chao], Yang, Y.[Yi],
Instance-Invariant Domain Adaptive Object Detection Via Progressive Disentanglement,
PAMI(44), No. 8, August 2022, pp. 4178-4193.
IEEE DOI 2207
Feature extraction, Object detection, Training, Task analysis, Optimization, Proposals, Adaptation models, instance-invariant features BibRef

Wu, A.[Aming], Liu, R.[Rui], Han, Y.[Yahong], Zhu, L.C.[Lin-Chao], Yang, Y.[Yi],
Vector-Decomposed Disentanglement for Domain-Invariant Object Detection,
ICCV21(9322-9331)
IEEE DOI 2203
Object detection, Detectors, Performance gain, Feature extraction, Proposals, Compounds, Detection and localization in 2D and 3D BibRef

Zhang, X.H.[Xiao-Hong], Chen, Y.[Yi], Shen, Z.[Ziyi], Shen, Y.M.[Yu-Ming], Zhang, H.F.[Hao-Feng], Zhang, Y.D.[Yu-Dong],
Confidence-and-Refinement Adaptation Model for Cross-Domain Semantic Segmentation,
ITS(23), No. 7, July 2022, pp. 9529-9542.
IEEE DOI 2207
Semantics, Adaptation models, Image segmentation, Entropy, Training, Annotations, Data models, Semantic segmentation, confidence-aware entropy alignment BibRef

Iqbal, J.[Javed], Rawal, H.[Hamza], Hafiz, R.[Rehan], Chi, Y.T.[Yu-Tseh], Ali, M.[Mohsen],
Distribution regularized self-supervised learning for domain adaptation of semantic segmentation,
IVC(124), 2022, pp. 104504.
Elsevier DOI 2208
Semantic segmentation, Self-supervised learning, Domain adaptation, Multi-modal distribution learning BibRef

Zheng, Z.D.[Zhe-Dong], Yang, Y.[Yi],
Adaptive Boosting for Domain Adaptation: Toward Robust Predictions in Scene Segmentation,
IP(31), 2022, pp. 5371-5382.
IEEE DOI 2208
Adaptation models, Data models, Training, Predictive models, Computational modeling, Semantics, Benchmark testing, scene segmentation BibRef

Zhang, B.[Bo], Chen, T.[Tao], Wang, B.[Bin], Li, R.Y.[Ruo-Yao],
Joint Distribution Alignment via Adversarial Learning for Domain Adaptive Object Detection,
MultMed(24), 2022, pp. 4102-4112.
IEEE DOI 2208
Feature extraction, Detectors, Object detection, Adversarial machine learning, Task analysis, Training, class-wise transferability BibRef

An, S.M.[Shu-Min], Liao, Q.M.[Qing-Min], Lu, Z.Q.[Zong-Qing], Xue, J.H.[Jing-Hao],
Efficient Semantic Segmentation via Self-Attention and Self-Distillation,
ITS(23), No. 9, September 2022, pp. 15256-15266.
IEEE DOI 2209
Semantics, Context modeling, Knowledge engineering, Correlation, Convolution, Adaptation models, Transforms, Semantic segmentation, layer-wise context distillation BibRef

Zhao, Y.Y.[Yu-Yang], Zhong, Z.[Zhun], Luo, Z.M.[Zhi-Ming], Lee, G.H.[Gim Hee], Sebe, N.[Nicu],
Source-Free Open Compound Domain Adaptation in Semantic Segmentation,
CirSysVideo(32), No. 10, October 2022, pp. 7019-7032.
IEEE DOI 2210
Adaptation models, Compounds, Training, Semantics, Data models, Image segmentation, Transfer learning, Semantic segmentation, source-free domain adaptation BibRef

Wang, W.[Wei], Zhong, Z.[Zhun], Wang, W.J.[Wei-Jie], Chen, X.[Xi], Ling, C.[Charles], Wang, B.[Boyu], Sebe, N.[Nicu],
Dynamically Instance-Guided Adaptation: A Backward-free Approach for Test-Time Domain Adaptive Semantic Segmentation,
CVPR23(24090-24099)
IEEE DOI 2309
BibRef

Li, G.[Guofa], Ji, Z.F.[Ze-Feng], Qu, X.D.[Xing-Da],
Stepwise Domain Adaptation (SDA) for Object Detection in Autonomous Vehicles Using an Adaptive CenterNet,
ITS(23), No. 10, October 2022, pp. 17729-17743.
IEEE DOI 2210
Object detection, Detectors, Training, Deep learning, Feature extraction, Adaptive systems, Task analysis, adversarial learning BibRef

Chen, X.[Xu], Kuang, T.S.[Tian-Shu], Deng, H.[Hannah], Fung, S.H.[Steve H.], Gateno, J.[Jaime], Xia, J.J.[James J.], Yap, P.T.[Pew-Thian],
Dual Adversarial Attention Mechanism for Unsupervised Domain Adaptive Medical Image Segmentation,
MedImg(41), No. 11, November 2022, pp. 3445-3453.
IEEE DOI 2211
Image segmentation, Annotations, Semantics, Feature extraction, Task analysis, Medical diagnostic imaging, Adaptation models, medical image segmentation BibRef

Klingner, M.[Marvin], Ayache, M.[Mouadh], Fingscheidt, T.[Tim],
Continual BatchNorm Adaptation (CBNA) for Semantic Segmentation,
ITS(23), No. 11, November 2022, pp. 20899-20911.
IEEE DOI 2212
Semantics, Adaptation models, Task analysis, Data models, Image segmentation, Neural networks, Delays, Domain adaptation, batch normalization BibRef

Bou, X.[Xavier],
A Study of RobustNet, a Domain Generalization Method for Semantic Segmentation,
IPOL(12), 2022, pp. 469-479.
DOI Link 2212
Code, Domain Generalization. Code, Semantic Segmentation.
See also RobustNet: Improving Domain Generalization in Urban-Scene Segmentation via Instance Selective Whitening. BibRef

Wu, X.[Xinyi], Wu, Z.Y.[Zhen-Yao], Ju, L.[Lili], Wang, S.[Song],
A One-Stage Domain Adaptation Network With Image Alignment for Unsupervised Nighttime Semantic Segmentation,
PAMI(45), No. 1, January 2023, pp. 58-72.
IEEE DOI 2212
Semantics, Image segmentation, Training, Adaptation models, Lighting, Meteorology, Computational modeling, Domain adaptation, image alignment BibRef

Wu, X.[Xinyi], Wu, Z.Y.[Zhen-Yao], Guo, H.[Hao], Ju, L.[Lili], Wang, S.[Song],
DANNet: A One-Stage Domain Adaptation Network for Unsupervised Nighttime Semantic Segmentation,
CVPR21(15764-15773)
IEEE DOI 2111
Training, Bridges, Image segmentation, Annotations, Semantics, Neural networks BibRef

Chen, J.Z.[Jun-Zhang], Liu, Z.[Zichao], Jin, D.[Darui], Wang, Y.Y.[Yuan-Yuan], Yang, F.[Fan], Bai, X.Z.[Xiang-Zhi],
Light Transport Induced Domain Adaptation for Semantic Segmentation in Thermal Infrared Urban Scenes,
ITS(23), No. 12, December 2022, pp. 23194-23211.
IEEE DOI 2212
Semantics, Image segmentation, Task analysis, Feature extraction, Cameras, Voltage control, Lighting, Urban scenes, semantic segmentation BibRef

Zhu, S.[Siyu], Tian, Y.J.[Ying-Jie],
Shape robustness in style enhanced cross domain semantic segmentation,
PR(135), 2023, pp. 109143.
Elsevier DOI 2212
Domain adaptation, Semantic segmentation, Transfer learning BibRef

Wang, S.[Shuang], Zhao, D.[Dong], Zhang, C.[Chi], Guo, Y.W.[Yu-Wei], Zang, Q.[Qi], Gu, Y.[Yu], Li, Y.[Yi], Jiao, L.C.[Li-Cheng],
Cluster Alignment With Target Knowledge Mining for Unsupervised Domain Adaptation Semantic Segmentation,
IP(31), 2022, pp. 7403-7418.
IEEE DOI 2212
Adaptation models, Correlation, Semantic segmentation, Clustering methods, Transforms, Benchmark testing, Task analysis, graph cut BibRef

Liu, F.[Feng], Zhang, X.S.[Xiao-Song], Wan, F.[Fang], Ji, X.Y.[Xiang-Yang], Ye, Q.X.[Qi-Xiang],
Domain Contrast for Domain Adaptive Object Detection,
CirSysVideo(32), No. 12, December 2022, pp. 8227-8237.
IEEE DOI 2212
Detectors, Adaptation models, Object detection, Feature extraction, Minimization, Transfer learning, Task analysis, Domain adaptation, transfer learning BibRef

Zhang, Y.[You], Chen, H.[Houjin], Li, Y.F.[Yan-Feng], Zhou, J.Q.[Jun-Qi],
ImDeeplabV3plus with instance selective whitening loss in domain generalization semantic segmentation,
IET-ITS(17), No. 1, 2023, pp. 180-192.
DOI Link 2301
BibRef

Gu, R.[Ran], Zhang, J.Y.[Jing-Yang], Wang, G.[Guotai], Lei, W.H.[Wen-Hui], Song, T.[Tao], Zhang, X.F.[Xiao-Fan], Li, K.[Kang], Zhang, S.T.[Shao-Ting],
Contrastive Semi-Supervised Learning for Domain Adaptive Segmentation Across Similar Anatomical Structures,
MedImg(42), No. 1, January 2023, pp. 245-256.
IEEE DOI 2301
Image segmentation, Annotations, Adaptation models, Training, Biomedical imaging, Anatomical structure, Task analysis, contrastive learning BibRef

Fang, Z.Y.[Zhi-Yuan], Gao, G.Y.[Guang-Yu], Zhang, Z.[Zekang], Zhang, A.[Anqi],
Hierarchical context-agnostic network with contrastive feature diversity for one-shot semantic segmentation,
JVCIR(90), 2023, pp. 103754.
Elsevier DOI 2301
Semantic segmentation, Few-shot learning, Unsupervised clustering, Hierarchical pyramid, Background exclusion BibRef

Zhou, Q.Y.[Qian-Yu], Feng, Z.Y.[Zheng-Yang], Gu, Q.Q.[Qi-Qi], Pang, J.M.[Jiang-Miao], Cheng, G.L.[Guang-Liang], Lu, X.Q.[Xue-Quan], Shi, J.P.[Jian-Ping], Ma, L.Z.[Li-Zhuang],
Context-Aware Mixup for Domain Adaptive Semantic Segmentation,
CirSysVideo(33), No. 2, February 2023, pp. 804-817.
IEEE DOI 2302
Semantics, Image segmentation, Adaptation models, Uncertainty, Task analysis, Degradation, Domain adaptation, scene understanding BibRef

Xu, S.[Shan], Zhang, H.D.[Huai-Dong], Xu, X.M.[Xue-Miao], Hu, X.W.[Xiao-Wei], Xu, Y.Y.[Yang-Yang], Dai, L.G.[Lian-Gui], Choi, K.S.[Kup-Sze], Heng, P.A.[Pheng-Ann],
Representative Feature Alignment for Adaptive Object Detection,
CirSysVideo(33), No. 2, February 2023, pp. 689-700.
IEEE DOI 2302
Feature extraction, Detectors, Proposals, Adaptation models, Object detection, Semantics, Prototypes, Domain adaptation, object detection BibRef

Chen, C.Q.[Chao-Qi], Li, J.C.[Jiong-Cheng], Zhou, H.Y.[Hong-Yu], Han, X.G.[Xiao-Guang], Huang, Y.[Yue], Ding, X.H.[Xing-Hao], Yu, Y.Z.[Yi-Zhou],
Relation Matters: Foreground-Aware Graph-Based Relational Reasoning for Domain Adaptive Object Detection,
PAMI(45), No. 3, March 2023, pp. 3677-3694.
IEEE DOI 2302
Cognition, Feature extraction, Semantics, Object detection, Training, Task analysis, Knowledge transfer, intra- and inter-domain BibRef

Qiu, Y.Q.[Yi-Qiao], Shen, Y.X.[Yi-Xing], Sun, Z.[Zhuohao], Zheng, Y.[Yanchong], Chang, X.B.[Xia-Bin], Zheng, W.S.[Wei-Shi], Wang, R.X.[Rui-Xuan],
SATS: Self-attention transfer for continual semantic segmentation,
PR(138), 2023, pp. 109383.
Elsevier DOI 2303
Continual learning, Semantic segmentation, Self-attention transfer, Class-specific region pooling BibRef

Zhou, H.Y.[Hua-Yi], Jiang, F.[Fei], Lu, H.T.[Hong-Tao],
SSDA-YOLO: Semi-supervised domain adaptive YOLO for cross-domain object detection,
CVIU(229), 2023, pp. 103649.
Elsevier DOI 2303
Domain adaptation, Knowledge distillation, Semi-supervised, YOLO BibRef

Zhao, Z.Y.[Zi-Yuan], Zhou, F.C.[Fang-Cheng], Xu, K.X.[Kai-Xin], Zeng, Z.[Zeng], Guan, C.T.[Cun-Tai], Zhou, S.K.[S. Kevin],
LE-UDA: Label-Efficient Unsupervised Domain Adaptation for Medical Image Segmentation,
MedImg(42), No. 3, March 2023, pp. 633-646.
IEEE DOI 2303
Image segmentation, Adaptation models, Biomedical imaging, Annotations, Adversarial machine learning, adversarial learning BibRef

Marnissi, M.A.[Mohamed Amine], Fradi, H.[Hajer], Sahbani, A.[Anis], Essoukri-Ben Amara, N.[Najoua],
Improved domain adaptive object detector via adversarial feature learning,
CVIU(230), 2023, pp. 103660.
Elsevier DOI 2303
BibRef
And: Corrigendum: CVIU(237), 2023, pp. 103685.
Elsevier DOI 2311
Unsupervised domain adaptation, Object detection, Adversarial learning, Feature alignment, Discriminator, Transferability BibRef

Ouyang, C.[Cheng], Chen, C.[Chen], Li, S.[Surui], Li, Z.[Zeju], Qin, C.[Chen], Bai, W.J.[Wen-Jia], Rueckert, D.[Daniel],
Causality-Inspired Single-Source Domain Generalization for Medical Image Segmentation,
MedImg(42), No. 4, April 2023, pp. 1095-1106.
IEEE DOI 2304
Image segmentation, Training, Biomedical imaging, Correlation, Robustness, Data models, Training data, Domain generalization, data augmentation BibRef

Liu, D.N.[Dong-Nan], Zhang, C.Y.[Chao-Yi], Song, Y.[Yang], Huang, H.[Heng], Wang, C.Y.[Chen-Yu], Barnett, M.[Michael], Cai, W.D.[Wei-Dong],
Decompose to Adapt: Cross-Domain Object Detection Via Feature Disentanglement,
MultMed(25), 2023, pp. 1333-1344.
IEEE DOI 2305
Feature extraction, Object detection, Task analysis, Training, Visualization, Minimization, Data mining, Automatic drive, object detection BibRef

Jiao, Y.F.[Yi-Fan], Yao, H.T.[Han-Tao], Xu, C.S.[Chang-Sheng],
Dual Instance-Consistent Network for Cross-Domain Object Detection,
PAMI(45), No. 6, June 2023, pp. 7338-7352.
IEEE DOI 2305
Feature extraction, Object detection, Detectors, Visualization, Proposals, Head, Task analysis, Cross-domain object detection, dual instance-consistent network BibRef

Li, W.Y.[Wu-Yang], Liu, X.Y.[Xin-Yu], Yuan, Y.X.[Yi-Xuan],
SIGMA++: Improved Semantic-Complete Graph Matching for Domain Adaptive Object Detection,
PAMI(45), No. 7, July 2023, pp. 9022-9040.
IEEE DOI 2306
BibRef
Earlier:
SIGMA: Semantic-complete Graph Matching for Domain Adaptive Object Detection,
CVPR22(5281-5290)
IEEE DOI 2210
Semantics, Adaptation models, Object detection, Prototypes, Image edge detection, Detectors, Feature extraction. Training, GSM, Visualization, Semantics, Self- semi- meta- Visual reasoning BibRef

Li, W.Y.[Wu-Yang], Liu, X.Y.[Xin-Yu], Yuan, Y.X.[Yi-Xuan],
SCAN++: Enhanced Semantic Conditioned Adaptation for Domain Adaptive Object Detection,
MultMed(25), 2023, pp. 7051-7061.
IEEE DOI Code:
WWW Link. 2311
BibRef

Zhou, Q.Y.[Qian-Yu], Gu, Q.Q.[Qi-Qi], Pang, J.M.[Jiang-Miao], Lu, X.Q.[Xue-Quan], Ma, L.Z.[Li-Zhuang],
Self-Adversarial Disentangling for Specific Domain Adaptation,
PAMI(45), No. 7, July 2023, pp. 8954-8968.
IEEE DOI 2306
Object detection, Semantic segmentation, Adaptation models, Meteorology, Computational modeling, Training, Task analysis, scene understanding BibRef

Xie, B.H.[Bin-Hui], Li, S.[Shuang], Li, M.J.[Ming-Jia], Liu, C.H.[Chi Harold], Huang, G.[Gao], Wang, G.R.[Guo-Ren],
SePiCo: Semantic-Guided Pixel Contrast for Domain Adaptive Semantic Segmentation,
PAMI(45), No. 7, July 2023, pp. 9004-9021.
IEEE DOI 2306
Semantics, Training, Task analysis, Semantic segmentation, Adaptation models, Prototypes, Visualization, Domain adaptation, self-training BibRef

Cheng, Y.T.[Yi-Ting], Wei, F.Y.[Fang-Yun], Bao, J.M.[Jian-Min], Chen, D.[Dong], Zhang, W.Q.[Wen-Qiang],
ADPL: Adaptive Dual Path Learning for Domain Adaptation of Semantic Segmentation,
PAMI(45), No. 8, August 2023, pp. 9339-9356.
IEEE DOI 2307
Visualization, Adaptation models, Training, Semantic segmentation, Pipelines, Synthetic data, Data models, Domain adaptation, self-supervised learning BibRef

Cheng, Y.T.[Yi-Ting], Wei, F.Y.[Fang-Yun], Bao, J.M.[Jian-Min], Chen, D.[Dong], Wen, F.[Fang], Zhang, W.Q.[Wen-Qiang],
Dual Path Learning for Domain Adaptation of Semantic Segmentation,
ICCV21(9062-9071)
IEEE DOI 2203
Image segmentation, Adaptation models, Visualization, Codes, Annotations, Computational modeling, grouping and shape BibRef

Guo, X.Q.[Xiao-Qing], Liu, J.[Jie], Liu, T.L.[Tong-Liang], Yuan, Y.X.[Yi-Xuan],
Handling Open-Set Noise and Novel Target Recognition in Domain Adaptive Semantic Segmentation,
PAMI(45), No. 8, August 2023, pp. 9846-9861.
IEEE DOI 2307
BibRef
Earlier:
SimT: Handling Open-set Noise for Domain Adaptive Semantic Segmentation,
CVPR22(7022-7031)
IEEE DOI 2210
Semantics, Noise measurement, Target recognition, Semantic segmentation, Data models, Adaptation models, simplex noise transition matrix. Representation learning, Adaptation models, Solid modeling, Computational geometry, Computational modeling, grouping and shape analysis BibRef

Gao, K.L.[Kui-Liang], Yu, A.[Anzhu], You, X.[Xiong], Qiu, C.P.[Chun-Ping], Liu, B.[Bing], Zhang, F.B.[Fu-Bing],
Cross-Domain Multi-Prototypes with Contradictory Structure Learning for Semi-Supervised Domain Adaptation Segmentation of Remote Sensing Images,
RS(15), No. 13, 2023, pp. 3398.
DOI Link 2307
BibRef

Ma, L.F.[Ling-Feng], Xie, H.T.[Hong-Tao], Liu, C.B.[Chuan-Bin], Zhang, Y.D.[Yong-Dong],
Learning Cross-Channel Representations for Semantic Segmentation,
MultMed(25), 2023, pp. 2774-2787.
IEEE DOI 2307
Feature extraction, Semantics, Cognition, Convolution, Image segmentation, Data mining, Context modeling, inter-channel relationship BibRef

Wang, Z.J.[Zhi-Jie], Liu, X.[Xing], Suganuma, M.[Masanori], Okatani, T.[Takayuki],
Unsupervised domain adaptation for semantic segmentation via cross-region alignment,
CVIU(234), 2023, pp. 103743.
Elsevier DOI 2307
Domain adaptation, Semantic segmentation, CNN BibRef

Cao, Y.H.[Yi-Hong], Zhang, H.[Hui], Lu, X.[Xiao], Chen, Y.R.[Yu-Rong], Xiao, Z.[Zheng], Wang, Y.N.[Yao-Nan],
Adaptive Refining-Aggregation-Separation Framework for Unsupervised Domain Adaptation Semantic Segmentation,
CirSysVideo(33), No. 8, August 2023, pp. 3822-3832.
IEEE DOI 2308
Semantic segmentation, Training, Semantics, Prototypes, Task analysis, Robots, Refining, Unsupervised domain adaptation, clustering technique BibRef

Wang, P.[Ping], Peng, J.[Jizong], Pedersoli, M.[Marco], Zhou, Y.F.[Yuan-Feng], Zhang, C.M.[Cai-Ming], Desrosiers, C.[Christian],
Shape-Aware Joint Distribution Alignment for Cross-Domain Image Segmentation,
MedImg(42), No. 8, August 2023, pp. 2338-2347.
IEEE DOI 2308
Image segmentation, Entropy, Software, Adversarial machine learning, Training, Task analysis, domain adaptation BibRef

Lu, Z.[Zhihe], Li, D.[Da], Song, Y.Z.[Yi-Zhe], Xiang, T.[Tao], Hospedales, T.M.[Timothy M.],
Uncertainty-Aware Source-Free Domain Adaptive Semantic Segmentation,
IP(32), 2023, pp. 4664-4676.
IEEE DOI 2309
BibRef

Ning, M.[Munan], Lu, D.H.[Dong-Huan], Xie, Y.J.[Yu-Jia], Chen, D.D.[Dong-Dong], Wei, D.[Dong], Zheng, Y.F.[Ye-Feng], Tian, Y.H.[Yong-Hong], Yan, S.C.[Shui-Cheng], Yuan, L.[Li],
MADAv2: Advanced Multi-Anchor Based Active Domain Adaptation Segmentation,
PAMI(45), No. 11, November 2023, pp. 13553-13566.
IEEE DOI 2310
BibRef

Ning, M.[Munan], Lu, D.H.[Dong-Huan], Wei, D.[Dong], Bian, C.[Cheng], Yuan, C.L.[Cheng-Lang], Yu, S.[Shuang], Ma, K.[Kai], Zheng, Y.F.[Ye-Feng],
Multi-Anchor Active Domain Adaptation for Semantic Segmentation,
ICCV21(9092-9102)
IEEE DOI 2203
Training, Costs, Codes, Annotations, Semantics, Manuals, Transfer/Low-shot/Semi/Unsupervised Learning, grouping and shape BibRef

Chao, C.H.[Chen-Hao], Cheng, B.W.[Bo-Wun], Wang, T.W.[Tzu-Wen], Liao, H.R.[Huang-Ru], Lee, C.Y.[Chun-Yi],
Rainbow UDA: Combining Domain Adaptive Models for Semantic Segmentation Tasks,
PAMI(45), No. 10, October 2023, pp. 12707-12713.
IEEE DOI 2310
BibRef

Dong, Y.S.[Yong-Sheng], Zhao, K.Y.[Kai-Yuan], Zheng, L.T.[Lin-Tao], Yang, H.T.[Hao-Tian], Liu, Q.[Qing], Pei, Y.H.[Yuan-Hua],
Refinement Co-supervision network for real-time semantic segmentation,
IET-CV(17), No. 6, 2023, pp. 652-662.
DOI Link 2310
image segmentation BibRef

Li, L.Y.[Lu-Yang], Ma, T.[Tai], Lu, Y.[Yue], Li, Q.L.[Qing-Li], He, L.[Lianghua], Wen, Y.[Ying],
A multi-grained unsupervised domain adaptation approach for semantic segmentation,
PR(144), 2023, pp. 109841.
Elsevier DOI 2310
Domain adaptation, Unsupervised semantic segmentation, Neural network BibRef

Kang, M.[Myeongkyun], Chikontwe, P.[Philip], Won, D.[Dongkyu], Luna, M.[Miguel], Park, S.H.[Sang Hyun],
Structure-preserving image translation for multi-source medical image domain adaptation,
PR(144), 2023, pp. 109840.
Elsevier DOI 2310
Domain adaptation, Data augmentation, Mutual information, Segmentation, Unpaired image translation BibRef

Zhang, L.[Lei], Qin, L.Y.[Ling-Yun], Xu, M.J.[Ming-Jun], Chen, W.J.[Wei-Jie], Pu, S.L.[Shi-Liang], Zhang, W.S.[Wen-Sheng],
Randomized Spectrum Transformations for Adapting Object Detector in Unseen Domains,
IP(32), 2023, pp. 4868-4879.
IEEE DOI 2310
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Munir, M.A.[Muhammad Akhtar], Khan, M.H.[Muhammad Haris], Sarfraz, M.S.[M. Saquib], Ali, M.[Mohsen],
Domain Adaptive Object Detection via Balancing Between Self-Training and Adversarial Learning,
PAMI(45), No. 12, December 2023, pp. 14353-14365.
IEEE DOI 2311
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Pang, J.[Jian], Liu, W.F.[Wei-Feng], Zhang, B.F.[Bing-Feng], Yang, X.[Xinghao], Liu, B.[Baodi], Tao, D.P.[Da-Peng],
MCNet: Magnitude consistency network for domain adaptive object detection under inclement environments,
PR(145), 2024, pp. 109947.
Elsevier DOI 2311
Object detection, Inclement environments, Frequency domain, Magnitude spectrum BibRef

Dong, Z.[Zihao], Niu, S.[Sijie], Gao, X.[Xizhan], Shao, X.L.[Xiu-Li],
Coarse-to-fine online latent representations matching for one-stage domain adaptive semantic segmentation,
PR(146), 2024, pp. 110019.
Elsevier DOI 2311
Unsupervised domain adaptation, Semantic segmentation, Coarse-to-fine matching, Latent representations, Adversarial structure BibRef

Shao, J.[Jie], Wu, J.C.[Jia-Cheng], Shen, W.Z.[Wen-Zhong], Yang, C.[Cheng],
A Pairwise DomMix Attentive Adversarial Network for Unsupervised Domain Adaptive Object Detection,
SPLetters(30), 2023, pp. 1667-1671.
IEEE DOI 2311
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Hu, X.G.[Xue-Gang], Xu, S.H.[Shu-Han], Jing, L.Y.[Li-Yuan],
Lightweight attention-guided redundancy-reuse network for real-time semantic segmentation,
IET-IPR(17), No. 9, 2023, pp. 2649-2658.
DOI Link 2307
convolutional neural nets, image segmentation, neural net architecture BibRef

Hu, X.G.[Xue-Gang], Liu, Y.J.[Yuan-Jing],
Lightweight multi-scale attention-guided network for real-time semantic segmentation,
IVC(139), 2023, pp. 104823.
Elsevier DOI 2311
Lightweight network, Attention mechanism, Multi-scale feature fusion, Real-time semantic segmentation BibRef

Tian, H.T.[Hai-Tao], Qu, S.[Shiru], Payeur, P.[Pierre],
Learning a target-dependent classifier for cross-domain semantic segmentation: Fine-tuning versus meta-learning,
PR(147), 2024, pp. 110091.
Elsevier DOI 2312
Domain adaptation, Semantic segmentation, Unsupervised learning, Meta-learning BibRef

Wang, Y.[Yan], Cheng, J.[Jian], Chen, Y.X.[Yi-Xin], Shao, S.[Shuai], Zhu, L.[Lanyun], Wu, Z.Z.[Zhen-Zhou], Liu, T.[Tao], Zhu, H.[Haogang],
FVP: Fourier Visual Prompting for Source-Free Unsupervised Domain Adaptation of Medical Image Segmentation,
MedImg(42), No. 12, December 2023, pp. 3738-3751.
IEEE DOI 2312
BibRef

Liu, S.L.[Shao-Lei], Yin, S.Q.[Si-Qi], Qu, L.[Linhao], Wang, M.[Manning], Song, Z.J.[Zhi-Jian],
A Structure-Aware Framework of Unsupervised Cross-Modality Domain Adaptation via Frequency and Spatial Knowledge Distillation,
MedImg(42), No. 12, December 2023, pp. 3919-3931.
IEEE DOI Code:
WWW Link. 2312
BibRef

Wu, J.H.[Jiang-Hao], Wang, G.[Guotai], Gu, R.[Ran], Lu, T.[Tao], Chen, Y.[Yinan], Zhu, W.T.[Wen-Tao], Vercauteren, T.[Tom], Ourselin, S.[Sébastien], Zhang, S.T.[Shao-Ting],
UPL-SFDA: Uncertainty-Aware Pseudo Label Guided Source-Free Domain Adaptation for Medical Image Segmentation,
MedImg(42), No. 12, December 2023, pp. 3932-3943.
IEEE DOI 2312
BibRef

Suzuki, S.[Satoshi], Yamane, T.[Taiga], Makishima, N.[Naoki], Suzuki, K.[Keita], Ando, A.[Atsushi], Masumura, R.[Ryo],
OnDA-DETR: Online Domain Adaptation for Detection Transformers with Self-Training Framework,
ICIP23(1780-1785)
IEEE DOI 2312
BibRef

Xi, Z.H.[Zhi-Hao], Meng, Y.[Yu], Chen, J.B.[Jing-Bo], Deng, Y.P.[Yu-Peng], Liu, D.[Diyou], Kong, Y.L.[Yun-Long], Yue, A.[Anzhi],
Learning to Adapt Adversarial Perturbation Consistency for Domain Adaptive Semantic Segmentation of Remote Sensing Images,
RS(15), No. 23, 2023, pp. 5498.
DOI Link 2312
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Hoyer, L.[Lukas], Dai, D.X.[Deng-Xin], Van Gool, L.J.[Luc J.],
Domain Adaptive and Generalizable Network Architectures and Training Strategies for Semantic Image Segmentation,
PAMI(46), No. 1, January 2024, pp. 220-235.
IEEE DOI 2312
BibRef
Earlier:
DAFormer: Improving Network Architectures and Training Strategies for Domain-Adaptive Semantic Segmentation,
CVPR22(9914-9925)
IEEE DOI 2210
Training, Image segmentation, Annotations, Semantics, Network architecture, Transformers, Transfer/low-shot/long-tail learning BibRef

Doan, A.D.[Anh-Dzung], Nguyen, B.L.[Bach Long], Gupta, S.[Surabhi], Reid, I.[Ian], Wagner, M.[Markus], Chin, T.J.[Tat-Jun],
Assessing domain gap for continual domain adaptation in object detection,
CVIU(238), 2024, pp. 103885.
Elsevier DOI Code:
WWW Link. 2312
Domain gap, Continual domain adaptation, Object detection BibRef

Xu, Y.H.[Yong-Hao], He, F.X.[Feng-Xiang], Du, B.[Bo], Tao, D.C.[Da-Cheng], Zhang, L.P.[Liang-Pei],
Self-Ensembling GAN for Cross-Domain Semantic Segmentation,
MultMed(25), 2023, pp. 7837-7850.
IEEE DOI 2312
BibRef

Xie, Q.S.[Qing-Song], Li, Y.X.[Yue-Xiang], He, N.[Nanjun], Ning, M.[Munan], Ma, K.[Kai], Wang, G.X.[Guo-Xing], Lian, Y.[Yong], Zheng, Y.F.[Ye-Feng],
Unsupervised Domain Adaptation for Medical Image Segmentation by Disentanglement Learning and Self-Training,
MedImg(43), No. 1, January 2024, pp. 4-14.
IEEE DOI 2401
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Chen, Y.[Yang], Shan, L.[Liang], Qu, Y.[Yi], Zhang, W.L.[Wei-Long], Chang, L.[Lu],
AMSC: Adaptive Masking and Structure-Constraint Learning for Domain Adaptive Semantic Segmentation Under Adverse Conditions,
SPLetters(31), 2024, pp. 181-185.
IEEE DOI 2401
BibRef

Kim, S.[Sunghwan], Kim, D.H.[Dae-Hwan], Kim, H.[Hoseong],
Texture Learning Domain Randomization for Domain Generalized Segmentation,
ICCV23(677-687)
IEEE DOI Code:
WWW Link. 2401
BibRef

Kim, Y.E.[Young-Eun], Lee, Y.W.[Yu-Won], Lee, S.W.[Seong-Whan],
LC-MSM: Language-Conditioned Masked Segmentation Model for unsupervised domain adaptation,
PR(148), 2024, pp. 110201.
Elsevier DOI 2402
Unsupervised domain adaptation, Semantic segmentation, Text-image correlation BibRef

Peng, J.K.[Jun-Kun], Sun, M.J.[Ming-Jie], Lim, E.G.[Eng Gee], Wang, Q.F.[Qiu-Feng], Xiao, J.[Jimin],
Prototype Guided Pseudo Labeling and Perturbation-based Active Learning for domain adaptive semantic segmentation,
PR(148), 2024, pp. 110203.
Elsevier DOI 2402
Domain adaptation, Active learning, Prototype, Perturbation BibRef

Li, J.[Jing], Zhou, K.[Kang], Qian, S.H.[Shen-Han], Li, W.[Wen], Duan, L.X.[Li-Xin], Gao, S.H.[Sheng-Hua],
Feature Re-Representation and Reliable Pseudo Label Retraining for Cross-Domain Semantic Segmentation,
PAMI(46), No. 3, March 2024, pp. 1682-1694.
IEEE DOI 2402
Semantics, Image segmentation, Reliability, Entropy, Feature extraction, Training, Pattern analysis, reliable pseudo label retraining BibRef

Ma, H.Y.[Hao-Yu], Lin, X.R.[Xiang-Ru], Yu, Y.Z.[Yi-Zhou],
I2F: A Unified Image-to-Feature Approach for Domain Adaptive Semantic Segmentation,
PAMI(46), No. 3, March 2024, pp. 1695-1710.
IEEE DOI 2402
Semantic segmentation, Manifolds, Adaptation models, Task analysis, Pipelines, Semantics, Benchmark testing, Category triplet loss, unsupervised domain adaptation BibRef

Luo, X.[Xin], Chen, W.[Wei], Liang, Z.F.[Zheng-Fa], Yang, L.Q.[Long-Qi], Wang, S.W.[Si-Wei], Li, C.[Chen],
Crots: Cross-Domain Teacher-Student Learning for Source-Free Domain Adaptive Semantic Segmentation,
IJCV(132), No. 1, January 2024, pp. 20-39.
Springer DOI 2402
BibRef

Chen, Y.D.[Ya-Dang], Jiang, R.[Ren], Zheng, Y.H.[Yu-Hui], Sheng, B.[Bin], Yang, Z.X.[Zhi-Xin], Wu, E.[Enhua],
Dual Branch Multi-Level Semantic Learning for Few-Shot Segmentation,
IP(33), 2024, pp. 1432-1447.
IEEE DOI 2402
Prototypes, Training, Semantics, Semantic segmentation, Self-supervised learning, Feature extraction, Measurement, metric learning BibRef

Zhu, G.L.[Gui-Lin], Wang, R.[Runmin], Liu, Y.Y.[Ying-Ying], Zhu, Z.[Zhenlin], Gao, C.X.[Chang-Xin], Liu, L.[Li], Sang, N.[Nong],
An Adaptive Post-Processing Network With the Global-Local Aggregation for Semantic Segmentation,
CirSysVideo(34), No. 2, February 2024, pp. 1159-1173.
IEEE DOI Code:
WWW Link. 2402
Context modeling, Semantic segmentation, Task analysis, Predictive models, Transformers, Modeling, Adaptation models, class-aware attention BibRef

Ren, Q.H.[Qing-Hua], Mao, Q.[Qirong], Lu, S.J.[Shi-Jian],
Prototypical Bidirectional Adaptation and Learning for Cross-Domain Semantic Segmentation,
MultMed(26), 2024, pp. 501-513.
IEEE DOI 2402
Prototypes, Semantic segmentation, Feature extraction, Adaptation models, Training, Task analysis, Tail, prototypical learning BibRef

Ma, Y.[You], Chai, L.[Lin], Jin, L.[Lizuo], Yan, J.[Jun],
Hierarchical alignment network for domain adaptive object detection in aerial images,
PandRS(208), 2024, pp. 39-52.
Elsevier DOI Code:
WWW Link. 2402
Object detection, Domain adaptation, Aerial image, Feature alignment, Transfer learning BibRef

Guan, S.X.[Sheng-Xian], Dong, S.[Shuai], Gao, Y.[Yuefang], Zou, K.[Kun],
Category-related attention domain adaptation for one-stage cross-domain object detection,
IET-IPR(18), No. 2, 2024, pp. 362-378.
DOI Link 2402
computer vision, object detection BibRef


Liu, Q.P.[Qi-Peng], Lin, L.J.[Luo-Jun], Shen, Z.F.[Zhi-Feng], Yang, Z.F.[Zhi-Feng],
Periodically Exchange Teacher-Student for Source-Free Object Detection,
ICCV23(6391-6401)
IEEE DOI 2401
BibRef

Zhao, Z.J.[Zi-Jing], Wei, S.[Sitong], Chen, Q.C.[Qing-Chao], Li, D.[Dehui], Yang, Y.F.[Yi-Fan], Peng, Y.X.[Yu-Xin], Liu, Y.[Yang],
Masked Retraining Teacher-Student Framework for Domain Adaptive Object Detection,
ICCV23(18993-19003)
IEEE DOI Code:
WWW Link. 2401
BibRef

Gao, C.L.[Chang-Long], Liu, C.X.[Cheng-Xu], Dun, Y.J.[Yu-Jie], Qian, X.M.[Xue-Ming],
CSDA: Learning Category-Scale Joint Feature for Domain Adaptive Object Detection,
ICCV23(11387-11396)
IEEE DOI 2401
BibRef

Termöhlen, J.A.[Jan-Aike], Bartels, T.[Timo], Fingscheidt, T.[Tim],
A Re-Parameterized Vision Transformer (ReVT) for Domain-Generalized Semantic Segmentation,
OutDistri23(4378-4387)
IEEE DOI 2401
BibRef

Yao, D.[Dongyu], Li, B.[Boheng],
Dual-level Interaction for Domain Adaptive Semantic Segmentation,
Uncertainty23(4529-4538)
IEEE DOI Code:
WWW Link. 2401
BibRef

Alcover-Couso, R.[Roberto], San Miguel, J.C.[Juan C.], Escudero-Viñolo, M.[Marcos],
Biased Class disagreement: detection of out of distribution instances by using differently biased semantic segmentation models,
Uncertainty23(4582-4590)
IEEE DOI 2401
BibRef

Khandelwal, A.[Anant],
SegDA: Maximum Separable Segment Mask with Pseudo Labels for Domain Adaptive Semantic Segmentation,
JRDB23(2150-2160)
IEEE DOI 2401
BibRef

Yin, Y.F.[Yi-Fang], Hu, W.M.[Wen-Miao], Liu, Z.G.[Zhen-Guang], Wang, G.F.[Guan-Feng], Xiang, S.[Shili], Zimmermann, R.[Roger],
CrossMatch: Source-Free Domain Adaptive Semantic Segmentation via Cross-Modal Consistency Training,
ICCV23(21729-21739)
IEEE DOI 2401
BibRef

Huo, X.Y.[Xin-Yue], Xie, L.X.[Ling-Xi], Zhou, W.G.[Wen-Gang], Li, H.Q.[Hou-Qiang], Tian, Q.[Qi],
Focus on Your Target: A Dual Teacher-Student Framework for Domain-adaptive Semantic Segmentation,
ICCV23(18981-18992)
IEEE DOI Code:
WWW Link. 2401
BibRef

Zhao, D.[Dong], Wang, S.[Shuang], Zang, Q.[Qi], Quan, D.[Dou], Ye, X.[Xiutiao], Yang, R.[Rui], Jiao, L.C.[Li-Cheng],
Learning Pseudo-Relations for Cross-domain Semantic Segmentation,
ICCV23(19134-19146)
IEEE DOI Code:
WWW Link. 2401
BibRef

Wang, Y.X.[Yu-Xi], Liang, J.[Jian], Xiao, J.[Jun], Mei, S.Q.[Shu-Qi], Yang, Y.[Yuran], Zhang, Z.X.[Zhao-Xiang],
Informative Data Mining for One-shot Cross-Domain Semantic Segmentation,
ICCV23(1064-1074)
IEEE DOI Code:
WWW Link. 2401
BibRef

Peng, D.[Duo], Hu, P.[Ping], Ke, Q.H.[Qiu-Hong], Liu, J.[Jun],
Diffusion-based Image Translation with Label Guidance for Domain Adaptive Semantic Segmentation,
ICCV23(808-820)
IEEE DOI 2401
BibRef

Miao, J.Z.[Ju-Zheng], Chen, C.[Cheng], Liu, F.[Furui], Wei, H.[Hao], Heng, P.A.[Pheng-Ann],
CauSSL: Causality-Inspired Semi-Supervised Learning for Medical Image Segmentation,
ICCV23(21369-21380)
IEEE DOI Code:
WWW Link. 2401
BibRef

Chang, S.J.[Shu-Jung], Lu, C.Y.[Chen-Yu], Huang, P.K.[Pei-Kai], Hsu, C.T.[Chiou-Ting],
Single-Domain Generalization for Semantic Segmentation Via Dual-Level Domain Augmentation,
ICIP23(2335-2339)
IEEE DOI 2312
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Lu, P.J.[Peggy Joy], Jui, C.Y.[Chia-Yung], Chuang, J.H.[Jen-Hui],
A Privacy-Preserving Approach for Multi-Source Domain Adaptive Object Detection,
ICIP23(1075-1079)
IEEE DOI 2312
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Li, G.[Gang], Zhang, Q.F.[Qi-Fei], Wang, P.Z.[Pei-Zheng], He, R.[Rui], Wu, C.[Chao],
Target-Discriminability-Induced Multi-Source-Free Domain Adaptation,
ICIP23(76-80)
IEEE DOI 2312
BibRef

Ma, Y.Q.[Yu-Qing], Li, H.N.[Hai-Nan], Zhang, Z.[Zhange], Guo, J.Y.[Jin-Yang], Zhang, S.H.[Shang-Hang], Gong, R.H.[Rui-Hao], Liu, X.L.[Xiang-Long],
Annealing-based Label-Transfer Learning for Open World Object Detection,
CVPR23(11454-11463)
IEEE DOI 2309
BibRef

Jain, J.[Jitesh], Li, J.C.[Jia-Chen], Chiu, M.[MangTik], Hassani, A.[Ali], Orlov, N.[Nikita], Shi, H.[Humphrey],
OneFormer: One Transformer to Rule Universal Image Segmentation,
CVPR23(2989-2998)
IEEE DOI 2309
BibRef

Li, F.[Feng], Zhang, H.[Hao], Xu, H.Z.[Huai-Zhe], Liu, S.L.[Shi-Long], Zhang, L.[Lei], Ni, L.M.[Lionel M.], Shum, H.Y.[Heung-Yeung],
Mask DINO: Towards A Unified Transformer-based Framework for Object Detection and Segmentation,
CVPR23(3041-3050)
IEEE DOI 2309
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Gao, Y.P.[Yi-Peng], Lin, K.Y.[Kun-Yu], Yan, J.[Junkai], Wang, Y.[Yaowei], Zheng, W.S.[Wei-Shi],
AsyFOD: An Asymmetric Adaptation Paradigm for Few-Shot Domain Adaptive Object Detection,
CVPR23(3261-3271)
IEEE DOI 2309
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Kennerley, M.[Mikhail], Wang, J.G.[Jian-Gang], Veeravalli, B.[Bharadwaj], Tan, R.T.[Robby T.],
2PCNet: Two-Phase Consistency Training for Day-to-Night Unsupervised Domain Adaptive Object Detection,
CVPR23(11484-11493)
IEEE DOI 2309
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Liu, Y.[Yabo], Wang, J.H.[Jing-Hua], Huang, C.[Chao], Wang, Y.[Yaowei], Xu, Y.[Yong],
CIGAR: Cross-Modality Graph Reasoning for Domain Adaptive Object Detection,
CVPR23(23776-23786)
IEEE DOI 2309
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Ding, J.[Jian], Xue, N.[Nan], Xia, G.S.[Gui-Song], Schiele, B.[Bernt], Dai, D.X.[Deng-Xin],
HGFormer: Hierarchical Grouping Transformer for Domain Generalized Semantic Segmentation,
CVPR23(15413-15423)
IEEE DOI 2309
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Lo, S.Y.[Shao-Yuan], Oza, P.[Poojan], Chennupati, S.[Sumanth], Galindo, A.[Alejandro], Patel, V.M.[Vishal M.],
Spatio-Temporal Pixel-Level Contrastive Learning-based Source-Free Domain Adaptation for Video Semantic Segmentation,
CVPR23(10534-10543)
IEEE DOI 2309
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Hajimiri, S.[Sina], Boudiaf, M.[Malik], Ayed, I.B.[Ismail Ben], Dolz, J.[Jose],
A Strong Baseline for Generalized Few-Shot Semantic Segmentation,
CVPR23(11269-11278)
IEEE DOI 2309
BibRef

He, S.T.[Shu-Ting], Ding, H.H.[Heng-Hui], Jiang, W.[Wei],
Primitive Generation and Semantic-Related Alignment for Universal Zero-Shot Segmentation,
CVPR23(11238-11247)
IEEE DOI 2309
BibRef

Zhao, D.[Dong], Wang, S.[Shuang], Zang, Q.[Qi], Quan, D.[Dou], Ye, X.[Xiutiao], Jiao, L.C.[Li-Cheng],
Towards Better Stability and Adaptability: Improve Online Self-Training for Model Adaptation in Semantic Segmentation,
CVPR23(11733-11743)
IEEE DOI 2309
BibRef

Zhao, Z.[Zhen], Yang, L.[Lihe], Long, S.[Sifan], Pi, J.[Jimin], Zhou, L.P.[Lu-Ping], Wang, J.D.[Jing-Dong],
Augmentation Matters: A Simple-Yet-Effective Approach to Semi-Supervised Semantic Segmentation,
CVPR23(11350-11359)
IEEE DOI 2309
BibRef

Huang, H.M.[Hui-Min], Xie, S.[Shiao], Lin, L.[Lanfen], Tong, R.F.[Ruo-Feng], Chen, Y.W.[Yen-Wei], Li, Y.X.[Yue-Xiang], Wang, H.[Hong], Huang, Y.W.[Ya-Wen], Zheng, Y.F.[Ye-Feng],
SemiCVT: Semi-Supervised Convolutional Vision Transformer for Semantic Segmentation,
CVPR23(11340-11349)
IEEE DOI 2309
BibRef

Liu, S.A.[Sun-Ao], Zhang, Y.H.[Yi-Heng], Qiu, Z.[Zhaofan], Xie, H.T.[Hong-Tao], Zhang, Y.D.[Yong-Dong], Yao, T.[Ting],
Learning Orthogonal Prototypes for Generalized Few-Shot Semantic Segmentation,
CVPR23(11319-11328)
IEEE DOI 2309
BibRef

Shen, F.Y.[Feng-Yi], Gurram, A.[Akhil], Liu, Z.Y.[Zi-Yuan], Wang, H.[He], Knoll, A.[Alois],
DiGA: Distil to Generalize and then Adapt for Domain Adaptive Semantic Segmentation,
CVPR23(15866-15877)
IEEE DOI 2309
BibRef

Kalb, T.[Tobias], Beyerer, J.[Jürgen],
Principles of Forgetting in Domain-Incremental Semantic Segmentation in Adverse Weather Conditions,
CVPR23(19508-19518)
IEEE DOI 2309
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Cardace, A.[Adriano], Ramirez, P.Z.[Pierluigi Zama], Salti, S.[Samuele], Stefano, L.D.[Luigi Di],
Exploiting the Complementarity of 2D and 3D Networks to Address Domain-Shift in 3D Semantic Segmentation,
WAD23(98-109)
IEEE DOI 2309
BibRef

Vidit, V.[Vidit], Engilberge, M.[Martin], Salzmann, M.[Mathieu],
CLIP the Gap: A Single Domain Generalization Approach for Object Detection,
CVPR23(3219-3229)
IEEE DOI 2309
BibRef

Li, T.Y.[Tian-Yu], Roy, S.[Subhankar], Zhou, H.Y.[Hua-Yi], Lu, H.T.[Hong-Tao], Lathuilière, S.[Stéphane],
Contrast, Stylize and Adapt: Unsupervised Contrastive Learning Framework for Domain Adaptive Semantic Segmentation,
L3D-IVU23(4869-4879)
IEEE DOI 2309
BibRef

Cao, S.C.[Sheng-Cao], Joshi, D.[Dhiraj], Gui, L.Y.[Liang-Yan], Wang, Y.X.[Yu-Xiong],
Contrastive Mean Teacher for Domain Adaptive Object Detectors,
CVPR23(23839-23848)
IEEE DOI 2309
BibRef

Shang, C.[Chao], Li, H.L.[Hong-Liang], Meng, F.M.[Fan-Man], Wu, Q.B.[Qing-Bo], Qiu, H.Q.[He-Qian], Wang, L.X.[Lan-Xiao],
Incrementer: Transformer for Class-Incremental Semantic Segmentation with Knowledge Distillation Focusing on Old Class,
CVPR23(7214-7224)
IEEE DOI 2309
BibRef

Geng, H.R.[Hao-Ran], Xu, H.[Helin], Zhao, C.Y.[Cheng-Yang], Xu, C.[Chao], Yi, L.[Li], Huang, S.Y.[Si-Yuan], Wang, H.[He],
GAPartNet: Cross-Category Domain-Generalizable Object Perception and Manipulation via Generalizable and Actionable Parts,
CVPR23(7081-7091)
IEEE DOI 2309
BibRef

Dong, J.H.[Jia-Hua], Zhang, D.[Duzhen], Cong, Y.[Yang], Cong, W.[Wei], Ding, H.H.[Heng-Hui], Dai, D.X.[Deng-Xin],
Federated Incremental Semantic Segmentation,
CVPR23(3934-3943)
IEEE DOI 2309
BibRef

Zhu, L.[Lanyun], Chen, T.R.[Tian-Run], Yin, J.X.[Jian-Xiong], See, S.[Simon], Liu, J.[Jun],
Continual Semantic Segmentation with Automatic Memory Sample Selection,
CVPR23(3082-3092)
IEEE DOI 2309
BibRef

Huang, W.[Wei], Chen, C.[Chang], Li, Y.[Yong], Li, J.C.[Jia-Cheng], Li, C.[Cheng], Song, F.[Fenglong], Yan, Y.[Youliang], Xiong, Z.W.[Zhi-Wei],
Style Projected Clustering for Domain Generalized Semantic Segmentation,
CVPR23(3061-3071)
IEEE DOI 2309
BibRef

Zheng, X.[Xu], Pan, T.[Tianbo], Luo, Y.H.[Yun-Hao], Wang, L.[Lin],
Look at the Neighbor: Distortion-aware Unsupervised Domain Adaptation for Panoramic Semantic Segmentation,
ICCV23(18641-18652)
IEEE DOI 2401
BibRef

Zheng, X.[Xu], Zhu, J.J.[Jin-Jing], Liu, Y.[Yexin], Cao, Z.D.[Zi-Dong], Fu, C.[Chong], Wang, L.[Lin],
Both Style and Distortion Matter: Dual-Path Unsupervised Domain Adaptation for Panoramic Semantic Segmentation,
CVPR23(1285-1295)
IEEE DOI 2309
BibRef

Zhang, H.[Hao], Zhang, R.[Ruimao],
Active Domain Adaptation with Multi-level Contrastive Units for Semantic Segmentation,
ACCV22(VII:448-464).
Springer DOI 2307
BibRef

Nakamura, Y.[Yuzuru], Ishii, Y.[Yasunori], Maruyama, Y.[Yuki], Yamashita, T.[Takayoshi],
Few-shot Adaptive Object Detection with Cross-domain Cutmix,
ACCV22(VI:746-763).
Springer DOI 2307
BibRef

VS, V.[Vibashan], Oza, P.[Poojan], Patel, V.M.[Vishal M.],
Towards Online Domain Adaptive Object Detection,
WACV23(478-488)
IEEE DOI 2302
Training, Representation learning, Adaptation models, Visualization, Source coding, Object detection, Detectors BibRef

Mattolin, G.[Giulio], Zanella, L.[Luca], Ricci, E.[Elisa], Wang, Y.M.[Yi-Ming],
ConfMix: Unsupervised Domain Adaptation for Object Detection via Confidence-based Mixing,
WACV23(423-433)
IEEE DOI 2302
Measurement, Training, Adaptation models, Uncertainty, Codes, Object detection, Algorithms: Machine learning architectures, visual reasoning BibRef

Agarwal, S.[Sharat], Anand, S.[Saket], Arora, C.[Chetan],
Reducing Annotation Effort by Identifying and Labeling Contextually Diverse Classes for Semantic Segmentation Under Domain Shift,
WACV23(5893-5902)
IEEE DOI 2302
Training, Costs, Uncertainty, Annotations, Semantic segmentation, Measurement uncertainty, Visualization BibRef

Xiao, J.W.[Jia-Wen], Zhang, C.B.[Chang-Bin], Feng, J.[Jiekang], Liu, X.[Xialei], van de Weijer, J.[Joost], Cheng, M.M.[Ming-Ming],
Endpoints Weight Fusion for Class Incremental Semantic Segmentation,
CVPR23(7204-7213)
IEEE DOI 2309
BibRef

Goswami, D.[Dipam], Schuster, R.[René], van de Weijer, J.[Joost], Stricker, D.[Didier],
Attribution-aware Weight Transfer: A Warm-Start Initialization for Class-Incremental Semantic Segmentation,
WACV23(3194-3203)
IEEE DOI 2302
Semantic segmentation, Semantics, Deep architecture, Algorithms: Machine learning architectures, formulations, visual reasoning) BibRef

Chung, I.[Inseop], Yoo, J.[Jayeon], Kwak, N.[Nojun],
Exploiting Inter-pixel Correlations in Unsupervised Domain Adaptation for Semantic Segmentation,
RealWorld23(12-21)
IEEE DOI 2302
Knowledge engineering, Correlation, Semantic segmentation, Heuristic algorithms, Conferences, Benchmark testing BibRef

Vandeghen, R.[Renaud], Louppe, G.[Gilles], van Droogenbroeck, M.[Marc],
Adaptive Self-Training for Object Detection,
LIMIT23(914-923)
IEEE DOI Code:
WWW Link. 2401
BibRef

Piérard, S.[Sébastien], Cioppa, A.[Anthony], Halin, A.[Anaïs], Vandeghen, R.[Renaud], Zanella, M.[Maxime], Macq, B.[Benoît], Mahmoudi, S.[Saïd], van Droogenbroeck, M.[Marc],
Mixture Domain Adaptation to Improve Semantic Segmentation in Real-World Surveillance,
RealWorld23(1-10)
IEEE DOI 2302
Adaptation models, Machine learning algorithms, Surveillance, Semantic segmentation, Computational modeling, Machine learning, Probabilistic logic BibRef

Maurya, J.[Jitender], Ranipa, K.R.[Keyur R.], Yamaguchi, O.[Osamu], Shibata, T.[Tomoyuki], Kobayashi, D.[Daisuke],
Domain Adaptation using Self-Training with Mixup for One-Stage Object Detection,
WACV23(4178-4187)
IEEE DOI 2302
Adaptation models, Detectors, Object detection, Benchmark testing, Predictive models, Feature extraction. BibRef

Piva, F.J.[Fabrizio J.], de Geus, D.[Daan], Dubbelman, G.[Gijs],
Empirical Generalization Study: Unsupervised Domain Adaptation vs. Domain Generalization Methods for Semantic Segmentation in the Wild,
WACV23(499-508)
IEEE DOI 2302
Training, Adaptation models, Protocols, Semantic segmentation, Computational modeling, Training data, Applications: Robotics, visual reasoning. BibRef

Liang, J.M.[Jian-Ming], Song, G.L.[Guang-Lu], Leng, B.[Biao], Liu, Y.[Yu],
Unifying Visual Perception by Dispersible Points Learning,
ECCV22(IX:439-456).
Springer DOI 2211

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Fan, Q.[Qi], Pei, W.J.[Wen-Jie], Tai, Y.W.[Yu-Wing], Tang, C.K.[Chi-Keung],
Self-support Few-Shot Semantic Segmentation,
ECCV22(XIX:701-719).
Springer DOI 2211
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Yu, J.Z.[Jin-Ze], Liu, J.M.[Jia-Ming], Wei, X.B.[Xiao-Bao], Zhou, H.Y.[Hao-Yi], Nakata, Y.[Yohei], Gudovskiy, D.[Denis], Okuno, T.[Tomoyuki], Li, J.X.[Jian-Xin], Keutzer, K.[Kurt], Zhang, S.H.[Shang-Hang],
MTTrans: Cross-domain Object Detection with Mean Teacher Transformer,
ECCV22(IX:629-645).
Springer DOI 2211
BibRef

Wu, Z.Y.[Zhen-Yao], Wu, X.[Xinyi], Zhang, X.P.[Xiao-Ping], Ju, L.[Lili], Wang, S.[Song],
SiamDoGe: Domain Generalizable Semantic Segmentation Using Siamese Network,
ECCV22(XXXVIII:603-620).
Springer DOI 2211
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Hoyer, L.[Lukas], Dai, D.X.[Deng-Xin], Van Gool, L.J.[Luc J.],
HRDA: Context-Aware High-Resolution Domain-Adaptive Semantic Segmentation,
ECCV22(XXX:372-391).
Springer DOI 2211
BibRef

Lai, X.[Xin], Tian, Z.T.[Zhuo-Tao], Xu, X.G.[Xiao-Gang], Chen, Y.C.[Ying-Cong], Liu, S.[Shu], Zhao, H.S.[Heng-Shuang], Wang, L.W.[Li-Wei], Jia, J.Y.[Jia-Ya],
DecoupleNet: Decoupled Network for Domain Adaptive Semantic Segmentation,
ECCV22(XXXIII:369-387).
Springer DOI 2211
BibRef

Lyu, S.C.[Shu-Chang], Liu, B.[Binghao], Chen, L.[Lijiang], Zhao, Q.[Qi],
A Similarity Distillation Guided Feature Refinement Network for Few-Shot Semantic Segmentation,
ICIP22(666-670)
IEEE DOI 2211
Visualization, Prototypes, Benchmark testing, Task analysis, Feature consistency, knowledge distillation, feature refinement, few-shot semantic segmentation BibRef

Vibashan, V.S., Oza, P.[Poojan], Patel, V.M.[Vishal M.],
Instance Relation Graph Guided Source-Free Domain Adaptive Object Detection,
CVPR23(3520-3530)
IEEE DOI 2309
BibRef

Vibashan, V.S., Oza, P.[Poojan], Sindagi, V.A.[Vishwanath A.], Patel, V.M.[Vishal M.],
Mixture of Teacher Experts for Source-Free Domain Adaptive Object Detection,
ICIP22(3606-3610)
IEEE DOI 2211
Training, Adaptation models, Uncertainty, Monte Carlo methods, Law, Object detection, Object detection, Domain adaptation, Pseudo-labels BibRef

Park, J.[Jinyoung], Son, M.[Minseok], Lee, S.[Sumin], Kim, C.[Changick],
DAT: Domain Adaptive Transformer for Domain Adaptive Semantic Segmentation,
ICIP22(4183-4187)
IEEE DOI 2211
Training, Adaptive systems, Annotations, Benchmark testing, Transformers, Reliability, Noise measurement, Transformers BibRef

Gong, R.[Rui], Danelljan, M.[Martin], Dai, D.X.[Deng-Xin], Paudel, D.P.[Danda Pani], Chhatkuli, A.[Ajad], Yu, F.[Fisher], Van Gool, L.J.[Luc J.],
TACS: Taxonomy Adaptive Cross-Domain Semantic Segmentation,
ECCV22(XXXIV:19-35).
Springer DOI 2211
BibRef

Jiang, Z.K.[Zheng-Kai], Li, Y.X.[Yu-Xi], Yang, C.[Ceyuan], Gao, P.[Peng], Wang, Y.B.[Ya-Biao], Tai, Y.[Ying], Wang, C.J.[Cheng-Jie],
Prototypical Contrast Adaptation for Domain Adaptive Semantic Segmentation,
ECCV22(XXXIV:36-54).
Springer DOI 2211
BibRef

Zhao, H.[Hanbin], Yang, F.Y.[Feng-Yu], Fu, X.[Xinghe], Li, X.[Xi],
RBC: Rectifying the Biased Context in Continual Semantic Segmentation,
ECCV22(XXXIV:55-72).
Springer DOI 2211
BibRef

Panagiotakopoulos, T.[Theodoros], Dovesi, P.L.[Pier Luigi], Härenstam-Nielsen, L.[Linus], Poggi, M.[Matteo],
Online Domain Adaptation for Semantic Segmentation in Ever-Changing Conditions,
ECCV22(XXXIV:128-146).
Springer DOI 2211
BibRef

Lee, G.[Geon], Eom, C.[Chanho], Lee, W.[Wonkyung], Park, H.[Hyekang], Ham, B.[Bumsub],
Bi-directional Contrastive Learning for Domain Adaptive Semantic Segmentation,
ECCV22(XXX:38-55).
Springer DOI 2211
BibRef

Lei, S.[Shuo], Zhang, X.C.[Xu-Chao], He, J.F.[Jian-Feng], Chen, F.L.[Fang-Lan], Du, B.[Bowen], Lu, C.T.[Chang-Tien],
Cross-Domain Few-Shot Semantic Segmentation,
ECCV22(XXX:73-90).
Springer DOI 2211
BibRef

Wu, T.H.[Tsung-Han], Liou, Y.S.[Yi-Syuan], Yuan, S.J.[Shao-Ji], Lee, H.Y.[Hsin-Ying], Chen, T.I.[Tung-I], Huang, K.C.[Kuan-Chih], Hsu, W.H.[Winston H.],
D2ADA: Dynamic Density-Aware Active Domain Adaptation for Semantic Segmentation,
ECCV22(XXIX:449-467).
Springer DOI 2211
BibRef

Zhao, Y.Y.[Yu-Yang], Zhong, Z.[Zhun], Zhao, N.[Na], Sebe, N.[Nicu], Lee, G.H.[Gim Hee],
Style-Hallucinated Dual Consistency Learning for Domain Generalized Semantic Segmentation,
ECCV22(XXVIII:535-552).
Springer DOI 2211
BibRef

Pan, F.[Fei], Hur, S.[Sungsu], Lee, S.[Seokju], Kim, J.[Junsik], Kweon, I.S.[In So],
ML-BPM: Multi-teacher Learning with Bidirectional Photometric Mixing for Open Compound Domain Adaptation in Semantic Segmentation,
ECCV22(XXXIV:236-251).
Springer DOI 2211
BibRef

Volpi, R.[Riccardo], de Jorge, P.[Pau], Larlus, D.[Diane], Csurka, G.[Gabriela],
On the Road to Online Adaptation for Semantic Image Segmentation,
CVPR22(19162-19173)
IEEE DOI 2210
Representation learning, Image segmentation, Adaptation models, Protocols, Roads, Semantics, Representation learning, Transfer/low-shot/long-tail learning BibRef

Liu, X.Y.[Xin-Yu], Li, W.Y.[Wu-Yang], Yang, Q.S.[Qiu-Shi], Li, B.[Baopu], Yuan, Y.X.[Yi-Xuan],
Towards Robust Adaptive Object Detection under Noisy Annotations,
CVPR22(14187-14196)
IEEE DOI 2210
Training, Adaptation models, Visualization, Upper bound, Annotations, Semantics, Object detection, Recognition: detection, Visual reasoning BibRef

Zhang, M.[Miao], Singh, H.[Harvineet], Chok, L.[Lazarus], Chunara, R.[Rumi],
Segmenting across places: The need for fair transfer learning with satellite imagery,
FaDE-TCV22(2915-2924)
IEEE DOI 2210
Measurement, Adaptation models, Image segmentation, Satellites, Systematics, Transfer learning, Urban areas BibRef

Vasconcelos, C.[Cristina], Birodkar, V.[Vighnesh], Dumoulin, V.[Vincent],
Proper Reuse of Image Classification Features Improves Object Detection,
CVPR22(13618-13627)
IEEE DOI 2210
Training, Schedules, Computational modeling, Transfer learning, Memory management, Object detection, Feature extraction, Transfer/low-shot/long-tail learning BibRef

Li, B.H.[Bang-Huai],
Adaptive Hierarchical Representation Learning for Long-Tailed Object Detection,
CVPR22(2303-2312)
IEEE DOI 2210
Representation learning, Measurement, Training, Adaptation models, Machine vision, Design methodology, Object detection, Transfer/low-shot/long-tail learning BibRef

Lee, M.[Minhyun], Kim, D.[Dongseob], Shim, H.J.[Hyun-Jung],
Threshold Matters in WSSS: Manipulating the Activation for the Robust and Accurate Segmentation Model Against Thresholds,
CVPR22(4320-4329)
IEEE DOI 2210
Image segmentation, Image resolution, Codes, Semantics, Robustness, Pattern recognition, Segmentation, grouping and shape analysis, Self- semi- meta- Transfer/low-shot/long-tail learning BibRef

Kalluri, T.[Tarun], Chandraker, M.[Manmohan],
Cluster-to-adapt: Few Shot Domain Adaptation for Semantic Segmentation across Disjoint Labels,
L3D-IVU22(4120-4130)
IEEE DOI 2210
Training, Image segmentation, Semantics, Minimization, Pattern recognition BibRef

Zhao, L.[Liang], Wang, L.M.[Li-Min],
Task-specific Inconsistency Alignment for Domain Adaptive Object Detection,
CVPR22(14197-14206)
IEEE DOI 2210
Location awareness, Degradation, Codes, Computational modeling, Detectors, Object detection, Recognition: detection, Self- semi- meta- Transfer/low-shot/long-tail learning BibRef

He, M.Z.[Meng-Zhe], Wang, Y.[Yali], Wu, J.X.[Jia-Xi], Wang, Y.[Yiru], Li, H.Q.[Han-Qing], Li, B.[Bo], Gan, W.H.[Wei-Hao], Wu, W.[Wei], Qiao, Y.[Yu],
Cross Domain Object Detection by Target-Perceived Dual Branch Distillation,
CVPR22(9560-9570)
IEEE DOI 2210
Training, Degradation, Object detection, Detectors, Benchmark testing, Pattern recognition, Proposals, retrieval BibRef

Zhou, W.Z.[Wen-Zhang], Du, D.W.[Da-Wei], Zhang, L.[Libo], Luo, T.J.[Tie-Jian], Wu, Y.J.[Yan-Jun],
Multi-Granularity Alignment Domain Adaptation for Object Detection,
CVPR22(9571-9580)
IEEE DOI 2210
Representation learning, Aggregates, Object detection, Detectors, Logic gates, Feature extraction, Recognition: detection, Self- semi- meta- unsupervised learning BibRef

Zhao, Y.Z.[Yi-Zhou], Guo, X.[Xun], Lu, Y.[Yan],
Semantic-aligned Fusion Transformer for One-shot Object Detection,
CVPR22(7591-7601)
IEEE DOI 2210
Correlation, Semantics, Object detection, Computer architecture, Benchmark testing, Transformers, Recognition: detection, Transfer/low-shot/long-tail learning BibRef

Li, S.F.[Shuai-Feng], Ye, M.[Mao], Zhu, X.T.[Xia-Tian], Zhou, L.H.[Li-Hua], Xiong, L.[Lin],
Source-Free Object Detection by Learning to Overlook Domain Style,
CVPR22(8004-8013)
IEEE DOI 2210
Adaptation models, Semantics, Training data, Object detection, Detectors, Self-supervised learning, Predictive models, Self- semi- meta- unsupervised learning BibRef

Lang, C.[Chunbo], Cheng, G.[Gong], Tu, B.[Binfei], Han, J.W.[Jun-Wei],
Learning What Not to Segment: A New Perspective on Few-Shot Segmentation,
CVPR22(8047-8057)
IEEE DOI 2210
Image segmentation, Adaptation models, Sensitivity, Semantics, Predictive models, Performance gain, grouping and shape analysis BibRef

Li, Y.J.[Yu-Jhe], Dai, X.L.[Xiao-Liang], Ma, C.Y.[Chih-Yao], Liu, Y.C.[Yen-Cheng], Chen, K.[Kan], Wu, B.[Bichen], He, Z.J.[Zi-Jian], Kitani, K.[Kris], Vajda, P.[Peter],
Cross-Domain Adaptive Teacher for Object Detection,
CVPR22(7571-7580)
IEEE DOI 2210
Training, Adaptation models, Annotations, Target recognition, Computational modeling, Object detection, Data models, Self- semi- meta- unsupervised learning BibRef

Wu, J.X.[Jia-Xi], Chen, J.X.[Jia-Xin], He, M.Z.[Meng-Zhe], Wang, Y.[Yiru], Li, B.[Bo], Ma, B.Q.[Bing-Qi], Gan, W.H.[Wei-Hao], Wu, W.[Wei], Wang, Y.[Yali], Huang, D.[Di],
Target-Relevant Knowledge Preservation for Multi-Source Domain Adaptive Object Detection,
CVPR22(5291-5300)
IEEE DOI 2210
Knowledge engineering, Degradation, Object detection, Detectors, Benchmark testing, Pattern recognition, Recognition: detection, retrieval BibRef

Liu, Y.[Yahao], Deng, J.H.[Jin-Hong], Tao, J.[Jiale], Chu, T.[Tong], Duan, L.X.[Li-Xin], Li, W.[Wen],
Undoing the Damage of Label Shift for Cross-domain Semantic Segmentation,
CVPR22(7032-7042)
IEEE DOI 2210
Codes, Shape, Semantics, Benchmark testing, Data models, Pattern recognition, Transfer/low-shot/long-tail learning, grouping and shape analysis BibRef

Prabhu, V.[Viraj], Selvaraju, R.R.[Ramprasaath R.], Hoffman, J.[Judy], Naik, N.[Nikhil],
Can domain adaptation make object recognition work for everyone?,
L3D-IVU22(3980-3987)
IEEE DOI 2210
Geography, Adaptation models, Visualization, Image recognition, Computational modeling BibRef

Peng, D.[Duo], Lei, Y.J.[Yin-Jie], Hayat, M.[Munawar], Guo, Y.L.[Yu-Lan], Li, W.[Wen],
Semantic-Aware Domain Generalized Segmentation,
CVPR22(2584-2595)
IEEE DOI 2210
Deep learning, Adaptation models, Image segmentation, Image analysis, Shape, Surface acoustic waves, Semantics, Transfer/low-shot/long-tail learning BibRef

Xu, J.R.[Jia-Rui], de Mello, S.[Shalini], Liu, S.[Sifei], Byeon, W.[Wonmin], Breuel, T.[Thomas], Kautz, J.[Jan], Wang, X.L.[Xiao-Long],
GroupViT: Semantic Segmentation Emerges from Text Supervision,
CVPR22(18113-18123)
IEEE DOI 2210
Representation learning, Image segmentation, Visualization, Shape, Semantics, Object detection, Transformers, Vision + language, Self- semi- meta- unsupervised learning BibRef

Lee, S.H.[Seung-Hun], Choi, W.[Wonhyeok], Kim, C.J.[Chang-Jae], Choi, M.W.[Min-Woo], Im, S.H.[Sung-Hoon],
ADAS: A Direct Adaptation Strategy for Multi-Target Domain Adaptive Semantic Segmentation,
CVPR22(19174-19184)
IEEE DOI 2210
Training, Representation learning, Adaptation models, Image segmentation, Visualization, Semantics, Transfer/low-shot/long-tail learning BibRef

Zhang, J.M.[Jia-Ming], Yang, K.L.[Kai-Lun], Ma, C.X.[Chao-Xiang], Reiß, S.[Simon], Peng, K.Y.[Kun-Yu], Stiefelhagen, R.[Rainer],
Bending Reality: Distortion-aware Transformers for Adapting to Panoramic Semantic Segmentation,
CVPR22(16896-16906)
IEEE DOI 2210
Training, Image segmentation, Adaptation models, Annotations, Shape, Semantics, Transformers, Scene analysis and understanding, Self- semi- meta- unsupervised learning BibRef

Phan, M.H.[Minh Hieu], Ta, T.A.[The-Anh], Phung, S.L.[Son Lam], Tran-Thanh, L.[Long], Bouzerdoum, A.[Abdesselam],
Class Similarity Weighted Knowledge Distillation for Continual Semantic Segmentation,
CVPR22(16845-16854)
IEEE DOI 2210
Deep learning, Representation learning, Shape, Computational modeling, Machine vision, Semantics, Segmentation BibRef

Ji, D.Y.[De-Yi], Wang, H.R.[Hao-Ran], Tao, M.Y.[Ming-Yuan], Huang, J.Q.[Jian-Qiang], Hua, X.S.[Xian-Sheng], Lu, H.T.[Hong-Tao],
Structural and Statistical Texture Knowledge Distillation for Semantic Segmentation,
CVPR22(16855-16864)
IEEE DOI 2210
Knowledge engineering, Quantization (signal), Laplace equations, Image analysis, Shape, Semantics, Force, grouping and shape analysis BibRef

Zhou, B.[Brady], Krähenbühl, P.[Philipp],
Cross-view Transformers for real-time Map-view Semantic Segmentation,
CVPR22(13750-13759)
IEEE DOI 2210
Convolutional codes, Image segmentation, Navigation, Semantics, Computer architecture, Transformers, Navigation and autonomous driving BibRef

Li, R.H.[Rui-Huang], Li, S.[Shuai], He, C.H.[Chen-Hang], Zhang, Y.[Yabin], Jia, X.[Xu], Zhang, L.[Lei],
Class-Balanced Pixel-Level Self-Labeling for Domain Adaptive Semantic Segmentation,
CVPR22(11583-11593)
IEEE DOI 2210
Training, Image segmentation, Statistical analysis, Shape, Semantics, Pipelines, Predictive models, Segmentation, Self- semi- meta- Transfer/low-shot/long-tail learning BibRef

Zhang, W.Q.[Wen-Qiang], Huang, Z.L.[Zi-Long], Luo, G.Z.[Guo-Zhong], Chen, T.[Tao], Wang, X.G.[Xing-Gang], Liu, W.Y.[Wen-Yu], Yu, G.[Gang], Shen, C.H.[Chun-Hua],
TopFormer: Token Pyramid Transformer for Mobile Semantic Segmentation,
CVPR22(12073-12083)
IEEE DOI 2210
Deep learning, Shape, Semantics, Computer architecture, Transformers, Mobile handsets, Deep learning architectures and techniques, grouping and shape analysis BibRef

Liu, Y.[Yuanwei], Liu, N.[Nian], Cao, Q.L.[Qing-Long], Yao, X.[Xiwen], Han, J.W.[Jun-Wei], Shao, L.[Ling],
Learning Non-target Knowledge for Few-shot Semantic Segmentation,
CVPR22(11563-11572)
IEEE DOI 2210
Codes, Shape, Semantics, Prototypes, Object segmentation, Filtering algorithms, Segmentation, grouping and shape analysis, Transfer/low-shot/long-tail learning BibRef

Tian, Z.[Zhuotao], Lai, X.[Xin], Jiang, L.[Li], Liu, S.[Shu], Shu, M.[Michelle], Zhao, H.S.[Heng-Shuang], Jia, J.Y.[Jia-Ya],
Generalized Few-shot Semantic Segmentation,
CVPR22(11553-11562)
IEEE DOI 2210
Training, Image segmentation, Codes, Shape, Semantics, Prototypes, grouping and shape analysis, Representation learning, Segmentation BibRef

Guan, D.[Dayan], Huang, J.X.[Jia-Xing], Xiao, A.[Aoran], Lu, S.J.[Shi-Jian],
Unbiased Subclass Regularization for Semi-Supervised Semantic Segmentation,
CVPR22(9958-9968)
IEEE DOI 2210
Deep learning, Image segmentation, Semantics, Neural networks, Object detection, Logic gates, Semisupervised learning, grouping and shape analysis BibRef

Gao, H.[Huan], Guo, J.C.[Ji-Chang], Wang, G.L.[Guo-Li], Zhang, Q.[Qian],
Cross-Domain Correlation Distillation for Unsupervised Domain Adaptation in Nighttime Semantic Segmentation,
CVPR22(9903-9913)
IEEE DOI 2210
Image segmentation, Correlation, Shape, Semantics, Lighting, Feature extraction, grouping and shape analysis, Self- semi- meta- Segmentation BibRef

Lee, S.[Suhyeon], Seong, H.[Hongje], Lee, S.W.[Seong-Won], Kim, E.T.[Eun-Tai],
WildNet: Learning Domain Generalized Semantic Segmentation from the Wild,
CVPR22(9926-9936)
IEEE DOI 2210
Image segmentation, Codes, Semantics, Pattern recognition, Self- semi- meta- Scene analysis and understanding BibRef

Fan, J.S.[Jia-Shuo], Gao, B.[Bin], Jin, H.[Huan], Jiang, L.H.[Li-Hui],
UCC: Uncertainty guided Cross-head Cotraining for Semi-Supervised Semantic Segmentation,
CVPR22(9937-9946)
IEEE DOI 2210
Training, Deep learning, Uncertainty, Protocols, Semantics, Neural networks, Self- semi- meta- Machine learning BibRef

Huo, X.Y.[Xin-Yue], Xie, L.X.[Ling-Xi], Hu, H.[Hengtong], Zhou, W.G.[Wen-Gang], Li, H.Q.[Hou-Qiang], Tian, Q.[Qi],
Domain-Agnostic Prior for Transfer Semantic Segmentation,
CVPR22(7065-7075)
IEEE DOI 2210
Representation learning, Protocols, Shape, Navigation, Semantics, Training data, Transfer/low-shot/long-tail learning, grouping and shape analysis BibRef

Ren, H.X.[Han-Xiang], Yang, Y.C.[Yan-Chao], Wang, H.[He], Shen, B.[Bokui], Fan, Q.[Qingnan], Zheng, Y.Y.[You-Yi], Liu, C.K.[C. Karen], Guibas, L.J.[Leonidas J.],
ADeLA: Automatic Dense Labeling with Attention for Viewpoint Shift in Semantic Segmentation,
CVPR22(8069-8079)
IEEE DOI 2210
Image segmentation, Uncertainty, Shape, Semantics, Robot vision systems, Object segmentation, Color, Vision applications and systems BibRef

Xie, B.H.[Bin-Hui], Yuan, L.[Longhui], Li, S.[Shuang], Liu, C.H.[Chi Harold], Cheng, X.[Xinjing],
Towards Fewer Annotations: Active Learning via Region Impurity and Prediction Uncertainty for Domain Adaptive Semantic Segmentation,
CVPR22(8058-8068)
IEEE DOI 2210
Image segmentation, Adaptation models, Uncertainty, Annotations, Shape, Impurities, Semantics, Transfer/low-shot/long-tail learning, grouping and shape analysis BibRef

Scherer, S.[Sebastian], Brehm, S.[Stephan], Lienhart, R.[Rainer],
Consistency Regularization for Unsupervised Domain Adaptation in Semantic Segmentation,
CIAP22(I:500-511).
Springer DOI 2205
BibRef

Chen, S.Y.[Si-Yuan],
Conditional Context-Aware Feature Alignment for Domain Adaptive Detection Transformer,
MMMod22(I:272-283).
Springer DOI 2203
BibRef

Wang, X.[Xin], Huang, T.E.[Thomas E.], Liu, B.[Benlin], Yu, F.[Fisher], Wang, X.L.[Xiao-Long], Gonzalez, J.E.[Joseph E.], Darrell, T.J.[Trevor J.],
Robust Object Detection via Instance-Level Temporal Cycle Confusion,
ICCV21(9123-9132)
IEEE DOI 2203
Training, Adaptation models, Lightning, Detectors, Object detection, Benchmark testing, Feature extraction, Detection and localization in 2D and 3D BibRef

Ramamonjison, R.[Rindra], Banitalebi-Dehkordi, A.[Amin], Kang, X.Y.[Xin-Yu], Bai, X.L.[Xiao-Long], Zhang, Y.[Yong],
SimROD: A Simple Adaptation Method for Robust Object Detection,
ICCV21(3550-3559)
IEEE DOI 2203
Adaptation models, Computational modeling, Object detection, Computer architecture, Benchmark testing, Data models, Transfer/Low-shot/Semi/Unsupervised Learning BibRef

Rezaeianaran, F.[Farzaneh], Shetty, R.[Rakshith], Aljundi, R.[Rahaf], Reino, D.O.[Daniel Olmeda], Zhang, S.S.[Shan-Shan], Schiele, B.[Bernt],
Seeking Similarities over Differences: Similarity-based Domain Alignment for Adaptive Object Detection,
ICCV21(9184-9193)
IEEE DOI 2203
Training, Visualization, Computational modeling, Prototypes, Detectors, Object detection, Detection and localization in 2D and 3D BibRef

Jing, T.T.[Tao-Tao], Liu, H.F.[Hong-Fu], Ding, Z.M.[Zheng-Ming],
Towards Novel Target Discovery Through Open-Set Domain Adaptation,
ICCV21(9302-9311)
IEEE DOI 2203
Representation learning, Visualization, Adaptation models, Computational modeling, Semantics, Benchmark testing, Vision + other modalities BibRef

Lin, C.[Chuang], Yuan, Z.H.[Ze-Huan], Zhao, S.C.[Si-Cheng], Sun, P.[Peize], Wang, C.H.[Chang-Hu], Cai, J.F.[Jian-Fei],
Domain-Invariant Disentangled Network for Generalizable Object Detection,
ICCV21(8751-8760)
IEEE DOI 2203
Laser radar, Object detection, Detectors, Benchmark testing, Image reconstruction, Image classification, Representation learning BibRef

Kundu, J.N.[Jogendra Nath], Kulkarni, A.[Akshay], Singh, A.[Amit], Jampani, V.[Varun], Babu, R.V.[R. Venkatesh],
Generalize then Adapt: Source-Free Domain Adaptive Semantic Segmentation,
ICCV21(7026-7036)
IEEE DOI 2203
Training, Art, Target recognition, Semantics, Reliability theory, Benchmark testing, Segmentation, grouping and shape, Transfer/Low-shot/Semi/Unsupervised Learning BibRef

Wang, Y.X.[Yu-Xi], Peng, J.R.[Jun-Ran], Zhang, Z.X.[Zhao-Xiang],
Uncertainty-aware Pseudo Label Refinery for Domain Adaptive Semantic Segmentation,
ICCV21(9072-9081)
IEEE DOI 2203
Training, Adaptation models, Uncertainty, Semantics, Predictive models, Noise measurement, grouping and shape BibRef

Li, S.[Shuang], Xie, M.[Mixue], Lv, F.R.[Fang-Rui], Liu, C.H.[Chi Harold], Liang, J.[Jian], Qin, C.[Chen], Li, W.[Wei],
Semantic Concentration for Domain Adaptation,
ICCV21(9082-9091)
IEEE DOI 2203
Adaptation models, Annotations, Semantics, Predictive models, Benchmark testing, Feature extraction, Adversarial learning BibRef

Tian, K.[Kun], Zhang, C.H.[Cheng-Hao], Wang, Y.[Ying], Xiang, S.M.[Shi-Ming], Pan, C.H.[Chun-Hong],
Knowledge Mining and Transferring for Domain Adaptive Object Detection,
ICCV21(9113-9122)
IEEE DOI 2203
Training, Degradation, Adaptation models, Correlation, Focusing, Detectors, Object detection, Representation learning BibRef

Truong, T.D.[Thanh-Dat], Le, N.[Ngan], Raj, B.[Bhiksha], Cothren, J.[Jackson], Luu, K.[Khoa],
FREDOM: Fairness Domain Adaptation Approach to Semantic Scene Understanding,
CVPR23(19988-19997)
IEEE DOI 2309
BibRef

Truong, T.D.[Thanh-Dat], Duong, C.N.[Chi Nhan], Le, N.[Ngan], Phung, S.L.[Son Lam], Rainwater, C.[Chase], Luu, K.[Khoa],
BiMaL: Bijective Maximum Likelihood Approach to Domain Adaptation in Semantic Scene Segmentation,
ICCV21(8528-8537)
IEEE DOI 2203
Measurement, Adaptation models, Computational modeling, Semantics, Benchmark testing, Minimization, grouping and shape BibRef

Shin, I.[Inkyu], Kim, D.J.[Dong-Jin], Cho, J.W.[Jae Won], Woo, S.[Sanghyun], Park, K.Y.[Kwan-Yong], Kweon, I.S.[In So],
LabOR: Labeling Only if Required for Domain Adaptive Semantic Segmentation,
ICCV21(8568-8578)
IEEE DOI 2203
Degradation, Adaptation models, Costs, Semantics, Labeling, Transfer/Low-shot/Semi/Unsupervised Learning, Scene analysis and understanding BibRef

Guizilini, V.[Vitor], Li, J.[Jie], Ambrus, R.[Rares], Gaidon, A.[Adrien],
Geometric Unsupervised Domain Adaptation for Semantic Segmentation,
ICCV21(8517-8527)
IEEE DOI 2203
Bridges, Visualization, Semantics, Estimation, Benchmark testing, Multitasking, Transfer/Low-shot/Semi/Unsupervised Learning, Vision for robotics and autonomous vehicles BibRef

Peng, D.[Duo], Lei, Y.J.[Yin-Jie], Li, W.[Wen], Zhang, P.P.[Ping-Ping], Guo, Y.L.[Yu-Lan],
Sparse-to-dense Feature Matching: Intra and Inter domain Cross-modal Learning in Domain Adaptation for 3D Semantic Segmentation,
ICCV21(7088-7097)
IEEE DOI 2203
Point cloud compression, Training, Image segmentation, Semantics, Adversarial machine learning, Probability distribution, Transfer/Low-shot/Semi/Unsupervised Learning BibRef

Chen, C.Q.[Chao-Qi], Li, J.C.[Jiong-Cheng], Zheng, Z.B.[Ze-Biao], Huang, Y.[Yue], Ding, X.[Xinghao], Yu, Y.Z.[Yi-Zhou],
Dual Bipartite Graph Learning: A General Approach for Domain Adaptive Object Detection,
ICCV21(2683-2692)
IEEE DOI 2203
Training, Adaptation models, Semantics, Pipelines, Detectors, Object detection, Benchmark testing, Transfer/Low-shot/Semi/Unsupervised Learning BibRef

Yao, X.X.[Xing-Xu], Zhao, S.C.[Si-Cheng], Xu, P.F.[Peng-Fei], Yang, J.F.[Ju-Feng],
Multi-Source Domain Adaptation for Object Detection,
ICCV21(3253-3262)
IEEE DOI 2203
Adaptation models, Annotations, Supervised learning, Object detection, Feature extraction, Approximation algorithms, BibRef

Zhang, H.[Hui], Ding, H.H.[Heng-Hui],
Prototypical Matching and Open Set Rejection for Zero-Shot Semantic Segmentation,
ICCV21(6954-6963)
IEEE DOI 2203
Training, Visualization, Semantics, Prototypes, Segmentation, grouping and shape, BibRef

Baek, D.[Donghyeon], Oh, Y.[Youngmin], Ham, B.[Bumsub],
Exploiting a Joint Embedding Space for Generalized Zero-Shot Semantic Segmentation,
ICCV21(9516-9525)
IEEE DOI 2203
Visualization, Semantics, Prototypes, Transforms, Benchmark testing, Calibration, Transfer/Low-shot/Semi/Unsupervised Learning, grouping and shape BibRef

Cheng, J.X.[Jia-Xin], Nandi, S.[Soumyaroop], Natarajan, P.[Prem], Abd-Almageed, W.[Wael],
SIGN: Spatial-information Incorporated Generative Network for Generalized Zero-shot Semantic Segmentation,
ICCV21(9536-9546)
IEEE DOI 2203
Training, Image segmentation, Image coding, Annealing, Semantics, Government, Benchmark testing, grouping and shape BibRef

Lu, Z.[Zhihe], He, S.[Sen], Zhu, X.T.[Xia-Tian], Zhang, L.[Li], Song, Y.Z.[Yi-Zhe], Xiang, T.[Tao],
Simpler is Better: Few-shot Semantic Segmentation with Classifier Weight Transformer,
ICCV21(8721-8730)
IEEE DOI 2203
Training, Image segmentation, Adaptation models, Continuous wavelet transforms, Semantics, Transformers, grouping and shape BibRef

Tjio, G.[Gabriel], Liu, P.[Ping], Zhou, J.T.Y.[Joey Tian-Yi], Goh, R.S.M.[Rick Siow Mong],
Adversarial Semantic Hallucination for Domain Generalized Semantic Segmentation,
WACV22(3849-3858)
IEEE DOI 2202
Training, Image segmentation, Data privacy, Codes, Semantics, Ash, Grouping and Shape BibRef

Kuznietsov, Y.[Yevhen], Proesmans, M.[Marc], Van Gool, L.J.[Luc J.],
Towards Unsupervised Online Domain Adaptation for Semantic Segmentation,
Novelty22(261-271)
IEEE DOI 2202
Adaptation models, Conferences, Semantics, Pipelines, Training data, Predictive models BibRef

Klingner, M.[Marvin], Termöhlen, J.A.[Jan-Aike], Ritterbach, J.[Jacob], Fingscheidt, T.[Tim],
Unsupervised BatchNorm Adaptation (UBNA): A Domain Adaptation Method for Semantic Segmentation Without Using Source Domain Representations,
Novelty22(210-220)
IEEE DOI 2202
Training, Knowledge engineering, Adaptation models, Image segmentation, Semantics, Network architecture BibRef

Zhang, Y.Z.[Yi-Zhe], Borse, S.[Shubhankar], Cai, H.[Hong], Porikli, F.M.[Fatih M.],
AuxAdapt: Stable and Efficient Test-Time Adaptation for Temporally Consistent Video Semantic Segmentation,
WACV22(2633-2642)
IEEE DOI 2202
Adaptation models, Uncertainty, Semantics, Neural networks, Estimation, Streaming media, Stability analysis, Segmentation, Semi- and Un- supervised Learning BibRef

Cardace, A.[Adriano], Ramirez, P.Z.[Pierluigi Zama], Salti, S.[Samuele], di Stefano, L.[Luigi],
Shallow Features Guide Unsupervised Domain Adaptation for Semantic Segmentation at Class Boundaries,
WACV22(2010-2020)
IEEE DOI 2202
Deep learning, Semantics, Neural networks, Task analysis, Transfer, Few-shot, Grouping and Shape BibRef

Chung, I.[Inseop], Kim, D.[Daesik], Kwak, N.[Nojun],
Maximizing Cosine Similarity Between Spatial Features for Unsupervised Domain Adaptation in Semantic Segmentation,
WACV22(1979-1988)
IEEE DOI 2202
Image segmentation, Head, Dictionaries, Semantics, Feature extraction, Task analysis, Segmentation, Scene Understanding BibRef

Garg, P.[Prachi], Saluja, R.[Rohit], Balasubramanian, V.N.[Vineeth N], Arora, C.[Chetan], Subramanian, A.[Anbumani], Jawahar, C.V.,
Multi-Domain Incremental Learning for Semantic Segmentation,
WACV22(2080-2090)
IEEE DOI 2202
Visualization, Roads, Semantics, Computer architecture, Interference, Stability analysis, Semi- and Un- supervised Learning BibRef

Bevandic, P.[Petra], Oršic, M.[Marin], Grubišic, I.[Ivan], Šaric, J.[Josip], Šegvic, S.[Siniša],
Multi-domain semantic segmentation with overlapping labels *,
WACV22(2422-2431)
IEEE DOI 2202
Training, Visualization, Roads, Taxonomy, Semantics, Training data, Benchmark testing, Semi- and Un- supervised Learning BibRef

Razani, R.[Ryan], Cheng, R.[Ran], Li, E.[Enxu], Taghavi, E.[Ehsan], Ren, Y.[Yuan], Liu, B.B.[Bing-Bing],
GP-S3Net: Graph-based Panoptic Sparse Semantic Segmentation Network,
ICCV21(16056-16065)
IEEE DOI 2203
Laser radar, Convolution, Semantics, Benchmark testing, Computational efficiency, Scene analysis and understanding, Vision for robotics and autonomous vehicles BibRef

Cheng, R.[Ran], Razani, R.[Ryan], Taghavi, E.[Ehsan], Li, E.[Enxu], Liu, B.B.[Bing-Bing],
(AF)2-S3Net: Attentive Feature Fusion with Adaptive Feature Selection for Sparse Semantic Segmentation Network,
CVPR21(12542-12551)
IEEE DOI 2111
Learning systems, Laser radar, Fuses, Roads, Semantics, Feature extraction BibRef

Zhang, P.[Pan], Zhang, B.[Bo], Zhang, T.[Ting], Chen, D.[Dong], Wang, Y.[Yong], Wen, F.[Fang],
Prototypical Pseudo Label Denoising and Target Structure Learning for Domain Adaptive Semantic Segmentation,
CVPR21(12409-12419)
IEEE DOI 2111
Training, Adaptation models, Codes, Supervised learning, Semantics, Noise reduction, Prototypes BibRef

Zhang, Y.X.[Yi-Xin], Wang, Z.[Zilei], Mao, Y.S.[Yu-Shi],
RPN Prototype Alignment For Domain Adaptive Object Detector,
CVPR21(12420-12429)
IEEE DOI 2111
Degradation, Prototypes, Detectors, Object detection, Feature extraction, Pattern recognition BibRef

Chen, S.J.[Shuai-Jun], Jia, X.[Xu], He, J.Z.[Jian-Zhong], Shi, Y.J.[Yong-Jie], Liu, J.Z.[Jian-Zhuang],
Semi-supervised Domain Adaptation based on Dual-level Domain Mixing for Semantic Segmentation,
CVPR21(11013-11022)
IEEE DOI 2111
Training, Adaptation models, Image segmentation, Costs, Semantics, Benchmark testing BibRef

Zhang, Q.[Qiang], Zhao, S.[Shenlu], Luo, Y.J.[Yong-Jiang], Zhang, D.W.[Ding-Wen], Huang, N.Z.[Nian-Zchang], Han, J.G.[Jun-Gong],
ABMDRNet: Adaptive-weighted Bi-directional Modality Difference Reduction Network for RGB-T Semantic Segmentation,
CVPR21(2633-2642)
IEEE DOI 2111
Image segmentation, Technological innovation, Fuses, Semantics, Lighting, Imaging BibRef

Liu, Y.[Yuang], Zhang, W.[Wei], Wang, J.[Jun],
Source-Free Domain Adaptation for Semantic Segmentation,
CVPR21(1215-1224)
IEEE DOI 2111
Adaptation models, Image segmentation, Semantics, Benchmark testing, Pattern recognition, Convolutional neural networks BibRef

Yang, J.Y.[Jin-Yu], An, W.Z.[Wei-Zhi], Yan, C.C.[Chao-Chao], Zhao, P.L.[Pei-Lin], Huang, J.Z.[Jun-Zhou],
Context-Aware Domain Adaptation in Semantic Segmentation,
WACV21(514-524)
IEEE DOI 2106
Adaptation models, Aggregates, Semantics BibRef

Huang, J.X.[Jia-Xing], Lu, S.J.[Shi-Jian], Guan, D.[Dayan], Zhang, X.B.[Xiao-Bing],
Contextual-relation Consistent Domain Adaptation for Semantic Segmentation,
ECCV20(XV:705-722).
Springer DOI 2011
BibRef

Subhani, M.N.[M. Naseer], Ali, M.[Mohsen],
Learning from Scale-invariant Examples for Domain Adaptation in Semantic Segmentation,
ECCV20(XXII:290-306).
Springer DOI 2011
BibRef

Yang, J.Y.[Jin-Yu], An, W.Z.[Wei-Zhi], Wang, S.[Sheng], Zhu, X.L.[Xin-Liang], Yan, C.C.[Chao-Chao], Huang, J.Z.[Jun-Zhou],
Label-driven Reconstruction for Domain Adaptation in Semantic Segmentation,
ECCV20(XXVII:480-498).
Springer DOI 2011
BibRef

Paul, S.[Sujoy], Tsai, Y.H.[Yi-Hsuan], Schulter, S.[Samuel], Roy-Chowdhury, A.K.[Amit K.], Chandraker, M.[Manmohan],
Domain Adaptive Semantic Segmentation Using Weak Labels,
ECCV20(IX:571-587).
Springer DOI 2011
BibRef

Pan, F., Shin, I., Rameau, F., Lee, S., Kweon, I.S.,
Unsupervised Intra-Domain Adaptation for Semantic Segmentation Through Self-Supervision,
CVPR20(3763-3772)
IEEE DOI 2008
Adaptation models, Entropy, Image segmentation, Semantics, Generators, Data models, Task analysis BibRef

Yang, Y., Soatto, S.,
FDA: Fourier Domain Adaptation for Semantic Segmentation,
CVPR20(4084-4094)
IEEE DOI 2008
Semantics, Image segmentation, Training, Entropy, Adaptation models, Task analysis, Frequency-domain analysis BibRef

Wang, Z., Wei, Y., Feris, R., Xiong, J., Hwu, W., Huang, T.S., Shi, H.,
Alleviating Semantic-level Shift: A Semi-supervised Domain Adaptation Method for Semantic Segmentation,
VL3W20(4043-4047)
IEEE DOI 2008
Semantics, Task analysis, Adaptation models, Image segmentation, Training, Feature extraction, Urban areas BibRef

Luo, Y., Liu, P., Guan, T., Yu, J., Yang, Y.,
Significance-Aware Information Bottleneck for Domain Adaptive Semantic Segmentation,
ICCV19(6777-6786)
IEEE DOI 2004
feature extraction, image classification, image segmentation, neural nets, unsupervised learning, Data mining BibRef

Lin, Y.X.[Yong-Xiang], Tan, D.S.[Daniel Stanley], Cheng, W.H.[Wen-Huang], Chen, Y.Y.[Yung-Yao], Hua, K.L.[Kai-Lung],
Spatially-Aware Domain Adaptation for Semantic Segmentation of Urban Scenes,
ICIP19(1870-1874)
IEEE DOI 1910
Semantic segmentation, Domain adaptation, Spatial Structure BibRef

Lv, F.M.[Feng-Mao], Lian, Q.[Qing], Yang, G.[Guowu], Lin, G.S.[Guo-Sheng], Pan, S.J.[Sinno Jialin], Duan, L.X.[Li-Xin],
Domain Adaptive Semantic Segmentation Through Structure Enhancement,
TASKCV18(II:172-179).
Springer DOI 1905
BibRef

Zou, Y.[Yang], Yu, Z.D.[Zhi-Ding], Kumar, B.V.K.V.[B. V. K. Vijaya], Wang, J.S.[Jin-Song],
Unsupervised Domain Adaptation for Semantic Segmentation via Class-Balanced Self-training,
ECCV18(III: 297-313).
Springer DOI 1810
BibRef

Chapter on 2-D Region Segmentation Techniques, Snakes, Active Contours continues in
Remote Sensing Semantic Segmentation .


Last update:Feb 29, 2024 at 09:13:14