8.6.3 Semantic Segmentation, Label and Segment Together

Chapter Contents (Back)
Semantic Segmentation.
See also Domain Adaption for Semantic Segmentation.
See also Remote Sensing, Aerial Imagery, Semantic Segmentation.
See also Boundary Detection for Semantic Segmentation, Border Analysis.
See also Neural Networks for Segmentation.
See also Efficient Semantic Segmentation, Real-Time Segmentation.
See also Neural Networks for Semantic Segmentation.
See also Video Semantic Object Segmentation.
See also Weakly Supervised, Self Supervised Semantic Segmentation.
See also Semi-Supervised Semantic Segmentation.
See also Medical Image Semantic Segmentation.

Osuna-Enciso, V.[Valentín],
Bioinspired metaheuristics for image segmentation,
ELCVIA(13), No. 2, 2014, pp. xx-yy.
DOI Link 1407
Ph.D.. Thesis. BibRef

Wang, L.[Le], Hua, G.[Gang], Xue, J.R.[Jian-Ru], Gao, Z.N.[Zhan-Ning], Zheng, N.N.[Nan-Ning],
Joint Segmentation and Recognition of Categorized Objects From Noisy Web Image Collection,
IP(23), No. 9, September 2014, pp. 4070-4086.
IEEE DOI 1410
image retrieval BibRef

Gould, S.[Stephen], He, X.M.[Xu-Ming],
Scene Understanding by Labeling Pixels,
CACM(57), No. 11, November 2014, pp. 68-77.
DOI Link 1411
Pixels labeled with a scene's semantics and geometry let computers describe what they see. BibRef

Liu, Z.[Zhi], Xu, S.Q.[Shu-Qiong], Zhang, Y.[Yun], Chen, C.L.P.,
A Multiple-Feature and Multiple-Kernel Scene Segmentation Algorithm for Humanoid Robot,
Cyber(44), No. 11, November 2014, pp. 2232-2241.
IEEE DOI 1411
Gabor filters BibRef

Kang, H., Hebert, M., Efros, A.A., Kanade, T.,
Data-Driven Objectness,
PAMI(37), No. 1, January 2015, pp. 189-195.
IEEE DOI 1412
Databases. Is it an object, not a specific object. BibRef

Wang, L.L.[Li-Li], Yung, N.H.C.[Nelson H.C.],
Hybrid graphical model for semantic image segmentation,
JVCIR(28), No. 1, 2015, pp. 83-96.
Elsevier DOI 1503
Semantic segmentation BibRef

Wang, L.L.[Li-Li], Yung, N.H.C.[Nelson H. C.],
Improved hierarchical conditional random field model for object segmentation,
MVA(26), No. 7-8, November 2015, pp. 1027-1043.
WWW Link. 1511
BibRef

Xia, W.[Wei], Domokos, C.[Csaba], Cheong, L.F.[Loong-Fah], Yan, S.C.[Shui-Cheng],
Background Context Augmented Hypothesis Graph for Object Segmentation,
CirSysVideo(25), No. 4, April 2015, pp. 582-594.
IEEE DOI 1504
Context BibRef

Xia, W.[Wei], Domokos, C.[Csaba], Xiong, J., Cheong, L.F.[Loong-Fah], Yan, S.C.[Shui-Cheng],
Segmentation Over Detection via Optimal Sparse Reconstructions,
CirSysVideo(25), No. 8, August 2015, pp. 1295-1308.
IEEE DOI 1508
Bismuth BibRef

Xia, W.[Wei], Domokos, C.[Csaba], Dong, J.[Jian], Cheong, L.F.[Loong-Fah], Yan, S.C.[Shui-Cheng],
Semantic Segmentation without Annotating Segments,
ICCV13(2176-2183)
IEEE DOI 1403
Given object bounding box. BibRef

Kumar, M.P., Turki, H., Preston, D., Koller, D.,
Parameter Estimation and Energy Minimization for Region-Based Semantic Segmentation,
PAMI(37), No. 7, July 2015, pp. 1373-1386.
IEEE DOI 1506
Biological system modeling BibRef

Zou, W.B.[Wen-Bin], Liu, Z.[Zhi], Kpalma, K.[Kidiyo], Ronsin, J.[Joseph], Zhao, Y.[Yong], Komodakis, N.[Nikos],
Unsupervised Joint Salient Region Detection and Object Segmentation,
IP(24), No. 11, November 2015, pp. 3858-3873.
IEEE DOI 1509
BibRef
And: A1, A3, A4, Only:
Semantic image segmentation using region bank,
ICPR12(922-925).
WWW Link. 1302
BibRef
And: A1, A3, A4, Only:
Semantic segmentation via sparse coding over hierarchical regions,
ICIP12(2577-2580).
IEEE DOI 1302
Markov processes Hierarchical region segmentation, sparse coding of regions for recognition. BibRef

Mottaghi, R.[Roozbeh], Fidler, S.[Sanja], Yuille, A.L., Urtasun, R.[Raquel], Parikh, D.[Devi],
Human-Machine CRFs for Identifying Bottlenecks in Scene Understanding,
PAMI(38), No. 1, January 2016, pp. 74-87.
IEEE DOI 1601
Analytical models BibRef

Mottaghi, R.[Roozbeh], Fidler, S.[Sanja], Yao, J.[Jian], Urtasun, R.[Raquel], Parikh, D.[Devi],
Analyzing Semantic Segmentation Using Hybrid Human-Machine CRFs,
CVPR13(3143-3150)
IEEE DOI 1309
Explore effects by using humans in loop for parts of the problem. BibRef

Ravě, D., Bober, M., Farinella, G.M., Guarnera, M., Battiato, S.,
Semantic segmentation of images exploiting DCT based features and random forest,
PR(52), No. 1, 2016, pp. 260-273.
Elsevier DOI 1601
Semantic segmentation BibRef

Zarchi, M.S., Tan, R.T., van Gemeren, C.[Coert], Monadjemi, A., Veltkamp, R.C.[Remco C.],
Understanding image concepts using ISTOP model,
PR(53), No. 1, 2016, pp. 174-183.
Elsevier DOI 1602
Visual term. Image parsing. BibRef

Zand, M., Doraisamy, S., Halin, A.A.[A. Abdul], Mustaffa, M.R.,
Ontology-Based Semantic Image Segmentation Using Mixture Models and Multiple CRFs,
IP(25), No. 7, July 2016, pp. 3233-3248.
IEEE DOI 1606
image segmentation BibRef

Zhang, J.[Jing], Mu, Y.K.[Ya-Kun], Feng, S.W.[Sheng-Wei], Li, K.H.[Ke-Huang], Yuan, Y.[Yubo], Lee, C.H.[Chin-Hui],
Image region annotation based on segmentation and semantic correlation analysis,
IET-IPR(12), No. 8, August 2018, pp. 1331-1337.
DOI Link 1808
BibRef

Shi, H., Li, H., Meng, F., Wu, Q., Xu, L., Ngan, K.N.,
Hierarchical Parsing Net: Semantic Scene Parsing From Global Scene to Objects,
MultMed(20), No. 10, October 2018, pp. 2670-2682.
IEEE DOI 1810
backpropagation, feature extraction, image classification, image coding, local appearance features, contextual feature, context learning BibRef

Noormohamadi, N.[Neda], Adibi, P.[Peyman], Ehsani, S.M.S.[Sayyed Mohammad Saeed],
Semantic image segmentation using an improved hierarchical graphical model,
IET-IPR(12), No. 11, November 2018, pp. 1943-1950.
DOI Link 1810
BibRef

Ates, H.F.[Hasan F.], Sunetci, S.[Sercan],
Multi-hypothesis contextual modeling for semantic segmentation,
PRL(117), 2019, pp. 104-110.
Elsevier DOI 1901
Image parsing, Segmentation, Superpixel, MRF BibRef

Blott, G.[Gregor], Takami, M.[Masato], Heipke, C.[Christian],
Semantic Segmentation of Fisheye Images,
CVRoads18(I:181-196).
Springer DOI 1905
BibRef

Li, X., Ma, H., Luo, X.,
Weaklier Supervised Semantic Segmentation With Only One Image Level Annotation per Category,
IP(29), No. 1, 2020, pp. 128-141.
IEEE DOI 1910
image recognition, image segmentation, object recognition, supervised learning, weaklier supervised semantic segmentation, dual-branch iterative learning BibRef

Arunkumar, M.[Manonmani], Pushparaj, V.[Vijayakumari],
Seed picking crossover optimisation algorithm for semantic segmentation from images,
IET-IPR(14), No. 11, September 2020, pp. 2503-2511.
DOI Link 2009
BibRef
And: Erratum (adds the authors): IET-IPR(15), No. 13, November, pp. 3410-3410.
DOI Link 2110
BibRef

Lian, X.[Xuhang], Pang, Y.W.[Yan-Wei], Han, J.G.[Jun-Gong], Pan, J.[Jing],
Cascaded hierarchical atrous spatial pyramid pooling module for semantic segmentation,
PR(110), 2021, pp. 107622.
Elsevier DOI 2011
Semantic segmentation, Atrous convolution, Atrous spatial pyramid pooling(ASPP), Cascaded module BibRef

Pemasiri, A.[Akila], Nguyen, K.[Kien], Sridharan, S.[Sridha], Fookes, C.[Clinton],
Multi-modal semantic image segmentation,
CVIU(202), 2021, pp. 103085.
Elsevier DOI 2012
Segmentation, X-ray, Mask R-CNN, Neural networks BibRef

Tasar, O., Giros, A., Tarabalka, Y., Alliez, P., Clerc, S.,
DAugNet: Unsupervised, Multisource, Multitarget, and Life-Long Domain Adaptation for Semantic Segmentation of Satellite Images,
GeoRS(59), No. 2, February 2021, pp. 1067-1081.
IEEE DOI 2101
Satellites, Training, Semantics, Image segmentation, Adaptation models, Remote sensing, Standardization, semantic segmentation BibRef

Zhou, W., Wang, Y., Chu, J., Yang, J., Bai, X., Xu, Y.,
Affinity Space Adaptation for Semantic Segmentation Across Domains,
IP(30), 2021, pp. 2549-2561.
IEEE DOI 2102
Semantics, Image segmentation, Cleaning, Annotations, Adaptation models, Data models, Training, affinity relationship BibRef

Huang, L.[Li], He, M.L.[Mei-Ling], Tan, C.[Chong], Jiang, D.[Du], Li, G.F.[Gong-Fa], Yu, H.[Hui],
Special Issue Retraction: Jointly network image processing: multi-task image semantic segmentation of indoor scene based on CNN,
IET-IPR(17), No. 1, January 2023, pp. 301.
DOI Link 2301
BibRef
And: IET-IPR(14), No. 15, 15 December 2020, pp. 3689-3697.
DOI Link 2103
BibRef

Zheng, Z.D.[Zhe-Dong], Yang, Y.[Yi],
Rectifying Pseudo Label Learning via Uncertainty Estimation for Domain Adaptive Semantic Segmentation,
IJCV(129), No. 4, April 2021, pp. 1106-1120.
Springer DOI 2104
BibRef

Ji, J.[Jian], Shi, R.[Rui], Li, S.T.[Si-Tong], Chen, P.[Peng], Miao, Q.G.[Qi-Guang],
Encoder-Decoder With Cascaded CRFs for Semantic Segmentation,
CirSysVideo(31), No. 5, 2021, pp. 1926-1938.
IEEE DOI 2105
BibRef

Yan, J.B.[Jie-Bin], Zhong, Y.[Yu], Fang, Y.M.[Yu-Ming], Wang, Z.Y.[Zhang-Yang], Ma, K.D.[Ke-De],
Exposing Semantic Segmentation Failures via Maximum Discrepancy Competition,
IJCV(129), No. 5, May 2021, pp. 1768-1786.
Springer DOI 2105
BibRef

Feng, Y.C.[Ying-Chao], Sun, X.[Xian], Diao, W.H.[Wen-Hui], Li, J.[Jihao], Gao, X.[Xin],
Double Similarity Distillation for Semantic Image Segmentation,
IP(30), 2021, pp. 5363-5376.
IEEE DOI 2106
Knowledge engineering, Image segmentation, Correlation, Semantics, Task analysis, Complexity theory, Training, convolutional neural networks BibRef

Hu, J.[Jie], Kong, H.F.[Hui-Fang], Fan, L.[Lei], Zhou, J.[Jun],
Enhancing feature fusion with spatial aggregation and channel fusion for semantic segmentation,
IET-CV(15), No. 6, 2021, pp. 418-427.
DOI Link 2108
BibRef

Tang, Q.[Quan], Liu, F.G.[Fa-Gui], Zhang, T.[Tong], Jiang, J.[Jun], Zhang, Y.[Yu],
Attention-guided chained context aggregation for semantic segmentation,
IVC(115), 2021, pp. 104309.
Elsevier DOI 2110
Semantic segmentation, Multi-scale contexts, Series-parallel hybrid streams, Convolutional networks BibRef

Cai, L.[Lile], Xu, X.[Xun], Zhang, L.N.[Li-Ning], Foo, C.S.[Chuan-Sheng],
Exploring Spatial Diversity for Region-Based Active Learning,
IP(30), 2021, pp. 8702-8712.
IEEE DOI 2110
Uncertainty, Spatial diversity, Semantics, Image segmentation, Task analysis, Labeling, Annotations, Active learning, semantic segmentation BibRef

Zhang, J.[Jian], Qi, L.[Lei], Shi, Y.H.[Ying-Huan], Gao, Y.[Yang],
Generalizable model-agnostic semantic segmentation via target-specific normalization,
PR(122), 2022, pp. 108292.
Elsevier DOI 2112
Domain generalization, Semantic segmentation, Model-agnostic learning, Target-specific normalization BibRef

Yu, L.T.[Li-Tao], Li, Z.B.[Zhi-Bin], Xu, M.[Min], Gao, Y.S.[Yong-Sheng], Luo, J.B.[Jie-Bo], Zhang, J.[Jian],
Distribution-Aware Margin Calibration for Semantic Segmentation in Images,
IJCV(130), No. 1, January 2022, pp. 95-110.
Springer DOI 2201
BibRef

Zhou, Q.[Quan], Wu, X.F.[Xiao-Fu], Zhang, S.F.[Suo-Fei], Kang, B.[Bin], Ge, Z.Y.[Zong-Yuan], Latecki, L.J.[Longin Jan],
Contextual ensemble network for semantic segmentation,
PR(122), 2022, pp. 108290.
Elsevier DOI 2112
Ensemble deconvolution, Semantic segmentation, FCNs, Context aggregation, Encoder-decoder networks BibRef

Liu, X.F.[Xiao-Feng], Lu, Y.H.[Yun-Hong], Liu, X.C.[Xiong-Chang], Bai, S.[Song], Li, S.[Site], You, J.[Jane],
Wasserstein Loss With Alternative Reinforcement Learning for Severity-Aware Semantic Segmentation,
ITS(23), No. 1, January 2022, pp. 587-596.
IEEE DOI 2201
Automobiles, Measurement, Roads, Semantics, Optimization, Training, Histograms, Semantic segmentation, autonomous driving, actor-critic BibRef

Liu, X.F.[Xiao-Feng], Ji, W.X.[Wen-Xuan], You, J.[Jane], El Fakhri, G.[Georges], Woo, J.H.[Jong-Hye],
Severity-Aware Semantic Segmentation With Reinforced Wasserstein Training,
CVPR20(12563-12572)
IEEE DOI 2008
Semantics, Autonomous vehicles, Measurement, Automobiles, Histograms, Training, Roads BibRef

Ma, T.Q.[Tian-Qi], Wang, Q.L.[Qi-Long], Zhang, H.Z.[Hong-Zhi], Zuo, W.M.[Wang-Meng],
Delving Deeper Into Pixel Prior for Box-Supervised Semantic Segmentation,
IP(31), 2022, pp. 1406-1417.
IEEE DOI 2202
Annotations, Semantics, Image segmentation, Training, Benchmark testing, Predictive models, Convolution, multiple instance learning BibRef

Ge, C.[Ce], Sun, H.F.[Hai-Feng], Song, Y.Z.[Yi-Zhe], Ma, Z.Y.[Zhan-Yu], Liao, J.X.[Jian-Xin],
Exploring Local Detail Perception for Scene Sketch Semantic Segmentation,
IP(31), 2022, pp. 1447-1461.
IEEE DOI 2202
Image segmentation, Semantics, Automobiles, Layout, Task analysis, Feature extraction, Airplanes, Sketch dataset, scene sketch, local detail perception BibRef

Sakaridis, C.[Christos], Dai, D.X.[Deng-Xin], Van Gool, L.J.[Luc J.],
Map-Guided Curriculum Domain Adaptation and Uncertainty-Aware Evaluation for Semantic Nighttime Image Segmentation,
PAMI(44), No. 6, June 2022, pp. 3139-3153.
IEEE DOI 2205
BibRef
Earlier:
Guided Curriculum Model Adaptation and Uncertainty-Aware Evaluation for Semantic Nighttime Image Segmentation,
ICCV19(7373-7382)
IEEE DOI 2004
Semantics, Image segmentation, Adaptation models, Annotations, Task analysis, Measurement, Lighting, Domain adaptation, curriculum learning. image annotation, learning (artificial intelligence), Uncertainty BibRef

Chen, M.H.[Ming-Hong], Shu, R.J.[Rui-Jun], Zhu, D.C.[Dong-Chen], Li, J.[Jiamao], Zhang, X.L.[Xiao-Lin],
CSF: Closed-mask-guided semantic fusion method for semantic perception of unknown scenes,
PRL(161), 2022, pp. 101-107.
Elsevier DOI 2209
Semantic fusion, Information entropy, Mask completion, Semantic segmentation BibRef

Zhang, X.[Xian], Li, Q.[Qiang], Quan, Z.B.[Zhi-Bin], Yang, W.K.[Wan-Kou],
Pyramid Geometric Consistency Learning For Semantic Segmentation,
PR(133), 2023, pp. 109020.
Elsevier DOI 2210
Semantic segmentation, Consistency learning, Supervised contrastive learning BibRef

Gao, G.Y.[Guang-Yu], Fang, Z.Y.[Zhi-Yuan], Han, C.[Cen], Wei, Y.C.[Yun-Chao], Liu, C.H.[Chi Harold], Yan, S.C.[Shui-Cheng],
DRNet: Double Recalibration Network for Few-Shot Semantic Segmentation,
IP(31), 2022, pp. 6733-6746.
IEEE DOI 2211
Convolution, Task analysis, Prototypes, Heating systems, Annotations, Image color analysis, Robustness, Few-shot learning, weakly-supervised learning BibRef

Li, Z.C.[Ze-Chao], Sun, Y.P.[Yan-Ping], Zhang, L.Y.[Li-Yan], Tang, J.H.[Jin-Hui],
CTNet: Context-Based Tandem Network for Semantic Segmentation,
PAMI(44), No. 12, December 2022, pp. 9904-9917.
IEEE DOI 2212
Semantics, Image segmentation, Feature extraction, Correlation, Computational modeling, Task analysis, Convolution, tandem network BibRef

Tian, Z.T.[Zhuo-Tao], Chen, P.G.[Peng-Guang], Lai, X.[Xin], Jiang, L.[Li], Liu, S.[Shu], Zhao, H.S.[Heng-Shuang], Yu, B.[Bei], Yang, M.C.[Ming-Chang], Jia, J.Y.[Jia-Ya],
Adaptive Perspective Distillation for Semantic Segmentation,
PAMI(45), No. 2, February 2023, pp. 1372-1387.
IEEE DOI 2301
Semantics, Feature extraction, Training, Predictive models, Adaptation models, Avalanche photodiodes, Context modeling, semantic segmentation BibRef

Cai, Y.X.[Yu-Xiang], Yu, Y.[Yuanlong], Jiang, W.J.[Wei-Jie], Chen, R.[Rong], Zheng, W.T.[Wei-Tao], Wu, X.[Xi], Su, R.J.[Ren-Jie],
A novel decoder based on Bayesian rules for task-driven object segmentation,
IET-IPR(17), No. 3, 2023, pp. 832-848.
DOI Link 2303
BibRef

Huang, Z.L.[Zi-Long], Wang, X.G.[Xing-Gang], Wei, Y.C.[Yun-Chao], Huang, L.C.[Li-Chao], Shi, H.[Humphrey], Liu, W.Y.[Wen-Yu], Huang, T.S.[Thomas S.],
CCNet: Criss-Cross Attention for Semantic Segmentation,
PAMI(45), No. 6, June 2023, pp. 6896-6908.
IEEE DOI 2305
Semantics, Task analysis, Aggregates, Benchmark testing, Lips, Image segmentation, Context modeling, Semantic segmentation, context modeling BibRef

Gao, S.H.[Shang-Hua], Li, Z.Y.[Zhong-Yu], Yang, M.H.[Ming-Hsuan], Cheng, M.M.[Ming-Ming], Han, J.W.[Jun-Wei], Torr, P.H.S.[Philip H.S.],
Large-Scale Unsupervised Semantic Segmentation,
PAMI(45), No. 6, June 2023, pp. 7457-7476.
IEEE DOI 2305
Task analysis, Semantics, Benchmark testing, Shape, Annotations, Representation learning, Training, Large-scale, unsupervised BibRef

Liu, J.S.[Jin-Shi], Jiang, Z.H.[Zhao-Hui], Cao, T.[Ting], Chen, Z.W.[Zhi-Wen], Zhang, C.[Chaobo], Gui, W.H.[Wei-Hua],
Generated Pseudo-Labels Guided by Background Skeletons for Overcoming Under-Segmentation in Overlapping Particle Objects,
CirSysVideo(33), No. 6, June 2023, pp. 2906-2919.
IEEE DOI 2306
Image segmentation, Skeleton, Training, Data models, Semantic segmentation, Task analysis, Training data, leaf vertices BibRef

An, T.H.[Taeg-Hyun], Kang, J.Y.[Jung-Yu], Min, K.W.[Kyoung-Wook],
Network adaptation for color image semantic segmentation,
IET-IPR(17), No. 10, 2023, pp. 2972-2983.
DOI Link 2308
computer vision, image colour analysis, image segmentation BibRef

Zhang, F.Y.[Feng-Yu], Panahi, A.[Ashkan], Gao, G.J.[Guang-Jun],
FsaNet: Frequency Self-Attention for Semantic Segmentation,
IP(32), 2023, pp. 4757-4772.
IEEE DOI 2309
BibRef

He, H.Y.[Hao-Yu], Cai, J.F.[Jian-Fei], Pan, Z.Z.[Zi-Zheng], Liu, J.[Jing], Zhang, J.[Jing], Tao, D.C.[Da-Cheng], Zhuang, B.[Bohan],
Dynamic Focus-aware Positional Queries for Semantic Segmentation,
CVPR23(11299-11308)
IEEE DOI 2309
BibRef

Zhao, D.[Danpei], Yuan, B.[Bo], Shi, Z.W.[Zhen-Wei],
Inherit With Distillation and Evolve With Contrast: Exploring Class Incremental Semantic Segmentation Without Exemplar Memory,
PAMI(45), No. 10, October 2023, pp. 11932-11947.
IEEE DOI 2310
BibRef

Dong, Z.[Zihao], Fang, T.[Tiyu], Li, J.P.[Jin-Ping], Shao, X.L.[Xiu-Li],
Weakly supervised fine-grained semantic segmentation via spatial correlation-guided learning,
CVIU(236), 2023, pp. 103815.
Elsevier DOI 2310
Weakly supervised semantic segmentation, Spatial correlation-guided learning, Multi-view clustering BibRef

Chen, J.C.[Jia-Cheng], Gao, B.B.[Bin-Bin], Lu, Z.Q.[Zong-Qing], Xue, J.H.[Jing-Hao], Wang, C.J.[Cheng-Jie], Liao, Q.M.[Qing-Min],
APANet: Adaptive Prototypes Alignment Network for Few-Shot Semantic Segmentation,
MultMed(25), 2023, pp. 4361-4373.
IEEE DOI 2310
BibRef

Lin, F.J.[Fang-Jian], Liang, Z.H.[Zhan-Hao], Wu, S.[Sitong], He, J.J.[Jun-Jun], Chen, K.[Kai], Tian, S.W.[Sheng-Wei],
StructToken: Rethinking Semantic Segmentation With Structural Prior,
CirSysVideo(33), No. 10, October 2023, pp. 5655-5663.
IEEE DOI 2310
BibRef

Nguyen, K.[Khang], Do, K.[Kien], Vu, T.[Truong], Than, K.[Khoat],
Unsupervised image segmentation with robust virtual class contrast,
PRL(173), 2023, pp. 10-16.
Elsevier DOI 2310
Unsupervised image segmentation, Contrastive learning BibRef

Hu, Y.[Yutao], Huang, X.[Xin], Luo, X.Y.[Xiao-Yan], Han, J.G.[Jun-Gong], Cao, X.B.[Xian-Bin], Zhang, J.[Jun],
Learning Foreground Information Bottleneck for few-shot semantic segmentation,
PR(146), 2024, pp. 109993.
Elsevier DOI 2311
Information bottleneck, Semantic segmentation, Few-shot learning, Feature undermining BibRef

Zhang, L.L.[Ling-Ling], Zhang, X.Y.[Xin-Yu], Wang, Q.[Qianying], Wu, W.J.[Wen-Jun], Chang, X.J.[Xiao-Jun], Liu, J.[Jun],
RPMG-FSS: Robust Prior Mask Guided Few-Shot Semantic Segmentation,
CirSysVideo(33), No. 11, November 2023, pp. 6609-6621.
IEEE DOI Code:
WWW Link. 2311
BibRef

Wang, R.G.[Rong-Gui], Yang, C.[Cong], Yang, J.[Juan], Xue, L.X.[Li-Xia],
FPIseg: Iterative segmentation network based on feature pyramid for few-shot segmentation,
IET-IPR(17), No. 13, 2023, pp. 3801-3814.
DOI Link 2311
attention mechanism, feature engineering, feature pyramid network, few-shot semantic segmentation, prototype network BibRef

Liu, W.[Weide], Zhang, C.[Chi], Ding, H.H.[Heng-Hui], Hung, T.Y.[Tzu-Yi], Lin, G.S.[Guo-Sheng],
Few-Shot Segmentation With Optimal Transport Matching and Message Flow,
MultMed(25), 2023, pp. 5130-5141.
IEEE DOI 2311
BibRef

Tan, W.M.[Wei-Min], Ru, G.H.[Gang-Hui], Jiang, Y.M.[Yue-Ming], Li, J.C.[Ji-Chun], Yan, B.[Bo],
Rethinking and Improving Few-Shot Segmentation From a Contour-Aware Perspective,
MultMed(25), 2023, pp. 6917-6929.
IEEE DOI Code:
WWW Link. 2311
BibRef

Zheng, Y.[Yu], Zhou, F.[Fugen], Liang, S.[Shangying], Song, W.T.[Wen-Tao], Bai, X.Z.[Xiang-Zhi],
Semantic Segmentation in Thermal Videos: A New Benchmark and Multi-Granularity Contrastive Learning-Based Framework,
ITS(24), No. 12, December 2023, pp. 14783-14799.
IEEE DOI Code:
HTML Version. 2312
BibRef

Ma, Y.D.[Ying-Dong], Jing, N.[Nan],
Semantic segmentation with cross convolution and multi-layer feature refinement,
JVCIR(97), 2023, pp. 103971.
Elsevier DOI 2312
Semantic segmentation, Cross convolution, Multi-scale context, Feature fusion BibRef

Chen, B.[Bike], Peng, W.[Wei], Cao, X.F.[Xiao-Feng], Röning, J.[Juha],
Hyperbolic Uncertainty Aware Semantic Segmentation,
ITS(25), No. 2, February 2024, pp. 1275-1290.
IEEE DOI 2402
Uncertainty, Training, Estimation, Computational modeling, Semantic segmentation, Drones, Task analysis, Hyperbolic space, autonomous drones BibRef

Zhu, Y.[Yi], Zhang, Z.Y.[Zhong-Yue], Wu, C.[Chongruo], Zhang, Z.[Zhi], He, T.[Tong], Zhang, H.[Hang], Manmatha, R., Li, M.[Mu], Smola, A.[Alexander],
Improving Semantic Segmentation via Efficient Self-Training,
PAMI(46), No. 3, March 2024, pp. 1589-1602.
IEEE DOI 2402
Training, Semantics, Computational modeling, Image segmentation, Data models, Schedules, Predictive models, Semantic segmentation, cross-domain generalization BibRef

Chen, L.[Lei], Dai, H.[Huhe], Zheng, Y.[Yuan],
RAFNet: Reparameterizable Across-Resolution Fusion Network for Real-Time Image Semantic Segmentation,
CirSysVideo(34), No. 2, February 2024, pp. 1212-1227.
IEEE DOI 2402
Decoding, Semantic segmentation, Real-time systems, Feature extraction, Training, Task analysis, Mobile handsets, hardware deployment BibRef

Du, Z.R.[Zhuo-Ran], Wei, S.[Shikui], Liu, T.[Ting], Zhang, S.[Shunli], Chen, X.T.[Xiao-Tong], Zhang, S.Y.[Shi-Yin], Zhao, Y.[Yao],
Exploring the Applicability of Spectral Recovery in Semantic Segmentation of RGB Images,
MultMed(26), 2024, pp. 1932-1943.
IEEE DOI 2402
Hyperspectral imaging, Semantic segmentation, Task analysis, Semantics, Image color analysis, Feature extraction, Data mining, semantic segmentation BibRef

Ding, H.X.[Hai-Xin], Zhang, S.[Shengchuan], Wu, Q.[Qiong], Yu, S.[Songlin], Hu, J.[Jie], Cao, L.J.[Liu-Juan], Ji, R.R.[Rong-Rong],
Bilateral Knowledge Interaction Network for Referring Image Segmentation,
MultMed(26), 2024, pp. 2966-2977.
IEEE DOI 2402
Image segmentation, Visualization, Kernel, Knowledge engineering, Feature extraction, Semantics, Convolution, vision-language BibRef

Zhang, X.[Xian], Quan, Z.B.[Zhi-Bin], Li, Q.[Qiang], Zhu, D.J.[De-Jun], Yang, W.K.[Wan-Kou],
SED: Searching Enhanced Decoder with switchable skip connection for semantic segmentation,
PR(149), 2024, pp. 110196.
Elsevier DOI 2403
NAS, Semantic segmentation, Encoder-decoder model BibRef

Li, L.L.[Liu-Lei], Wang, W.G.[Wen-Guan], Zhou, T.F.[Tian-Fei], Quan, R.J.[Rui-Jie], Yang, Y.[Yi],
Semantic Hierarchy-Aware Segmentation,
PAMI(46), No. 4, April 2024, pp. 2123-2138.
IEEE DOI 2403
Semantics, Semantic segmentation, Visualization, Task analysis, Training, Computer architecture, Adaptation models, semantic segmentation BibRef

Cong, W.[Wei], Cong, Y.[Yang], Dong, J.H.[Jia-Hua], Sun, G.[Gan], Ding, H.H.[Heng-Hui],
Gradient-Semantic Compensation for Incremental Semantic Segmentation,
MultMed(26), 2024, pp. 5561-5574.
IEEE DOI 2404
Semantics, Semantic segmentation, Dogs, Prototypes, Training, Task analysis, Heuristic algorithms, Gradient compensation, semantic segmentation BibRef

Karine, A.[Ayoub], Napoléon, T.[Thibault], Jridi, M.[Maher],
Channel-spatial knowledge distillation for efficient semantic segmentation,
PRL(180), 2024, pp. 48-54.
Elsevier DOI Code:
WWW Link. 2404
Semantic segmentation, Lightweight deep learning, Self-attention distillation, Centered kernel alignment BibRef

Yuan, H.C.[Hao-Chen], Peng, J.J.[Jun-Jie],
LCSeg-Net: A low-contrast images semantic segmentation model with structural and frequency spectrum information,
PR(151), 2024, pp. 110428.
Elsevier DOI 2404
Image semantic segmentation, Low-contrast image, Structural information enhancement, Feature adaptive fusion BibRef

Chen, J.L.[Jia-Lei], Deguchi, D.[Daisuke], Zhang, C.[Chenkai], Zheng, X.[Xu], Murase, H.[Hiroshi],
Frozen is better than learning: A new design of prototype-based classifier for semantic segmentation,
PR(152), 2024, pp. 110431.
Elsevier DOI 2405
Frozen prototype, Contrastive learning, Representation learning, Semantic segmentation BibRef

Ma, Y.D.[Ying-Dong], Lan, X.B.[Xia-Bin],
Semantic segmentation using cross-stage feature reweighting and efficient self-attention,
IVC(145), 2024, pp. 104996.
Elsevier DOI 2405
Semantic segmentation, Convolutional neural networks, Transformer, Feature fusion and reweighting BibRef

Zhang, D.[Dong], Lin, Y.[Yi], Tang, J.H.[Jin-Hui], Cheng, K.T.[Kwang-Ting],
CAE-GReaT: Convolutional-Auxiliary Efficient Graph Reasoning Transformer for Dense Image Predictions,
IJCV(132), No. 5, May 2024, pp. 1502-1520.
Springer DOI 2405
BibRef


Alexandropoulos, S.[Stamatis], Sakaridis, C.[Christos], Maragos, P.[Petros],
OVeNet: Offset Vector Network for Semantic Segmentation,
WACV24(7392-7403)
IEEE DOI Code:
WWW Link. 2404
Visualization, Shape, Semantic segmentation, Semantics, Benchmark testing, Predictive models, Performance gain, Autonomous Driving BibRef

Maag, K.[Kira], Fischer, A.[Asja],
Uncertainty-weighted Loss Functions for Improved Adversarial Attacks on Semantic Segmentation,
WACV24(3894-3902)
IEEE DOI 2404
Analytical models, Semantic segmentation, Perturbation methods, Computational modeling, Artificial neural networks, Autonomous Driving BibRef

Hariat, M.[Marwane], Laurent, O.[Olivier], Kazmierczak, R.[Rémi], Zhang, S.H.[Shi-Hao], Bursuc, A.[Andrei], Yao, A.[Angela], Franchi, G.[Gianni],
Learning to generate training datasets for robust semantic segmentation,
WACV24(3882-3893)
IEEE DOI 2404
Training, Semantic segmentation, Perturbation methods, Computer network reliability, Transformers, Datasets and evaluations BibRef

Liu, Y.[Yuang], Zhou, Q.[Qiang], Wang, J.[Jing], Wang, Z.B.[Zhi-Bin], Wang, F.[Fan], Wang, J.[Jun], Zhang, W.[Wei],
Dynamic Token-Pass Transformers for Semantic Segmentation,
WACV24(1816-1825)
IEEE DOI Code:
WWW Link. 2404
Costs, Semantic segmentation, Semantics, Predictive models, Transformers, Feature extraction, Throughput, Algorithms, Image recognition and understanding BibRef

Khoshsirat, S.[Seyedalireza], Kambhamettu, C.[Chandra],
Improving Normalization with the James-Stein Estimator,
WACV24(2030-2040)
IEEE DOI 2404
Visualization, Semantic segmentation, Estimation, Transformers, Vectors, Algorithms, Machine learning architectures, formulations, Image recognition and understanding BibRef

Qin, M.H.[Ming-Hai], Sun, C.[Chao], Hofmann, J.[Jaco], Vucinic, D.[Dejan],
DISCO: Distributed Inference with Sparse Communications,
WACV24(2421-2429)
IEEE DOI 2404
Computational modeling, Semantic segmentation, Memory management, Superresolution, Artificial neural networks, Parallel processing BibRef

Li, Q.[Qi], Yang, W.X.[Wei-Xiang], Liu, W.X.[Wen-Xi], Yu, Y.L.[Yuan-Long], He, S.F.[Sheng-Feng],
From Contexts to Locality: Ultra-high Resolution Image Segmentation via Locality-aware Contextual Correlation,
ICCV21(7232-7241)
IEEE DOI 2203
Image segmentation, Image resolution, Correlation, Codes, Computational modeling, Semantics, Segmentation, Scene analysis and understanding BibRef

Hu, R., Dollár, P., He, K., Darrell, T.J., Girshick, R.[Ross],
Learning to Segment Every Thing,
CVPR18(4233-4241)
IEEE DOI 1812
Training, Task analysis, Visualization, Transfer functions, Predictive models, Image segmentation, Genomics BibRef

Hariharan, B.[Bharath], Arbeláez, P.[Pablo], Girshick, R.[Ross], Malik, J.[Jitendra],
Simultaneous Detection and Segmentation,
ECCV14(VII: 297-312).
Springer DOI 1408

See also Indoor Scene Understanding with RGB-D Images: Bottom-up Segmentation, Object Detection and Semantic Segmentation. BibRef

Arbelaez, P.[Pablo], Hariharan, B.[Bharath], Gu, C.H.[Chun-Hui], Gupta, S.[Saurabh], Bourdev, L.[Lubomir], Malik, J.[Jitendra],
Semantic segmentation using regions and parts,
CVPR12(3378-3385).
IEEE DOI 1208
BibRef

Li, Z.[Ziyi], Zhou, Q.[Qinye], Zhang, X.Y.[Xiao-Yun], Zhang, Y.[Ya], Wang, Y.F.[Yan-Feng], Xie, W.[Weidi],
Open-vocabulary Object Segmentation with Diffusion Models,
ICCV23(7633-7642)
IEEE DOI 2401
BibRef

Zhang, D.[Dan], Sakmann, K.[Kaspar], Beluch, W.[William], Hutmacher, R.[Robin], Li, Y.[Yumeng],
Anomaly-Aware Semantic Segmentation via Style-Aligned OoD Augmentation,
BRAVO23(4067-4075)
IEEE DOI 2401
BibRef

Wu, J.N.[Jian-Nan], Jiang, Y.[Yi], Yan, B.[Bin], Lu, H.C.[Hu-Chuan], Yuan, Z.H.[Ze-Huan], Luo, P.[Ping],
Segment Every Reference Object in Spatial and Temporal Spaces,
ICCV23(2538-2550)
IEEE DOI 2401
Referring image segmentation BibRef

Hu, Y.[Yutao], Wang, Q.X.[Qi-Xiong], Shao, W.Q.[Wen-Qi], Xie, E.[Enze], Li, Z.G.[Zhen-Guo], Han, J.G.[Jun-Gong], Luo, P.[Ping],
Beyond One-to-One: Rethinking the Referring Image Segmentation,
ICCV23(4044-4054)
IEEE DOI Code:
WWW Link. 2401
BibRef

Lee, J.[Jungbeom], Lee, S.J.[Sung-Jin], Nam, J.[Jinseok], Yu, S.[Seunghak], Do, J.[Jaeyoung], Taghavi, T.[Tara],
Weakly Supervised Referring Image Segmentation with Intra-Chunk and Inter-Chunk Consistency,
ICCV23(21813-21824)
IEEE DOI 2401
BibRef

Liu, F.[Fang], Liu, Y.H.[Yu-Hao], Kong, Y.Q.[Yu-Qiu], Xu, K.[Ke], Zhang, L.[Lihe], Yin, B.C.[Bao-Cai], Hancke, G.[Gerhard], Lau, R.[Rynson],
Referring Image Segmentation Using Text Supervision,
ICCV23(22067-22077)
IEEE DOI Code:
WWW Link. 2401
BibRef

Xu, Z.[Zunnan], Chen, Z.H.[Zhi-Hong], Zhang, Y.[Yong], Song, Y.B.[Yi-Bing], Wan, X.[Xiang], Li, G.B.[Guan-Bin],
Bridging Vision and Language Encoders: Parameter-Efficient Tuning for Referring Image Segmentation,
ICCV23(17457-17466)
IEEE DOI Code:
WWW Link. 2401
BibRef

Zbinden, L.[Lukas], Doorenbos, L.[Lars], Pissas, T.[Theodoros], Huber, A.T.[Adrian Thomas], Sznitman, R.[Raphael], Márquez-Neila, P.[Pablo],
Stochastic Segmentation with Conditional Categorical Diffusion Models,
ICCV23(1119-1129)
IEEE DOI 2401
BibRef

Zhu, M.[Muzhi], Li, H.[Hengtao], Chen, H.[Hao], Fan, C.X.[Cheng-Xiang], Mao, W.[Weian], Jing, C.C.[Chen-Chen], Liu, Y.F.[Yi-Fan], Shen, C.H.[Chun-Hua],
SegPrompt: Boosting Open-world Segmentation via Category-level Prompt Learning,
ICCV23(999-1008)
IEEE DOI Code:
WWW Link. 2401
BibRef

Zhang, H.[Hao], Li, F.[Feng], Zou, X.[Xueyan], Liu, S.[Shilong], Li, C.Y.[Chun-Yuan], Yang, J.W.[Jian-Wei], Zhang, L.[Lei],
A Simple Framework for Open-Vocabulary Segmentation and Detection,
ICCV23(1020-1031)
IEEE DOI Code:
WWW Link. 2401
BibRef

Zhang, Z.K.[Ze-Kang], Gao, G.Y.[Guang-Yu], Jiao, J.B.[Jian-Bo], Liu, C.H.[Chi Harold], Wei, Y.C.[Yun-Chao],
CoinSeg: Contrast Inter- and Intra- Class Representations for Incremental Segmentation,
ICCV23(843-853)
IEEE DOI Code:
WWW Link. 2401
BibRef

Nayal, N.[Nazir], Yavuz, M.[Misra], Henriques, J.F.[Joăo F.], Güney, F.[Fatma],
RbA: Segmenting Unknown Regions Rejected by All,
ICCV23(711-722)
IEEE DOI Code:
WWW Link. 2401
BibRef

Xia, R.[Ruihao], Zhao, C.Q.[Chao-Qiang], Zheng, M.[Meng], Wu, Z.Y.[Zi-Yan], Sun, Q.Y.[Qi-Yu], Tang, Y.[Yang],
CMDA: Cross-Modality Domain Adaptation for Nighttime Semantic Segmentation,
ICCV23(21515-21524)
IEEE DOI Code:
WWW Link. 2401
BibRef

Wei, Z.X.[Zhi-Xiang], Chen, L.[Lin], Tu, T.[Tao], Ling, P.Y.[Peng-Yang], Chen, H.[Huaian], Jin, Y.[Yi],
Disentangle then Parse: Night-time Semantic Segmentation with Illumination Disentanglement,
ICCV23(21536-21546)
IEEE DOI Code:
WWW Link. 2401
BibRef

Huang, K.[Kai], Wang, F.[Feigege], Xi, Y.[Ye], Gao, Y.[Yutao],
Prototypical Kernel Learning and Open-set Foreground Perception for Generalized Few-shot Semantic Segmentation,
ICCV23(19199-19208)
IEEE DOI 2401
BibRef

Colomer, M.B.[Marc Botet], Dovesi, P.L.[Pier Luigi], Panagiotakopoulos, T.[Theodoros], Carvalho, J.F.[Joao Frederico], Härenstam-Nielsen, L.[Linus], Azizpour, H.[Hossein], Kjellström, H.[Hedvig], Cremers, D.[Daniel], Poggi, M.[Matteo],
To Adapt or Not to Adapt? Real-Time Adaptation for Semantic Segmentation,
ICCV23(16502-16513)
IEEE DOI 2401
BibRef

Liu, Y.[Yinhe], Shi, S.[Sunan], Wang, J.[Junjue], Zhong, Y.F.[Yan-Fei],
Seeing Beyond the Patch: Scale-Adaptive Semantic Segmentation of High-resolution Remote Sensing Imagery based on Reinforcement Learning,
ICCV23(16822-16832)
IEEE DOI 2401
BibRef

Bruggemann, D.[David], Sakaridis, C.[Christos], Brödermann, T.[Tim], Van Gool, L.J.[Luc J.],
Contrastive Model Adaptation for Cross-Condition Robustness in Semantic Segmentation,
ICCV23(11344-11353)
IEEE DOI Code:
WWW Link. 2401
BibRef

Han, C.[Cong], Zhong, Y.J.[Yu-Jie], Li, D.J.[Deng-Jie], Han, K.[Kai], Ma, L.[Lin],
Open-Vocabulary Semantic Segmentation with Decoupled One-Pass Network,
ICCV23(1086-1096)
IEEE DOI Code:
WWW Link. 2401
BibRef

Cai, K.X.[Kai-Xin], Ren, P.Z.[Peng-Zhen], Zhu, Y.[Yi], Xu, H.[Hang], Liu, J.Z.[Jian-Zhuang], Li, C.[Changlin], Wang, G.R.[Guang-Run], Liang, X.D.[Xiao-Dan],
MixReorg: Cross-Modal Mixed Patch Reorganization is a Good Mask Learner for Open-World Semantic Segmentation,
ICCV23(1196-1205)
IEEE DOI 2401
BibRef

Wu, W.J.[Wei-Jia], Zhao, Y.Z.[Yu-Zhong], Shou, M.Z.[Mike Zheng], Zhou, H.[Hong], Shen, C.H.[Chun-Hua],
DiffuMask: Synthesizing Images with Pixel-level Annotations for Semantic Segmentation Using Diffusion Models,
ICCV23(1206-1217)
IEEE DOI 2401
BibRef

Kim, H.[Hoyoung], Oh, M.[Minhyeon], Hwang, S.[Sehyun], Kwak, S.[Suha], Ok, J.[Jungseul],
Adaptive Superpixel for Active Learning in Semantic Segmentation,
ICCV23(943-953)
IEEE DOI 2401
BibRef

Liu, Y.[Yuhe], Liu, C.J.[Chuan-Jian], Han, K.[Kai], Tang, Q.[Quan], Qin, Z.[Zengchang],
Boosting Semantic Segmentation from the Perspective of Explicit Class Embeddings,
ICCV23(821-831)
IEEE DOI Code:
WWW Link. 2401
BibRef

Chen, J.[Jun], Zhu, D.[Deyao], Qian, G.C.[Guo-Cheng], Ghanem, B.[Bernard], Yan, Z.C.[Zhi-Cheng], Zhu, C.C.[Chen-Chen], Xiao, F.[Fanyi], Culatana, S.C.[Sean Chang], Elhoseiny, M.[Mohamed],
Exploring Open-Vocabulary Semantic Segmentation from CLIP Vision Encoder Distillation Only,
ICCV23(699-710)
IEEE DOI Code:
WWW Link. 2401
BibRef

Han, K.Y.[Kun-Yang], Liu, Y.[Yong], Liew, J.H.[Jun Hao], Ding, H.H.[Heng-Hui], Liu, J.J.[Jia-Jun], Wang, Y.T.[Yi-Tong], Tang, Y.S.[Yan-Song], Yang, Y.[Yujiu], Feng, J.S.[Jia-Shi], Zhao, Y.[Yao], Wei, Y.C.[Yun-Chao],
Global Knowledge Calibration for Fast Open-Vocabulary Segmentation,
ICCV23(797-807)
IEEE DOI 2401
BibRef

Barsellotti, L.[Luca], Amoroso, R.[Roberto], Baraldi, L.[Lorenzo], Cucchiara, R.[Rita],
FOSSIL: Free Open-Vocabulary Semantic Segmentation through Synthetic References Retrieval,
WACV24(1453-1462)
IEEE DOI 2404
BibRef
Earlier:
Enhancing Open-vocabulary Semantic Segmentation with Prototype Retrieval,
CIAP23(II:196-208).
Springer DOI 2312
Training, Visualization, Sensitivity, Semantic segmentation, Semantics, Prototypes, Predictive models, Algorithms, Image recognition and understanding BibRef

Liu, W.[Wei], Zhang, H.G.[Hui-Gang], Xia, X.J.[Xiao-Jie], Wang, L.[Liuan], Sun, J.[Jun],
Semantic-Embedded Knowledge Acquisition and Reasoning for Image Segmentation,
ICIP23(2360-2364)
IEEE DOI 2312
BibRef

Tan, Y.[Yang], Li, Y.C.[Yi-Cong], Li, Y.[Yang], Zhang, X.P.[Xiao-Ping],
Efficient Prediction of Model Transferability in Semantic Segmentation Tasks,
ICIP23(720-724)
IEEE DOI 2312
BibRef

Xu, J.[Jilan], Hou, J.L.[Jun-Lin], Zhang, Y.[Yuejie], Feng, R.[Rui], Wang, Y.[Yi], Qiao, Y.[Yu], Xie, W.[Weidi],
Learning Open-Vocabulary Semantic Segmentation Models From Natural Language Supervision,
CVPR23(2935-2944)
IEEE DOI 2309
BibRef

Chen, Z.W.[Zi-Wen], Patnaik, K.[Kaushik], Zhai, S.F.[Shuang-Fei], Wan, A.[Alvin], Ren, Z.[Zhile], Schwing, A.[Alex], Colburn, A.[Alex], Li, F.X.[Fu-Xin],
AutoFocusFormer: Image Segmentation off the Grid,
CVPR23(18227-18236)
IEEE DOI 2309
BibRef

Zou, X.Y.[Xue-Yan], Dou, Z.Y.[Zi-Yi], Yang, J.W.[Jian-Wei], Gan, Z.[Zhe], Li, L.J.[Lin-Jie], Li, C.Y.[Chun-Yuan], Dai, X.[Xiyang], Behl, H.[Harkirat], Wang, J.F.[Jian-Feng], Yuan, L.[Lu], Peng, N.[Nanyun], Wang, L.J.[Li-Juan], Lee, Y.J.[Yong Jae], Gao, J.F.[Jian-Feng],
Generalized Decoding for Pixel, Image, and Language,
CVPR23(15116-15127)
IEEE DOI 2309

WWW Link. BibRef

Cha, J.[Junbum], Mun, J.[Jonghwan], Roh, B.[Byungseok],
Learning to Generate Text-Grounded Mask for Open-World Semantic Segmentation from Only Image-Text Pairs,
CVPR23(11165-11174)
IEEE DOI 2309
BibRef

Mukhoti, J.[Jishnu], Lin, T.Y.[Tsung-Yu], Poursaeed, O.[Omid], Wang, R.[Rui], Shah, A.[Ashish], Torr, P.H.S.[Philip H.S.], Lim, S.N.[Ser-Nam],
Open Vocabulary Semantic Segmentation with Patch Aligned Contrastive Learning,
CVPR23(19413-19423)
IEEE DOI 2309
BibRef

Wang, D.D.[Dong-Dong], Gong, B.Q.[Bo-Qing], Wang, L.Q.[Li-Qiang],
On Calibrating Semantic Segmentation Models: Analyses and An Algorithm,
CVPR23(23652-23662)
IEEE DOI 2309
BibRef

de Jorge, P.[Pau], Volpi, R.[Riccardo], Torr, P.H.S.[Philip H.S.], Rogez, G.[Grégory],
Reliability in Semantic Segmentation: Are we on the Right Track?,
CVPR23(7173-7182)
IEEE DOI 2309
BibRef

Liang, F.[Feng], Wu, B.[Bichen], Dai, X.L.[Xiao-Liang], Li, K.[Kunpeng], Zhao, Y.[Yinan], Zhang, H.[Hang], Zhang, P.Z.[Pei-Zhao], Vajda, P.[Peter], Marculescu, D.[Diana],
Open-Vocabulary Semantic Segmentation with Mask-adapted CLIP,
CVPR23(7061-7070)
IEEE DOI 2309
BibRef

Yi, M.[Muyang], Cui, Q.[Quan], Wu, H.[Hao], Yang, C.[Cheng], Yoshie, O.[Osamu], Lu, H.T.[Hong-Tao],
A Simple Framework for Text-Supervised Semantic Segmentation,
CVPR23(7071-7080)
IEEE DOI 2309
BibRef

Liu, X.Y.[Xin-Yu], Tian, B.[Beiwen], Wang, Z.[Zhen], Wang, R.[Rui], Sheng, K.[Kehua], Zhang, B.[Bo], Zhao, H.[Hao], Zhou, G.[Guyue],
Delving into Shape-aware Zero-shot Semantic Segmentation,
CVPR23(2999-3009)
IEEE DOI 2309
BibRef

Yu, S.[Seonghoon], Seo, P.H.[Paul Hongsuck], Son, J.[Jeany],
Zero-shot Referring Image Segmentation with Global-Local Context Features,
CVPR23(19456-19465)
IEEE DOI 2309
BibRef

Yun, S.[Sukmin], Park, S.H.[Seong Hyeon], Seo, P.H.[Paul Hongsuck], Shin, J.[Jinwoo],
IFSeg: Image-free Semantic Segmentation via Vision-Language Model,
CVPR23(2967-2977)
IEEE DOI 2309
BibRef

Zhang, J.M.[Jia-Ming], Liu, R.P.[Rui-Ping], Shi, H.[Hao], Yang, K.L.[Kai-Lun], Reiß, S.[Simon], Peng, K.Y.[Kun-Yu], Fu, H.D.[Hao-Dong], Wang, K.W.[Kai-Wei], Stiefelhagen, R.[Rainer],
Delivering Arbitrary-Modal Semantic Segmentation,
CVPR23(1136-1147)
IEEE DOI 2309
BibRef

Dong, A.[Aimei], Liu, S.[Sidi],
Research on Multi-task Semantic Segmentation Based on Attention and Feature Fusion Method,
MMMod23(II: 362-373).
Springer DOI 2304
BibRef

Zabari, N.[Nir], Hoshen, Y.[Yedid],
Open-vocabulary Semantic Segmentation Using Test-time Distillation,
LLID22(56-72).
Springer DOI 2304
BibRef

Zheng, Z.S.[Zi-Shuo], Lin, C.Y.[Chun-Yu], Nie, L.[Lang], Liao, K.[Kang], Shen, Z.J.[Zhi-Jie], Zhao, Y.[Yao],
Complementary Bi-directional Feature Compression for Indoor 360° Semantic Segmentation with Self-distillation,
WACV23(4490-4499)
IEEE DOI 2302
Visualization, Image coding, Semantic segmentation, Bidirectional control, Distortion, Feature extraction, Virtual/augmented reality BibRef

Shen, F.Y.[Feng-Yi], Pataki, Z.[Zador], Gurram, A.[Akhil], Liu, Z.Y.[Zi-Yuan], Wang, H.[He], Knoll, A.[Alois],
LoopDA: Constructing Self-loops to Adapt Nighttime Semantic Segmentation,
WACV23(3255-3265)
IEEE DOI 2302
Training, Adaptation models, Codes, Semantic segmentation, Semantics, Pipelines, Algorithms: Machine learning architectures, visual reasoning BibRef

Sacha, M.[Mikolaj], Rymarczyk, D.[Dawid], Struski, L.[Lukasz], Tabor, J.[Jacek], Zielinski, B.[Bartosz],
ProtoSeg: Interpretable Semantic Segmentation with Prototypical Parts,
WACV23(1481-1492)
IEEE DOI 2302
Training, Adaptation models, Semantic segmentation, Semantics, Prototypes, Algorithms: Explainable, fair, accountable, visual reasoning BibRef

Kanakis, M.[Menelaos], Huang, T.E.[Thomas E.], Brüggemann, D.[David], Yu, F.[Fisher], Van Gool, L.J.[Luc J.],
Composite Learning for Robust and Effective Dense Predictions,
WACV23(2298-2307)
IEEE DOI 2302
Training, Semantic segmentation, Estimation, Multitasking, Robustness, Labeling, Algorithms: Machine learning architectures, and algorithms (including transfer) BibRef

Brüggemann, D.[David], Sakaridis, C.[Christos], Truong, P.[Prune], Van Gool, L.J.[Luc J.],
Refign: Align and Refine for Adaptation of Semantic Segmentation to Adverse Conditions,
WACV23(3173-3183)
IEEE DOI 2302
Training, Visualization, Uncertainty, Semantic segmentation, Semantics, Refining, Robotics BibRef

Endo, K.[Kazuki], Tanaka, M.[Masayuki], Okutomi, M.[Masatoshi],
Semantic Segmentation of Degraded Images Using Layer-Wise Feature Adjustor,
WACV23(3204-3212)
IEEE DOI 2302
Degradation, Knowledge engineering, Image recognition, Semantic segmentation, Surveillance, Transform coding, segmentation) BibRef

Nunes, I.[Ian], Pereira, M.B.[Matheus B.], Oliveira, H.[Hugo], dos Santos, J.A.[Jefersson A.], Poggi, M.[Marcus],
Conditional Reconstruction for Open-Set Semantic Segmentation,
ICIP22(946-950)
IEEE DOI 2211
Adaptation models, Semantics, Time series analysis, Data integration, Decoding, Task analysis, Image reconstruction, open world BibRef

Wang, Z.C.[Zi-Chao], Jiang, Z.Y.[Zhi-Yu], Yuan, Y.[Yuan],
Prototype Queue Learning for Multi-Class Few-Shot Semantic Segmentation,
ICIP22(1721-1725)
IEEE DOI 2211
Prototypes, Self-supervised learning, Feature extraction, Task analysis, Few-shot segmentation, Multi-class segmentation, Semantic segmentation BibRef

Kwon, H.[Hyeongjun], Song, T.[Taeyong], Kim, S.[Sunok], Sohn, K.H.[Kwang-Hoon],
Mask-Guided Attention and Episode Adaptive Weights for Few-Shot Segmentation,
ICIP22(2611-2615)
IEEE DOI 2211
Training, Image segmentation, Adaptation models, Benchmark testing, Feature extraction, Data mining, Few-shot segmentation, adaptive learning BibRef

Yang, X.H.[Xin-Hao], Ma, L.Y.[Li-Yan], Zhou, Y.[Yang], Peng, Y.[Yan], Xie, S.R.[Shao-Rong],
Prior Semantic Harmonization Network for Few-Shot Semantic Segmentation,
ICIP22(1126-1130)
IEEE DOI 2211
Correlation, Semantics, Few-shot segmentation, Semantic harmonization, Feature activation, Hierarchical aggregation BibRef

Kuhn, C.B.[Christopher B.], Hofbauer, M.[Markus], Petrovic, G.[Goran], Steinbach, E.[Eckehard],
Reverse Error Modeling for Improved Semantic Segmentation,
ICIP22(106-110)
IEEE DOI 2211
Image coding, Semantics, Predictive models, Data models, Image reconstruction, Testing, Semantic Segmentation, Error Correction BibRef

Xu, M.D.[Meng-De], Zhang, Z.[Zheng], Wei, F.Y.[Fang-Yun], Lin, Y.T.[Yu-Tong], Cao, Y.[Yue], Hu, H.[Han], Bai, X.[Xiang],
A Simple Baseline for Open-Vocabulary Semantic Segmentation with Pre-trained Vision-Language Model,
ECCV22(XXIX:736-753).
Springer DOI 2211
BibRef

Lin, Z.H.[Zi-Han], Wang, Z.L.[Zi-Lei], Zhang, Y.X.[Yi-Xin],
Continual Semantic Segmentation via Structure Preserving and Projected Feature Alignment,
ECCV22(XXIX:345-361).
Springer DOI 2211
BibRef

Pissas, T.[Theodoros], Ravasio, C.S.[Claudio S.], da Cruz, L.[Lyndon], Bergeles, C.[Christos],
Multi-scale and Cross-scale Contrastive Learning for Semantic Segmentation,
ECCV22(XXIX:413-429).
Springer DOI 2211
BibRef

Wu, T.[Tong], Gao, G.Y.[Guang-Yu], Huang, J.[Junshi], Wei, X.L.[Xiao-Lin], Wei, X.M.[Xiao-Ming], Liu, C.H.[Chi Harold],
Adaptive Spatial-BCE Loss for Weakly Supervised Semantic Segmentation,
ECCV22(XXIX:199-216).
Springer DOI 2211
BibRef

Yin, Z.Y.[Zhao-Yuan], Wang, P.[Pichao], Wang, F.[Fan], Xu, X.Z.[Xian-Zhe], Zhang, H.L.[Han-Ling], Li, H.[Hao], Jin, R.[Rong],
TransFGU: A Top-Down Approach to Fine-Grained Unsupervised Semantic Segmentation,
ECCV22(XXIX:73-89).
Springer DOI 2211
BibRef

Huang, Y.[Ye], Kang, D.[Di], Chen, L.[Liang], Zhe, X.F.[Xue-Fei], Jia, W.J.[Wen-Jing], Bao, L.C.[Lin-Chao], He, X.J.[Xiang-Jian],
CAR: Class-Aware Regularizations for Semantic Segmentation,
ECCV22(XXVIII:518-534).
Springer DOI 2211
BibRef

Liu, Q.D.[Quan-De], Wen, Y.P.[You-Peng], Han, J.H.[Jian-Hua], Xu, C.J.[Chun-Jing], Xu, H.[Hang], Liang, X.D.[Xiao-Dan],
Open-World Semantic Segmentation via Contrasting and Clustering Vision-Language Embedding,
ECCV22(XX:275-292).
Springer DOI 2211
BibRef

Wang, F.[Feng], Wang, H.Y.[Hui-Yu], Wei, C.[Chen], Yuille, A.L.[Alan L.], Shen, W.[Wei],
CP 2: Copy-Paste Contrastive Pretraining for Semantic Segmentation,
ECCV22(XXX:499-515).
Springer DOI 2211
BibRef

Yang, F.Y.[Feng-Yu], Ma, C.Y.[Chen-Yang],
Sparse and Complete Latent Organization for Geospatial Semantic Segmentation,
CVPR22(1799-1808)
IEEE DOI 2210
Image segmentation, Computational modeling, Semantics, Prototypes, Organizations, Geospatial analysis, Photogrammetry and remote sensing BibRef

Bär, A.[Andreas], Klingner, M.[Marvin], Löhdefink, J.[Jonas], Hüger, F.[Fabian], Schlicht, P.[Peter], Fingscheidt, T.[Tim],
Performance Prediction for Semantic Segmentation by a Self-Supervised Image Reconstruction Decoder,
WAD22(4398-4407)
IEEE DOI 2210
Training, Image segmentation, Semantics, Supervised learning, Training data, Benchmark testing, Sensors BibRef

Liu, S.A.[Sun-Ao], Xie, H.T.[Hong-Tao], Xu, H.[Hai], Zhang, Y.D.[Yong-Dong], Tian, Q.[Qi],
Partial Class Activation Attention for Semantic Segmentation,
CVPR22(16815-16824)
IEEE DOI 2210
Location awareness, Image segmentation, Codes, Semantics, Benchmark testing, Pattern recognition, grouping and shape analysis BibRef

Ding, J.[Jian], Xue, N.[Nan], Xia, G.S.[Gui-Song], Dai, D.X.[Deng-Xin],
Decoupling Zero-Shot Semantic Segmentation,
CVPR22(11573-11582)
IEEE DOI 2210
Training, Image segmentation, Codes, Shape, Semantics, Pattern recognition, Segmentation, grouping and shape analysis BibRef

Zhao, Y.Y.[Yu-Yang], Zhong, Z.[Zhun], Sebe, N.[Nicu], Lee, G.H.[Gim Hee],
Novel Class Discovery in Semantic Segmentation,
CVPR22(4330-4339)
IEEE DOI 2210
Training, Image segmentation, Uncertainty, Shape, Semantics, Self-supervised learning, Benchmark testing, Segmentation, Self- semi- meta- Transfer/low-shot/long-tail learning BibRef

Jin, Z.C.[Zhen-Chao], Liu, B.[Bin], Chu, Q.[Qi], Yu, N.H.[Neng-Hai],
ISNet: Integrate Image-Level and Semantic-Level Context for Semantic Segmentation,
ICCV21(7169-7178)
IEEE DOI 2203
Image segmentation, Visualization, Lips, Aggregates, Semantics, Benchmark testing, Segmentation, grouping and shape, BibRef

Zhang, Y.[Yu], Zhang, C.B.[Chang-Bin], Jiang, P.T.[Peng-Tao], Cheng, M.M.[Ming-Ming], Mao, F.[Feng],
Personalized Image Semantic Segmentation,
ICCV21(10529-10539)
IEEE DOI 2203
Image segmentation, Correlation, Codes, Semantics, Datasets and evaluation, Segmentation, grouping and shape BibRef

Jain, S.[Shipra], Paudel, D.P.[Danda Pani], Danelljan, M.[Martin], Van Gool, L.J.[Luc J.],
Scaling Semantic Segmentation Beyond 1K Classes on a Single GPU,
ICCV21(7406-7416)
IEEE DOI 2203
Training, Image segmentation, Computational modeling, Scalability, Semantics, Graphics processing units, Object detection, Representation learning BibRef

Wang, W.G.[Wen-Guan], Zhou, T.F.[Tian-Fei], Yu, F.[Fisher], Dai, J.F.[Ji-Feng], Konukoglu, E.[Ender], Van Gool, L.J.[Luc J.],
Exploring Cross-Image Pixel Contrast for Semantic Segmentation,
ICCV21(7283-7293)
IEEE DOI 2203
Training, Representation learning, Measurement, Image segmentation, Semantics, Training data, Optical character recognition software, Scene analysis and understanding BibRef

Hsiao, C.W.[Chi-Wei], Sun, C.[Cheng], Chen, H.T.[Hwann-Tzong], Sun, M.[Min],
Specialize and Fuse: Pyramidal Output Representation for Semantic Segmentation,
ICCV21(7117-7126)
IEEE DOI 2203
Fuses, Aggregates, Semantics, Task analysis, Segmentation, grouping and shape BibRef

Zhang, D.[Dong], Zhang, H.W.[Han-Wang], Tang, J.H.[Jin-Hui], Hua, X.S.[Xian-Sheng], Sun, Q.[Qianru],
Self-Regulation for Semantic Segmentation,
ICCV21(6933-6943)
IEEE DOI 2203
Training, Visualization, Computational modeling, Semantics, Neural networks, Performance gain, Segmentation, Scene analysis and understanding BibRef

Garcia, R.L., Happ, P.N., Feitosa, R.Q.,
Large Scale Semantic Segmentation of Virtual Environments to Facilitate Corrosion Management,
ISPRS21(B2-2021: 465-470).
DOI Link 2201
BibRef

Pang, Y.T.[Yu-Ting], Chang, J.[Jui], Hsu, C.T.[Chiou-Ting],
Self-Guided Adversarial Learning for Domain Adaptive Semantic Segmentation,
ICIP21(2249-2253)
IEEE DOI 2201
Learning systems, Image segmentation, Adaptation models, Semantics, Benchmark testing, Reliability, Unsupervised domain adaptation, self-guided adversarial learning BibRef

Shiau, Z.Y.[Zu-Yun], Lin, W.W.[Wei-Wei], Lin, C.S.[Ci-Siang], Wang, Y.C.A.F.[Yu-Chi-Ang Frank],
Meta-Learned Feature Critics for Domain Generalized Semantic Segmentation,
ICIP21(2244-2248)
IEEE DOI 2201
Adaptation models, Visualization, Image segmentation, Semantics, Benchmark testing, Feature extraction, domain generalization BibRef

Lee, H.J.[Hong Joo], Ro, Y.M.[Yong Man],
Adversarially Robust Multi-Sensor Fusion Model Training Via Random Feature Fusion for Semantic Segmentation,
ICIP21(339-343)
IEEE DOI 2201
Training, Image segmentation, Semantics, Data integration, Object detection, Feature extraction, Multi-sensor data fusion, random feature fusion BibRef

Aakerberg, A.[Andreas], Johansen, A.S.[Anders S.], Nasrollahi, K.[Kamal], Moeslund, T.B.[Thomas B.],
Single-Loss Multi-task Learning For Improving Semantic Segmentation Using Super-Resolution,
CAIP21(II:403-411).
Springer DOI 2112
BibRef

Cho, J.H.[Jang Hyun], Mall, U.[Utkarsh], Bala, K.[Kavita], Hariharan, B.[Bharath],
PiCIE: Unsupervised Semantic Segmentation using Invariance and Equivariance in Clustering,
CVPR21(16789-16799)
IEEE DOI 2111
Training, Visualization, Image segmentation, Codes, Clustering methods, Semantics BibRef

Huynh, C.[Chuong], Tran, A.T.[Anh Tuan], Luu, K.[Khoa], Hoai, M.[Minh],
Progressive Semantic Segmentation,
CVPR21(16750-16759)
IEEE DOI 2111
Image segmentation, Image resolution, Codes, Magnetic separation, Magnetic resonance imaging, Semantics BibRef

Teja, S.P.[S. Prabhu], Fleuret, F.[François],
Uncertainty Reduction for Model Adaptation in Semantic Segmentation,
CVPR21(9608-9618)
IEEE DOI 2111
Image segmentation, Adaptation models, Uncertainty, Semantics, Urban areas, Feature extraction, Data models BibRef

Li, S.[Shuang], Gong, K.X.[Kai-Xiong], Liu, C.H.[Chi Harold], Wang, Y.L.[Yu-Lin], Qiao, F.[Feng], Cheng, X.[Xinjing],
MetaSAug: Meta Semantic Augmentation for Long-Tailed Visual Recognition,
CVPR21(5208-5217)
IEEE DOI 2111
Training, Visualization, Semantics, Supervised learning, Training data, Benchmark testing BibRef

Yang, S.[Sibei], Xia, M.[Meng], Li, G.B.[Guan-Bin], Zhou, H.Y.[Hong-Yu], Yu, Y.Z.[Yi-Zhou],
Bottom-Up Shift and Reasoning for Referring Image Segmentation,
CVPR21(11261-11270)
IEEE DOI 2111
Location awareness, Visualization, Image segmentation, Fuses, Message passing, Computational modeling BibRef

Ma, H.Y.[Hao-Yu], Lin, X.R.[Xiang-Ru], Wu, Z.F.[Zi-Feng], Yu, Y.Z.[Yi-Zhou],
Coarse-to-Fine Domain Adaptive Semantic Segmentation with Photometric Alignment and Category-Center Regularization,
CVPR21(4050-4059)
IEEE DOI 2111
Image segmentation, Adaptation models, Annotations, Computational modeling, Semantics, Pipelines BibRef

Hänsch, R.[Ronny],
Looking Outside the Box: The Role of Context in Random Forest Based Semantic Segmentation of PolSAR Images,
GCPR20(260-274).
Springer DOI 2110
BibRef

Theodoridou, C.[Christina], Kargakos, A.[Andreas], Kostavelis, I.[Ioannis], Giakoumis, D.[Dimitrios], Tzovaras, D.[Dimitrios],
Spatially-Constrained Semantic Segmentation with Topological Maps and Visual Embeddings,
CVS21(117-129).
Springer DOI 2109
BibRef

Szabó, A.[Attila], Jamali-Rad, H.[Hadi], Mannava, S.D.[Siva-Datta],
Tilted Cross-Entropy (TCE): Promoting Fairness in Semantic Segmentation,
RCV21(2305-2310)
IEEE DOI 2109
Semantics, Performance analysis, Pattern recognition, Risk management BibRef

Tavera, A.[Antonio], Cermelli, F.[Fabio], Masone, C.[Carlo], Caputo, B.[Barbara],
Pixel-by-Pixel Cross-Domain Alignment for Few-Shot Semantic Segmentation,
WACV22(1959-1968)
IEEE DOI 2202
Training, Image segmentation, Semantics, Benchmark testing, Task analysis, Standards, Segmentation, Grouping and Shape Scene Understanding BibRef

Fontanel, D.[Dario], Cermelli, F.[Fabio], Mancini, M.[Massimiliano], Caputo, B.[Barbara],
Detecting Anomalies in Semantic Segmentation with Prototypes,
SAIAD21(113-121)
IEEE DOI 2109
Training, Visualization, Computational modeling, Semantics, Prototypes BibRef

Patel, Y.[Yash], Appalaraju, S.[Srikar], Manmatha, R.,
Saliency Driven Perceptual Image Compression,
WACV21(227-236)
IEEE DOI 2106
Measurement, Image segmentation, Image coding, Computational modeling, Bit rate BibRef

Zhang, B.[Bin], Zhao, S.J.[Sheng-Jie], Zhang, R.Q.[Rong-Qing],
Cross-Domain Semantic Segmentation of Urban Scenes via Multi-Level Feature Alignment,
ICPR21(1912-1917)
IEEE DOI 2105
Image segmentation, Solid modeling, Semantics, Neural networks, Virtual reality, Feature extraction, Robustness BibRef

Zhang, Y.F.[Yi-Fei], Sidibé, D.[Désiré], Morel, O.[Olivier], Meriaudeau, F.[Fabrice],
Multiscale Attention-Based Prototypical Network For Few-Shot Semantic Segmentation,
ICPR21(7372-7378)
IEEE DOI 2105
Training, Image segmentation, Adaptation models, Annotations, Semantics, Prototypes, Feature extraction BibRef

Nie, D.[Dong], Xue, J.[Jia], Ren, X.F.[Xiao-Feng],
Bidirectional Pyramid Networks for Semantic Segmentation,
ACCV20(I:654-671).
Springer DOI 2103
BibRef

Ouni, A.[Achref], Royer, E.[Eric], Chevaldonné, M.[Marc], Dhome, M.[Michel],
A Hybrid Approach for Improved Image Similarity Using Semantic Segmentation,
ISVC20(II:647-657).
Springer DOI 2103
BibRef

Mozaffari, M.H.[M. Hamed], Lee, W.S.[Won-Sook],
Semantic Segmentation with Peripheral Vision,
ISVC20(II:421-429).
Springer DOI 2103
BibRef

Huang, Y., Tang, Z., Su, K.,
Balance-batch: An Optimized Method for Semantic Segmentation Loss Functions,
CVIDL20(342-346)
IEEE DOI 2102
feature extraction, image classification, image representation, image segmentation, learning (artificial intelligence), loss function BibRef

Jiang, S.L., Li, G., Yao, W., Hong, Z.H., Kuc, T.Y.,
Dual Pyramids Encoder-decoder Network for Semantic Segmentation In Ground and Aerial View Images,
ISPRS20(B2:605-610).
DOI Link 2012
BibRef

Jing, Y.[Ya], Kong, T.[Tao], Wang, W.[Wei], Wang, L.[Liang], Li, L.[Lei], Tan, T.N.[Tie-Niu],
Locate then Segment: A Strong Pipeline for Referring Image Segmentation,
CVPR21(9853-9862)
IEEE DOI 2111
Location awareness, Image segmentation, Visualization, Fuses, Pipelines, Object segmentation, Feature extraction BibRef

Chen, W.L.[Wan-Li], Zhu, X.G.[Xin-Ge], Sun, R.Q.[Ruo-Qi], He, J.J.[Jun-Jun], Li, R.Y.[Rui-Yu], Shen, X.Y.[Xiao-Yong], Yu, B.[Bei],
Tensor Low-rank Reconstruction for Semantic Segmentation,
ECCV20(XVII:52-69).
Springer DOI 2011
BibRef

Hu, H.Z.[Han-Zhe], Ji, D.Y.[De-Yi], Gan, W.H.[Wei-Hao], Bai, S.[Shuai], Wu, W.[Wei], Yan, J.J.[Jun-Jie],
Class-wise Dynamic Graph Convolution for Semantic Segmentation,
ECCV20(XVII:1-17).
Springer DOI 2011
BibRef

Yin, M.H.[Ming-Hao], Yao, Z.L.[Zhu-Liang], Cao, Y.[Yue], Li, X.[Xiu], Zhang, Z.[Zheng], Lin, S.[Stephen], Hu, H.[Han],
Disentangled Non-local Neural Networks,
ECCV20(XV:191-207).
Springer DOI 2011
Code, Segmentation.
WWW Link.
WWW Link. BibRef

Lehman, C., Temel, D., Alregib, G.,
On the Structures of Representation for the Robustness of Semantic Segmentation to Input Corruption,
ICIP20(3239-3243)
IEEE DOI 2011
Robustness, Semantics, Entropy, Training, Estimation, Task analysis, Machine learning, Robustness in Machine Learning, Sigmoid BibRef

Li, S., Zhou, Q., Liu, J., Wang, J., Fan, Y., Wu, X., Latecki, L.J.,
DCM: A Dense-Attention Context Module For Semantic Segmentation,
ICIP20(1431-1435)
IEEE DOI 2011
Convolution, Feature extraction, Semantics, Data mining, Image segmentation, Kernel, Decoding, Semantic segmentation, Attention BibRef

Wang, Y.K.[Yu-Kang], Zhou, W.[Wei], Jiang, T.[Tao], Bai, X.[Xiang], Xu, Y.C.[Yong-Chao],
Intra-class Feature Variation Distillation for Semantic Segmentation,
ECCV20(VII:346-362).
Springer DOI 2011
BibRef

Michieli, U.[Umberto], Borsato, E.[Edoardo], Rossi, L.[Luca], Zanuttigh, P.[Pietro],
Gmnet: Graph Matching Network for Large Scale Part Semantic Segmentation in the Wild,
ECCV20(VIII:397-414).
Springer DOI 2011
BibRef

Yang, B.[Boyu], Liu, C.[Chang], Li, B.[Bohao], Jiao, J.B.[Jian-Bin], Ye, Q.X.[Qi-Xiang],
Prototype Mixture Models for Few-shot Semantic Segmentation,
ECCV20(VIII:763-778).
Springer DOI 2011
BibRef

Yuan, Y.H.[Yu-Hui], Chen, X.L.[Xi-Lin], Wang, J.D.[Jing-Dong],
Object-contextual Representations for Semantic Segmentation,
ECCV20(VI:173-190).
Springer DOI 2011
BibRef

Kamann, C.[Christoph], Rother, C.[Carsten],
Increasing the Robustness of Semantic Segmentation Models with Painting-by-numbers,
ECCV20(X:369-387).
Springer DOI 2011
BibRef

Liu, Y.F.[Yong-Fei], Zhang, X.Y.[Xiang-Yi], Zhang, S.Y.[Song-Yang], He, X.M.[Xu-Ming],
Part-aware Prototype Network for Few-Shot Semantic Segmentation,
ECCV20(IX:142-158).
Springer DOI 2011
BibRef

He, Y.[Yang], Rahimian, S.[Shadi], Schiele, B.[Bernt], Fritz, M.[Mario],
Segmentations-leak: Membership Inference Attacks and Defenses in Semantic Image Segmentation,
ECCV20(XXIII:519-535).
Springer DOI 2011
BibRef

Xia, Y.D.[Ying-Da], Zhang, Y.[Yi], Liu, F.Z.[Feng-Ze], Shen, W.[Wei], Yuille, A.L.[Alan L.],
Synthesize Then Compare: Detecting Failures and Anomalies for Semantic Segmentation,
ECCV20(I:145-161).
Springer DOI 2011
BibRef

Cheng, H.K.[Ho Kei], Chung, J.H.[Ji-Hoon], Tai, Y.W.[Yu-Wing], Tang, C.K.[Chi-Keung],
CascadePSP: Toward Class-Agnostic and Very High-Resolution Segmentation via Global and Local Refinement,
CVPR20(8887-8896)
IEEE DOI 2008
Image segmentation, Image resolution, Semantics, Computational modeling, Task analysis, Adaptation models, Feature extraction BibRef

Oberdiek, P., Rottmann, M., Fink, G.A.,
Detection and Retrieval of Out-of-Distribution Objects in Semantic Segmentation,
SAIAD20(1331-1340)
IEEE DOI 2008
Image segmentation, Feature extraction, Semantics, Visualization, Agriculture, Machine learning, Image retrieval BibRef

Kamann, C., Rother, C.,
Benchmarking the Robustness of Semantic Segmentation Models,
CVPR20(8825-8835)
IEEE DOI 2008
Robustness, Semantics, Computer architecture, Image segmentation, Feature extraction, Benchmark testing, Cameras BibRef

Siddiqui, Y., Valentin, J., Nießner, M.,
ViewAL: Active Learning With Viewpoint Entropy for Semantic Segmentation,
CVPR20(9430-9440)
IEEE DOI 2008
Entropy, Uncertainty, Semantics, Labeling, Image segmentation, Task analysis, Data models BibRef

Zhang, Y., Qiu, Z., Yao, T., Ngo, C., Liu, D., Mei, T.,
Transferring and Regularizing Prediction for Semantic Segmentation,
CVPR20(9618-9627)
IEEE DOI 2008
Semantics, Image segmentation, Roads, Buildings, Visualization, Labeling, Adaptation models BibRef

Araslanov, N., Roth, S.,
Single-Stage Semantic Segmentation From Image Labels,
CVPR20(4252-4261)
IEEE DOI 2008
Image segmentation, Training, Semantics, Task analysis, Logic gates, Stochastic processes, Decoding BibRef

Wang, L., Li, D., Zhu, Y., Tian, L., Shan, Y.,
Dual Super-Resolution Learning for Semantic Segmentation,
CVPR20(3773-3782)
IEEE DOI 2008
Semantics, Image segmentation, Spatial resolution, Task analysis, Pose estimation, Convolution BibRef

Rai, S.N., Balasubramanian, V.N., Subramanian, A., Jawahar, C.V.,
Munich to Dubai: How far is it for Semantic Segmentation?,
WACV20(2988-2997)
IEEE DOI 2006
Image restoration, Image segmentation, Atmospheric modeling, Meteorology, Semantics, Adaptation models, Training BibRef

Du, Y.M.[Yu-Ming], Xiao, Y.[Yang], Lepetit, V.[Vincent],
Learning to Better Segment Objects from Unseen Classes with Unlabeled Videos,
ICCV21(3355-3364)
IEEE DOI 2203
Training, Shape, Video sequences, Training data, Manuals, Object segmentation, Object detection, grouping and shape BibRef

Lin, H.[Hubert], Upchurch, P.[Paul], Bala, K.[Kavita],
Block Annotation: Better Image Annotation With Sub-Image Decomposition,
ICCV19(5289-5299)
IEEE DOI 2004
Generate the data needed to do semantic segmentation. image retrieval, image segmentation, image texture, block annotation, high-quality pixel-level annotations, Quality control BibRef

Cheng, B., Chen, L., Wei, Y., Zhu, Y., Huang, Z., Xiong, J., Huang, T., Hwu, W., Shi, H., Uiuc, U.,
SPGNet: Semantic Prediction Guidance for Scene Parsing,
ICCV19(5217-5227)
IEEE DOI 2004
feature extraction, image coding, image segmentation, learning (artificial intelligence), pose estimation, Feature extraction BibRef

Pang, Y., Li, Y., Shen, J., Shao, L.,
Towards Bridging Semantic Gap to Improve Semantic Segmentation,
ICCV19(4229-4238)
IEEE DOI 2004
feature extraction, image enhancement, image fusion, image representation, image segmentation, object detection, Convolution BibRef

Zhang, C., Liwicki, S., Smith, W., Cipolla, R.,
Orientation-Aware Semantic Segmentation on Icosahedron Spheres,
ICCV19(3532-3540)
IEEE DOI 2004
convolutional neural nets, feature extraction, image classification, image resolution, image segmentation, Task analysis BibRef

Nakajima, Y., Kang, B., Saito, H., Kitani, K.,
Incremental Class Discovery for Semantic Segmentation With RGBD Sensing,
ICCV19(972-981)
IEEE DOI 2004
image colour analysis, image representation, image segmentation, learning (artificial intelligence), object recognition, Image color analysis BibRef

Han, Q.Y.[Qiu-Yuan], Zheng, J.[Jin],
Multi-scale Spatial Location Preference for Semantic Segmentation,
MMMod20(I:593-604).
Springer DOI 2003
BibRef

Jiao, J.B.[Jian-Bo], Wei, Y.C.[Yun-Chao], Jie, Z.Q.[Ze-Qun], Shi, H.H.[Hong-Hui], Lau, R.W.H.[Rynson W.H.], Huang, T.S.[Thomas S.],
Geometry-Aware Distillation for Indoor Semantic Segmentation,
CVPR19(2864-2873).
IEEE DOI 2002
BibRef

Liu, Y.F.[Yi-Fan], Chen, K.[Ke], Liu, C.[Chris], Qin, Z.C.[Zeng-Chang], Luo, Z.B.[Zhen-Bo], Wang, J.D.[Jing-Dong],
Structured Knowledge Distillation for Semantic Segmentation,
CVPR19(2599-2608).
IEEE DOI 2002
BibRef

Tian, Z.[Zhi], He, T.[Tong], Shen, C.H.[Chun-Hua], Yan, Y.[Youliang],
Decoders Matter for Semantic Segmentation: Data-Dependent Decoding Enables Flexible Feature Aggregation,
CVPR19(3121-3130).
IEEE DOI 2002
BibRef

Zhou, Y.Z.[Yi-Zhou], Sun, X.Y.[Xiao-Yan], Zha, Z.J.[Zheng-Jun], Zeng, W.J.[Wen-Jun],
Context-Reinforced Semantic Segmentation,
CVPR19(4041-4050).
IEEE DOI 2002
BibRef

Zhang, Z.Y.[Zhen-Yu], Cui, Z.[Zhen], Xu, C.Y.[Chun-Yan], Yan, Y.[Yan], Sebe, N.[Nicu], Yang, J.[Jian],
Pattern-Affinitive Propagation Across Depth, Surface Normal and Semantic Segmentation,
CVPR19(4101-4110).
IEEE DOI 2002
BibRef

Zhang, H.[Hang], Zhang, H.[Han], Wang, C.G.[Chen-Guang], Xie, J.Y.[Jun-Yuan],
Co-Occurrent Features in Semantic Segmentation,
CVPR19(548-557).
IEEE DOI 2002
BibRef

Chang, W.L.[Wei-Lun], Wang, H.P.[Hui-Po], Peng, W.H.[Wen-Hsiao], Chiu, W.C.[Wei-Chen],
All About Structure: Adapting Structural Information Across Domains for Boosting Semantic Segmentation,
CVPR19(1900-1909).
IEEE DOI 2002
BibRef

Schmitz, M., Brandenburger, W., Mayer, H.,
Semantic Segmentation of Airborne Images and Corresponding Digital Surface Models - Additional Input Data Or Additional Task?,
PIA19(195-200).
DOI Link 1912
BibRef

Huang, Y., Proesmans, M., Georgoulis, S., Van Gool, L.J.,
Uncertainty based model selection for fast semantic segmentation,
MVA19(1-6)
DOI Link 1911
entropy, image segmentation, inference mechanisms, semantic labels, baseline model, reasonable inference speeds, Entropy BibRef

Bevandic, P.[Petra], Krešo, I.[Ivan], Oršic, M.[Marin], Šegvic, S.[Siniša],
Simultaneous Semantic Segmentation and Outlier Detection in Presence of Domain Shift,
GCPR19(33-47).
Springer DOI 1911
BibRef

Russo, P.[Paolo], Tommasi, T.[Tatiana], Caputo, B.[Barbara],
Towards Multi-source Adaptive Semantic Segmentation,
CIAP19(I:292-301).
Springer DOI 1909
BibRef

Zhuang, P.C.[Peng-Cheng], Sekikawa, Y.[Yusuke], Hara, K.[Kosuke], Saito, H.[Hideo],
Learning an Optimisable Semantic Segmentation Map with Image Conditioned Variational Autoencoder,
CIAP19(II:379-389).
Springer DOI 1909
BibRef

Dias, P.A.[Philipe Ambrozio], Medeiros, H.[Henry],
Semantic Segmentation Refinement by Monte Carlo Region Growing of High Confidence Detections,
ACCV18(II:131-146).
Springer DOI 1906
BibRef

Falcăo, A.X.[Alexandre X.], Bragantini, J.[Jordăo],
The Role of Optimum Connectivity in Image Segmentation: Can the Algorithm Learn Object Information During the Process?,
DGCI19(180-194).
Springer DOI 1905
Feature space and image domain linkage. BibRef

Guan, H., Zhang, Z., Tan, T.,
Inception Donut Convolution for Top-down Semantic Segmentation,
ICPR18(2492-2497)
IEEE DOI 1812
convolution, feature extraction, feedforward neural nets, image representation, image segmentation, Streaming media BibRef

Tsai, Y., Hung, W., Schulter, S., Sohn, K., Yang, M., Chandraker, M.,
Learning to Adapt Structured Output Space for Semantic Segmentation,
CVPR18(7472-7481)
IEEE DOI 1812
Image segmentation, Semantics, Adaptation models, Task analysis, Training, Prediction algorithms, Layout BibRef

Muralikrishnan, S., Kim, V.G., Chaudhuri, S.,
Tags2Parts: Discovering Semantic Regions from Shape Tags,
CVPR18(2926-2935)
IEEE DOI 1812
Shape, Computer architecture, Image segmentation, Convolution, Semantics, Training BibRef

Bilinski, P., Prisacariu, V.[Victor],
Dense Decoder Shortcut Connections for Single-Pass Semantic Segmentation,
CVPR18(6596-6605)
IEEE DOI 1812
Decoding, Semantics, Image segmentation, Architecture, Computer architecture, Fuses, Spatial resolution BibRef

Zhang, H., Dana, K., Shi, J., Zhang, Z., Wang, X., Tyagi, A., Agrawal, A.,
Context Encoding for Semantic Segmentation,
CVPR18(7151-7160)
IEEE DOI 1812
Encoding, Semantics, Convolution, Image segmentation, Training, Image coding, Feature extraction BibRef

Casanova, A., Cucurull, G., Drozdzal, M., Romero, A., Bengio, Y.,
On the Iterative Refinement of Densely Connected Representation Levels for Semantic Segmentation,
AutoDrive18(1091-109109)
IEEE DOI 1812
Semantics, Spatial resolution, Computer architecture, Convolutional codes, Computational modeling, Image segmentation BibRef

Huang, Y., Jia, X., Georgoulis, S., Tuytelaars, T., Van Gool, L.J.,
Error Correction for Dense Semantic Image Labeling,
AutoDrive18(1111-11118)
IEEE DOI 1812
Image segmentation, Labeling, Task analysis, Semantics, Error correction, Pipelines, Probability distribution BibRef

Yang, M., Yu, K., Zhang, C., Li, Z., Yang, K.,
DenseASPP for Semantic Segmentation in Street Scenes,
CVPR18(3684-3692)
IEEE DOI 1812
Convolution, Semantics, Image resolution, Kernel, Image segmentation, Neurons, Autonomous vehicles BibRef

Matsuzuki, D.[Daisuke], Hotta, K.[Kazuhiro],
Semantic Segmentation by Integrating Classifiers for Different Difficulty Levels,
ISVC18(607-615).
Springer DOI 1811
BibRef

Ke, T.W.[Tsung-Wei], Hwang, J.J.[Jyh-Jing], Liu, Z.W.[Zi-Wei], Yu, S.X.[Stella X.],
Adaptive Affinity Fields for Semantic Segmentation,
ECCV18(I: 605-621).
Springer DOI 1810
BibRef

Lin, D.[Di], Ji, Y.F.[Yuan-Feng], Lischinski, D.[Dani], Cohen-Or, D.[Daniel], Huang, H.[Hui],
Multi-scale Context Intertwining for Semantic Segmentation,
ECCV18(III: 622-638).
Springer DOI 1810
BibRef

Zhu, X.G.[Xin-Ge], Zhou, H.[Hui], Yang, C.Y.[Ce-Yuan], Shi, J.P.[Jian-Ping], Lin, D.[Dahua],
Penalizing Top Performers: Conservative Loss for Semantic Segmentation Adaptation,
ECCV18(VII: 587-603).
Springer DOI 1810
BibRef

Zhang, Z.Y.[Zhen-Yu], Cui, Z.[Zhen], Xu, C.Y.[Chun-Yan], Jie, Z.Q.[Ze-Qun], Li, X.[Xiang], Yang, J.[Jian],
Joint Task-Recursive Learning for Semantic Segmentation and Depth Estimation,
ECCV18(X: 238-255).
Springer DOI 1810
BibRef

Zhang, Z.L.[Zhen-Li], Zhang, X.Y.[Xiang-Yu], Peng, C.[Chao], Xue, X.Y.[Xiang-Yang], Sun, J.[Jian],
ExFuse: Enhancing Feature Fusion for Semantic Segmentation,
ECCV18(X: 273-288).
Springer DOI 1810
BibRef

Sulimowicz, L., Ahmad, I., Aved, A.,
Superpixel-Enhanced Pairwise Conditional Random Field for Semantic Segmentation,
ICIP18(271-275)
IEEE DOI 1809
Image segmentation, Semantics, Kernel, Labeling, Robustness, Visualization, Image color analysis, and Higher-order CRFs BibRef

Lu, L.H.[Li-Hsien], Hsu, C.T.[Chiou-Ting],
Semantic Segmentation for Real-World Data by Jointly Exploiting Supervised andxs Transferrable Knowledge,
BMVC16(xx-yy).
HTML Version. 1805
BibRef

Cui, Z., Zhang, Q., Geng, S., Niu, X., Yang, J., Qiao, Y.,
Semantic segmentation with multi-path refinement and pyramid pooling dilated-resnet,
ICIP17(3100-3104)
IEEE DOI 1803
Computer architecture, Convolution, Feature extraction, Image segmentation, Semantics, Task analysis, Training, Segmentation BibRef

Shen, F., Gan, R., Yan, S., Zeng, G.,
Semantic Segmentation via Structured Patch Prediction, Context CRF and Guidance CRF,
CVPR17(5178-5186)
IEEE DOI 1711
Complexity theory, Image segmentation, Message passing, Predictive models, Semantics, Training BibRef

Wigness, M., Rogers, J.G.,
Unsupervised Semantic Scene Labeling for Streaming Data,
CVPR17(5910-5919)
IEEE DOI 1711
Adaptation models, Data models, Image segmentation, Labeling, Semantics, Streaming media, Visualization BibRef

Bulň, S.R., Neuhold, G., Kontschieder, P.,
Loss Max-Pooling for Semantic Image Segmentation,
CVPR17(7082-7091)
IEEE DOI 1711
Benchmark testing, Image segmentation, Semantics, Standards, Training, Upper, bound BibRef

He, Y.[Yang], Keuper, M.[Margret], Schiele, B.[Bernt], Fritz, M.[Mario],
Learning Dilation Factors for Semantic Segmentation of Street Scenes,
GCPR17(41-51).
Springer DOI 1711
BibRef

Jégou, S.[Simon], Drozdzal, M.[Michal], Vazquez, D.[David], Romero, A.[Adriana], Bengio, Y.[Yoshua],
The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation,
CVVT17(1175-1183)
IEEE DOI 1709
Benchmark testing, Computer architecture, Image segmentation, Semantics, Spatial resolution, Standards BibRef

Derue, F.X.[François-Xavier], Dahmane, M.[Mohamed], Lalonde, M.[Marc], Foucher, S.[Samuel],
Exploiting Semantic Segmentation for Robust Camera Motion Classification,
ICIAR17(173-181).
Springer DOI 1706
BibRef

Hazirbas, C.[Caner], Ma, L.N.[Ling-Ni], Domokos, C.[Csaba], Cremers, D.[Daniel],
FuseNet: Incorporating Depth into Semantic Segmentation via Fusion-Based CNN Architecture,
ACCV16(I: 213-228).
Springer DOI 1704
BibRef

Bouachir, W., Torabi, A., Bilodeau, G.A., Blais, P.,
A bag of words approach for semantic segmentation of monitored scenes,
ISIVC16(88-93)
IEEE DOI 1704
Bayes methods BibRef

Souly, N.[Nasim], Shah, M.[Mubarak],
Scene Labeling Using Sparse Precision Matrix,
CVPR16(3650-3658)
IEEE DOI 1612
BibRef

Xu, C., Corso, J.J.[Jason J.],
Actor-Action Semantic Segmentation with Grouping Process Models,
CVPR16(3083-3092)
IEEE DOI 1612
BibRef

Gao, Y.[Yang], Beijbom, O.[Oscar], Zhang, N.[Ning], Darrell, T.J.[Trevor J.],
Compact Bilinear Pooling,
CVPR16(317-326)
IEEE DOI 1612
BibRef

Bearman, A.[Amy], Russakovsky, O.[Olga], Ferrari, V.[Vittorio], Fei-Fei, L.[Li],
What's the Point: Semantic Segmentation with Point Supervision,
ECCV16(VII: 549-565).
Springer DOI 1611
BibRef

Ghiasi, G.[Golnaz], Fowlkes, C.C.[Charless C.],
Laplacian Pyramid Reconstruction and Refinement for Semantic Segmentation,
ECCV16(III: 519-534).
Springer DOI 1611
BibRef

Fourure, D.[Damien], Emonet, R.[Rémi], Fromont, E.[Elisa], Muselet, D.[Damien], Trémeau, A.[Alain], Wolf, C.[Christian],
Semantic Segmentation via Multi-task, Multi-domain Learning,
SSSPR16(333-343).
Springer DOI 1611
BibRef

Tarashima, S., Pan, J., Irie, G., Kurozumi, T., Kinebuchi, T.,
Joint object discovery and segmentation with image-wise reconstruction error,
ICIP16(849-853)
IEEE DOI 1610
Airplanes BibRef

Zhou, H., Zhang, J.[Jun], Lei, J.[Jun], Li, S.[Shuohao], Tu, D.[Dan],
Image semantic segmentation based on FCN-CRF model,
ICIVC16(9-14)
IEEE DOI 1610
feature extraction BibRef

Tian, Q., Li, B.,
Simultaneous semantic segmentation of a set of partially labeled images,
WACV16(1-9)
IEEE DOI 1606
Computer science BibRef

Qi, X.J.[Xiao-Juan], Liu, Z.Z.[Zheng-Zhe], Shi, J.P.[Jian-Ping], Zhao, H.S.[Heng-Shuang], Jia, J.Y.[Jia-Ya],
Augmented Feedback in Semantic Segmentation Under Image Level Supervision,
ECCV16(VIII: 90-105).
Springer DOI 1611
BibRef

Qi, X.J.[Xiao-Juan], Shi, J.P.[Jian-Ping], Liu, S., Liao, R., Jia, J.Y.[Jia-Ya],
Semantic Segmentation with Object Clique Potential,
ICCV15(2587-2595)
IEEE DOI 1602
Computational modeling BibRef

Caesar, H.[Holger], Uijlings, J.[Jasper], Ferrari, V.[Vittorio],
Region-Based Semantic Segmentation with End-to-End Training,
ECCV16(I: 381-397).
Springer DOI 1611
BibRef
Earlier:
Joint Calibration for Semantic Segmentation,
BMVC15(xx-yy).
DOI Link 1601
BibRef

Srivatsa, R.S.[R. Sai], Babu, R.V.[R. Venkatesh],
Salient object detection via objectness measure,
ICIP15(4481-4485)
IEEE DOI 1512
Image Saliency; Image Segmentation; Objectness Proposals; Superpixels BibRef

Ventura, C.[Carles], Giro-i-Nieto, X.[Xavier], Vilaplana, V.[Veronica], McGuinness, K.[Kevin], Marques, F.[Ferran], O'Connor, N.E.[Noel E.],
Improving spatial codification in semantic segmentation,
ICIP15(3605-3609)
IEEE DOI 1512
Object recognition BibRef

Zhao, N.[Nan], Banerjee, C.[Chaity], Liu, X.W.[Xiu-Wen],
Nano-scale context-sensitive semantic segmentation,
ICIP15(3062-3066)
IEEE DOI 1512
Nano-scale; context-sensitive; microvilli; semantic segmentation; spike BibRef

Dai, J.F.[Ji-Feng], He, K.M.[Kai-Ming], Sun, J.[Jian],
Convolutional feature masking for joint object and stuff segmentation,
CVPR15(3992-4000)
IEEE DOI 1510
BibRef

Mostajabi, M.[Mohammadreza], Yadollahpour, P.[Payman], Shakhnarovich, G.[Gregory],
Feedforward semantic segmentation with zoom-out features,
CVPR15(3376-3385)
IEEE DOI 1510
BibRef

Ardeshir, S.[Shervin], Collins-Sibley, K.M.[Kofi Malcolm], Shah, M.[Mubarak],
Geo-semantic segmentation,
CVPR15(2792-2799)
IEEE DOI 1510
BibRef

Zhu, G.[Gao], Ming, Y.S.[Yan-Sheng], Li, H.D.[Hong-Dong],
Object category detection by incorporating mid-level grouping cues,
ICIP14(1604-1608)
IEEE DOI 1502
Computer vision BibRef

Bassiouny, A.[Ahmed], El-Saban, M.[Motaz],
Semantic segmentation as image representation for scene recognition,
ICIP14(981-985)
IEEE DOI 1502
Accuracy BibRef

Tegen, A.[Agnes], Weegar, R.[Rebecka], Hammarlund, L.[Linus], Oskarsson, M.[Magnus], Jiang, F.Y.[Fang-Yuan], Medved, D.[Dennis], Nugues, P.[Pierre], Astrom, K.[Kalle],
Image Segmentation and Labeling Using Free-Form Semantic Annotation,
ICPR14(2281-2286)
IEEE DOI 1412
Context BibRef

Kroeger, T.[Thorben], Kappes, J.H.[Jörg H.], Beier, T.[Thorsten], Koethe, U.[Ullrich], Hamprecht, F.A.[Fred A.],
Asymmetric Cuts: Joint Image Labeling and Partitioning,
GCPR14(199-211).
Springer DOI 1411
BibRef

Ladicky, L.[Lubor], Shi, J.B.[Jian-Bo], Pollefeys, M.[Marc],
Pulling Things out of Perspective,
CVPR14(89-96)
IEEE DOI 1409
Depth Estimation; Object Recognition; Semantic Segmentation BibRef

Mottaghi, R.[Roozbeh], Chen, X.J.[Xian-Jie], Liu, X.B.[Xiao-Bai], Cho, N.G.[Nam-Gyu], Lee, S.W.[Seong-Whan], Fidler, S.[Sanja], Urtasun, R.[Raquel], Yuille, A.L.[Alan L.],
The Role of Context for Object Detection and Semantic Segmentation in the Wild,
CVPR14(891-898)
IEEE DOI 1409
BibRef

Li, Z.Y.[Zhen-Yang], Gavves, E.[Efstratios], Mensink, T.[Thomas], Snoek, C.G.M.[Cees G.M.],
Attributes Make Sense on Segmented Objects,
ECCV14(VI: 350-365).
Springer DOI 1408
BibRef

Dong, J.[Jian], Chen, Q.A.[Qi-Ang], Yan, S.C.[Shui-Cheng], Yuille, A.L.[Alan L.],
Towards Unified Object Detection and Semantic Segmentation,
ECCV14(V: 299-314).
Springer DOI 1408
Joint detect and segment. BibRef

Riemenschneider, H.[Hayko], Bódis-Szomorú, A.[András], Weissenberg, J.[Julien], Van Gool, L.J.[Luc J.],
Learning Where to Classify in Multi-view Semantic Segmentation,
ECCV14(V: 516-532).
Springer DOI 1408
BibRef

Tao, L.L.[Ling-Ling], Porikli, F.M.[Fatih M.], Vidal, R.[René],
Sparse Dictionaries for Semantic Segmentation,
ECCV14(V: 549-564).
Springer DOI 1408
BibRef

Zhu, S.Q.[Sheng-Qi], Yang, Y.Q.[Yi-Qing], Zhang, L.[Li],
From Label Maps to Label Strokes: Semantic Segmentation for Street Scenes from Incomplete Training Data,
CVCP13(468-475)
IEEE DOI 1403
data handling BibRef

Baek, S.[Seung_Ryul], Lim, T.[Taegyu], Heo, Y.S.[Yong Seok], Park, S.B.[Sung-Bum], Kwak, H.[Hantak], Shim, W.[Woosung],
Superpixel Coherency and Uncertainty Models for Semantic Segmentation,
PGMs13(275-282)
IEEE DOI 1403
computational complexity BibRef

Barron, J.T.[Jonathan T.], Biggin, M.D.[Mark D.], Arbelaez, P.[Pablo], Knowles, D.W.[David W.], Keranen, S.V.E.[Soile V.E.], Malik, J.[Jitendra],
Volumetric Semantic Segmentation Using Pyramid Context Features,
ICCV13(3448-3455)
IEEE DOI 1403
BibRef

Singh, G.[Gautam], Kosecka, J.[Jana],
Introspective semantic segmentation,
WACV14(714-720)
IEEE DOI 1406
BibRef
Earlier:
Nonparametric Scene Parsing with Adaptive Feature Relevance and Semantic Context,
CVPR13(3151-3157)
IEEE DOI 1309
feature relevance; scene understanding; semantic segmentation. Small patches, simple features. Accuracy. BibRef

Csurka, G.[Gabriela], Larlus, D.[Diane], Perronnin, F.[Florent],
What is a good evaluation measure for semantic segmentation?,
BMVC13(xx-yy).
DOI Link 1402
BibRef

Li, F.X.[Fu-Xin], Carreira, J.[Joao], Lebanon, G.[Guy], Sminchisescu, C.[Cristian],
Composite Statistical Inference for Semantic Segmentation,
CVPR13(3302-3309)
IEEE DOI 1309
composite likelihood BibRef

Fröhlich, B.[Björn], Rodner, E.[Erik], Denzler, J.[Joachim],
Semantic Segmentation with Millions of Features: Integrating Multiple Cues in a Combined Random Forest Approach,
ACCV12(I:218-231).
Springer DOI 1304
BibRef
And:
As Time Goes by: Anytime Semantic Segmentation with Iterative Context Forests,
DAGM12(1-10).
Springer DOI 1209
BibRef

Hariharan, B.[Bharath], Zitnick, C.L.[C. Lawrence], Dollar, P.[Piotr],
Detecting Objects Using Deformation Dictionaries,
CVPR14(1995-2002)
IEEE DOI 1409
BibRef

Fidler, S.[Sanja], Mottaghi, R.[Roozbeh], Yuille, A.L.[Alan L.], Urtasun, R.[Raquel],
Bottom-Up Segmentation for Top-Down Detection,
CVPR13(3294-3301)
IEEE DOI 1309
Object detection; object class recognition; object segmentation BibRef

Yao, J.[Jian], Fidler, S.[Sanja], Urtasun, R.[Raquel],
Describing the scene as a whole: Joint object detection, scene classification and semantic segmentation,
CVPR12(702-709).
IEEE DOI 1208
BibRef

Pohlen, T., Badami, I., Mathias, M., Leibe, B.[Bastian],
Semantic segmentation of modular furniture,
WACV16(1-9)
IEEE DOI 1606
Face BibRef

Floros, G.[Georgios], Rematas, K.[Konstantinos], Leibe, B.[Bastian],
Multi-Class Image Labeling with Top-Down Segmentation and Generalized Robust P^N Potentials,
BMVC11(xx-yy).
HTML Version. 1110
BibRef

Passino, G.[Giuseppe], Patras, I.[Ioannis], Izquierdo, E.[Ebroul],
Pyramidal Model for Image Semantic Segmentation,
ICPR10(1554-1557).
IEEE DOI 1008
BibRef

Schnitman, Y.[Yaar], Caspi, Y.[Yaron], Cohen-Or, D.[Daniel], Lischinski, D.[Dani],
Inducing Semantic Segmentation from an Example,
ACCV06(II:373-384).
Springer DOI 0601
BibRef

Zhang, H.H.[Hong-Hui], Xiao, J.X.[Jian-Xiong], Quan, L.[Long],
Supervised Label Transfer for Semantic Segmentation of Street Scenes,
ECCV10(V: 561-574).
Springer DOI 1009
Set of labelled images of street scenes. Recognition is by matching at image level, then using the given lables. BibRef

Chapter on 2-D Region Segmentation Techniques, Snakes, Active Contours continues in
Vision Transformers for Semantic Segmentation .


Last update:May 23, 2024 at 14:31:23