Fu, H.,
Cao, X.,
Tu, Z.,
Cluster-Based Co-Saliency Detection,
IP(22), No. 10, 2013, pp. 3766-3778.
IEEE DOI
1309
Saliency detection
BibRef
Liu, Z.[Zhi],
Zou, W.B.[Wen-Bin],
Li, L.[Lina],
Shen, L.Q.[Li-Quan],
Le Meur, O.,
Co-Saliency Detection Based on Hierarchical Segmentation,
SPLetters(21), No. 1, January 2014, pp. 88-92.
IEEE DOI
1402
image segmentation
BibRef
Liu, Z.[Zhi],
Zhang, X.[Xiang],
Luo, S.H.[Shu-Hua],
Le Meur, O.,
Superpixel-Based Spatiotemporal Saliency Detection,
CirSysVideo(24), No. 9, September 2014, pp. 1522-1540.
IEEE DOI
1410
feature extraction
BibRef
Li, J.H.[Jun-Hao],
Liu, Z.[Zhi],
Zhang, X.[Xiang],
Le Meur, O.[Olivier],
Shen, L.Q.[Li-Quan],
Spatiotemporal saliency detection based on superpixel-level
trajectory,
SP:IC(38), No. 1, 2015, pp. 100-114.
Elsevier DOI
1512
Spatiotemporal saliency detection
BibRef
Liu, Z.[Zhi],
Li, J.H.[Jun-Hao],
Ye, L.,
Sun, G.,
Shen, L.Q.[Li-Quan],
Saliency Detection for Unconstrained Videos Using Superpixel-Level
Graph and Spatiotemporal Propagation,
CirSysVideo(27), No. 12, December 2017, pp. 2527-2542.
IEEE DOI
1712
Computational modeling, Feature extraction, Histograms,
Motion measurement, Spatiotemporal phenomena, Videos,
unconstrained video
BibRef
Zhou, X.F.[Xiao-Fei],
Liu, Z.[Zhi],
Li, K.[Kai],
Sun, G.L.[Guang-Ling],
Video Saliency Detection via Bagging-Based Prediction and
Spatiotemporal Propagation,
JVCIR(51), 2018, pp. 131-143.
Elsevier DOI
1802
Spatiotemporal saliency, Unconstrained video, Bagging,
Prediction, Propagation
BibRef
Zhou, X.F.[Xiao-Fei],
Liu, Z.[Zhi],
Gong, C.,
Liu, W.,
Improving Video Saliency Detection via Localized Estimation and
Spatiotemporal Refinement,
MultMed(20), No. 11, November 2018, pp. 2993-3007.
IEEE DOI
1810
Saliency detection, Spatiotemporal phenomena, Estimation,
Computational modeling, Feature extraction, saliency update
BibRef
Tsai, C.,
Hsu, K.,
Lin, Y.,
Qian, X.,
Chuang, Y.,
Deep Co-Saliency Detection via Stacked Autoencoder-Enabled Fusion and
Self-Trained CNNs,
MultMed(22), No. 4, April 2020, pp. 1016-1031.
IEEE DOI
2004
Proposals, Saliency detection, Image segmentation,
Image reconstruction, Reliability, Task analysis, Fuses, CNNs
BibRef
Li, H.L.[Hong-Liang],
Meng, F.M.[Fan-Man],
Ngan, K.N.[King Ngi],
Co-Salient Object Detection From Multiple Images,
MultMed(15), No. 8, December 2013, pp. 1896-1909.
IEEE DOI
1402
feature extraction
BibRef
Cao, X.C.[Xiao-Chun],
Tao, Z.Q.[Zhi-Qiang],
Zhang, B.[Bao],
Fu, H.Z.[Hua-Zhu],
Feng, W.[Wei],
Self-Adaptively Weighted Co-Saliency Detection via Rank Constraint,
IP(23), No. 9, September 2014, pp. 4175-4186.
IEEE DOI
1410
the common salient objects existing in multiple images.
BibRef
Du, S.[Shuze],
Chen, S.F.[Shi-Feng],
Detecting Co-Salient Objects in Large Image Sets,
SPLetters(22), No. 2, February 2015, pp. 145-148.
IEEE DOI
1410
computer vision
BibRef
Zhang, D.W.[Ding-Wen],
Han, J.W.[Jun-Wei],
Li, C.[Chao],
Wang, J.D.[Jing-Dong],
Li, X.L.[Xue-Long],
Detection of Co-salient Objects by Looking Deep and Wide,
IJCV(120), No. 2, November 2016, pp. 215-232.
Springer DOI
1609
BibRef
Ye, L.W.[Lin-Wei],
Liu, Z.[Zhi],
Li, J.H.[Jun-Hao],
Zhao, W.L.[Wan-Lei],
Shen, L.Q.[Li-Quan],
Co-Saliency Detection via Co-Salient Object Discovery and Recovery,
SPLetters(22), No. 11, November 2015, pp. 2073-2077.
IEEE DOI
1509
feature extraction
BibRef
Fan, X.X.[Xing-Xing],
Liu, Z.[Zhi],
Ye, L.W.[Lin-Wei],
Salient Object Segmentation from Stereoscopic Images,
GbRPR15(272-281).
Springer DOI
1511
BibRef
Zhang, D.,
Meng, D.,
Han, J.,
Co-Saliency Detection via a Self-Paced Multiple-Instance Learning
Framework,
PAMI(39), No. 5, May 2017, pp. 865-878.
IEEE DOI
1704
Automation
BibRef
Zhang, D.,
Meng, D.,
Li, C.,
Jiang, L.,
Zhao, Q.,
Han, J.,
A Self-Paced Multiple-Instance Learning Framework for Co-Saliency
Detection,
ICCV15(594-602)
IEEE DOI
1602
Context
BibRef
Jerripothula, K.R.[Koteswar Rao],
Cai, J.F.[Jian-Fei],
Yuan, J.S.[Jun-Song],
Quality-Guided Fusion-Based Co-Saliency Estimation for Image
Co-Segmentation and Colocalization,
MultMed(20), No. 9, September 2018, pp. 2466-2477.
IEEE DOI
1809
BibRef
Earlier:
Group saliency propagation for large scale and quick image
co-segmentation,
ICIP15(4639-4643)
IEEE DOI
1512
feature extraction, image fusion, image segmentation,
Quality-Guided Fusion-Based Co-Saliency Estimation,
quality.
ImageNet; co-segmentation; group; large scale; propagation.
BibRef
Jerripothula, K.R.[Koteswar Rao],
Cai, J.F.[Jian-Fei],
Meng, F.M.[Fan-Man],
Yuan, J.S.[Jun-Song],
Automatic Image Co-Segmentation Using Geometric Mean Saliency,
ICIP14(3277-3281)
IEEE DOI
1502
Computer vision
BibRef
Umeki, Y.[Yo],
Yoshida, T.[Taichi],
Iwahashi, M.[Masahiro],
Co-Propagation with Distributed Seeds for Salient Object Detection,
IEICE(E101-D), No. 6, June 2018, pp. 1640-1647.
WWW Link.
1806
BibRef
Tao, Q.Y.[Qing-Yi],
Yang, H.[Hao],
Cai, J.F.[Jian-Fei],
Exploiting Web Images for Weakly Supervised Object Detection,
MultMed(21), No. 5, May 2019, pp. 1135-1146.
IEEE DOI
1905
convolutional neural nets, Internet,
learning (artificial intelligence), object detection,
curriculum learning
BibRef
Jerripothula, K.R.[Koteswar Rao],
Cai, J.F.[Jian-Fei],
Yuan, J.S.[Jun-Song],
QCCE:
Quality constrained co-saliency estimation for common object detection,
VCIP15(1-4)
IEEE DOI
1605
Estimation
BibRef
Jeong, D.,
Hwang, I.,
Cho, N.I.,
Co-Salient Object Detection Based on Deep Saliency Networks and Seed
Propagation Over an Integrated Graph,
IP(27), No. 12, December 2018, pp. 5866-5879.
IEEE DOI
1810
Image segmentation, Feature extraction, Saliency detection,
Image color analysis, Object detection, Iris, Semantics, Co-saliency,
foreground probability
BibRef
Tsai, C.C.[Chung-Chi],
Li, W.Z.[Wei-Zhi],
Hsu, K.J.[Kuang-Jui],
Qian, X.N.[Xiao-Ning],
Lin, Y.Y.[Yen-Yu],
Image Co-Saliency Detection and Co-Segmentation via Progressive Joint
Optimization,
IP(28), No. 1, January 2019, pp. 56-71.
IEEE DOI
1810
graphs, image segmentation, object detection, optimisation,
progressive joint optimization, multiple images,
joint optimization
BibRef
Hsu, K.J.[Kuang-Jui],
Tsai, C.C.[Chung-Chi],
Lin, Y.Y.[Yen-Yu],
Qian, X.N.[Xiao-Ning],
Chuang, Y.Y.[Yung-Yu],
Unsupervised CNN-Based Co-saliency Detection with Graphical
Optimization,
ECCV18(VI: 502-518).
Springer DOI
1810
BibRef
Jerripothula, K.R.[Koteswar Rao],
Cai, J.F.[Jian-Fei],
Yuan, J.S.[Jun-Song],
Efficient Video Object Co-Localization With Co-Saliency Activated
Tracklets,
CirSysVideo(29), No. 3, March 2019, pp. 744-755.
IEEE DOI
1903
Jointly locate common visual objects across videos.
Tracking, Proposals, Benchmark testing,
Task analysis, Object recognition, Semantics, Tracklets, video,
co-saliency
BibRef
Jerripothula, K.R.[Koteswar Rao],
Cai, J.F.[Jian-Fei],
Lu, J.,
Yuan, J.S.[Jun-Song],
Image Co-Skeletonization via Co-Segmentation,
IP(30), 2021, pp. 2784-2797.
IEEE DOI
2102
Skeleton, Image segmentation, Shape, Task analysis, Annotations,
Semantics, Training, Skeletonization, segmentation, co-segmentation,
CO-SKELARGE
BibRef
Jerripothula, K.R.[Koteswar Rao],
Cai, J.F.[Jian-Fei],
Yuan, J.S.[Jun-Song],
CATS: Co-saliency Activated Tracklet Selection for Video
Co-Localization,
ECCV16(VII: 187-202).
Springer DOI
1611
jointly localizing common objects across videos
BibRef
Wei, L.[Lina],
Zhao, S.S.[Shan-Shan],
Bourahla, O.E.[Omar El_Farouk],
Li, X.[Xi],
Wu, F.[Fei],
Zhuang, Y.T.[Yue-Ting],
Deep Group-Wise Fully Convolutional Network for Co-Saliency Detection
With Graph Propagation,
IP(28), No. 10, October 2019, pp. 5052-5063.
IEEE DOI
1909
Feature extraction, Object detection, Task analysis,
Saliency detection, Semantics, Collaborative work, Deep learning,
jointly optimize
BibRef
Gao, G.S.[Guang-Shuai],
Zhao, W.T.[Wen-Ting],
Liu, Q.J.[Qing-Jie],
Wang, Y.H.[Yun-Hong],
Co-Saliency Detection With Co-Attention Fully Convolutional Network,
CirSysVideo(31), No. 3, March 2021, pp. 877-889.
IEEE DOI
2103
Feature extraction, Saliency detection, Task analysis, Convolution,
Image segmentation, Semantics, Predictive models,
deep supervised
BibRef
Fan, D.P.[Deng-Ping],
Li, T.P.[Teng-Peng],
Lin, Z.[Zheng],
Ji, G.P.[Ge-Peng],
Zhang, D.W.[Ding-Wen],
Cheng, M.M.[Ming-Ming],
Fu, H.Z.[Hua-Zhu],
Shen, J.B.[Jian-Bing],
Re-Thinking Co-Salient Object Detection,
PAMI(44), No. 8, August 2022, pp. 4339-4354.
IEEE DOI
2207
Benchmark testing, Object detection, Measurement, Semantics,
Task analysis, Annotations, Optimization, benchmark
BibRef
Tang, L.[Lv],
Li, B.[Bo],
Kuang, S.[Senyun],
Song, M.[Mofei],
Ding, S.H.[Shou-Hong],
Re-Thinking the Relations in Co-Saliency Detection,
CirSysVideo(32), No. 8, August 2022, pp. 5453-5466.
IEEE DOI
2208
Task analysis, Feature extraction, Reinforcement learning,
Object detection, Saliency detection, Visualization, Semantics,
graph convolutional network
BibRef
Li, B.[Bo],
Tang, L.[Lv],
Kuang, S.[Senyun],
Song, M.[Mofei],
Ding, S.H.[Shou-Hong],
Toward Stable Co-Saliency Detection and Object Co-Segmentation,
IP(31), 2022, pp. 6532-6547.
IEEE DOI
2211
Task analysis, Image segmentation, Saliency detection, Training,
Recurrent neural networks, Feature extraction, Semantics,
contrastive loss
BibRef
Wang, Y.[Yu],
Li, S.[Shuxiao],
Similarity activation map for co-salient object detection,
PRL(163), 2022, pp. 159-167.
Elsevier DOI
2212
Co-salient object detection, Similarity activation map,
Feature modulation, Edge guidance
BibRef
Bai, Z.[Zhen],
Liu, Z.[Zhi],
Li, G.Y.[Gong-Yang],
Wang, Y.[Yang],
Adaptive Group-Wise Consistency Network for Co-Saliency Detection,
MultMed(25), 2023, pp. 764-776.
IEEE DOI
2303
Feature extraction, Adaptation models, Decoding, Semantics,
Global communication, Aggregates, Prediction algorithms,
semantic information
BibRef
Li, T.P.[Teng-Peng],
Zhang, K.[Kaihua],
Shen, S.[Shiwen],
Liu, B.[Bo],
Liu, Q.S.[Qing-Shan],
Li, Z.[Zhu],
Image Co-Saliency Detection and Instance Co-Segmentation Using
Attention Graph Clustering Based Graph Convolutional Network,
MultMed(24), 2022, pp. 492-505.
IEEE DOI
2202
Integrated circuits, Image segmentation, Task analysis,
Feature extraction, Decoding, Clustering algorithms,
instance co-segmentation
BibRef
Ge, Y.L.[Yan-Liang],
Zhang, Q.[Qiao],
Xiang, T.Z.[Tian-Zhu],
Zhang, C.[Cong],
Zhang, J.[Jing],
Bi, H.B.[Hong-Bo],
GSNNet: Group semantic-guided neighbor interaction network for
co-salient object detection,
CVIU(227), 2023, pp. 103611.
Elsevier DOI
2301
Co-salient object detection, Salient object detection,
Group semantic information, Neighbor interaction
BibRef
Wang, Y.[Yu],
Li, S.[Shuxiao],
Hierarchical interaction and pooling network for co-salient object
detection,
IVC(132), 2023, pp. 104647.
Elsevier DOI
2303
Co-salient object detection, Four-branch network,
Hierarchical architecture, Pyramid pooling interaction
BibRef
Zheng, P.[Peng],
Fu, H.Z.[Hua-Zhu],
Fan, D.P.[Deng-Ping],
Fan, Q.[Qi],
Qin, J.[Jie],
Tai, Y.W.[Yu-Wing],
Tang, C.K.[Chi-Keung],
Van Gool, L.J.[Luc J.],
GCoNet+: A Stronger Group Collaborative Co-Salient Object Detector,
PAMI(45), No. 9, September 2023, pp. 10929-10946.
IEEE DOI
2309
BibRef
Zhang, N.[Ni],
Liu, N.[Nian],
Nan, F.[Fang],
Han, J.W.[Jun-Wei],
CADC++: Advanced Consensus-Aware Dynamic Convolution for Co-Salient
Object Detection,
PAMI(46), No. 5, May 2024, pp. 2741-2757.
IEEE DOI
2404
Adaptation models, Convolution, Scalability, Object detection,
Search problems, Feature extraction, Robustness,
saliency detection
BibRef
Li, L.[Long],
Han, J.W.[Jun-Wei],
Zhang, N.[Ni],
Liu, N.[Nian],
Khan, S.[Salman],
Cholakkal, H.[Hisham],
Anwer, R.M.[Rao Muhammad],
Khan, F.S.[Fahad Shahbaz],
Discriminative Co-Saliency and Background Mining Transformer for
Co-Salient Object Detection,
CVPR23(7247-7256)
IEEE DOI
2309
BibRef
Guo, R.[Ruohao],
Ying, X.H.[Xiang-Hua],
Qi, Y.[Yanyu],
Qu, L.[Liao],
UniTR: A Unified TRansformer-Based Framework for Co-Object and
Multi-Modal Saliency Detection,
MultMed(26), 2024, pp. 7622-7635.
IEEE DOI
2405
Object detection, Feature extraction, Task analysis, Transformers,
Image segmentation, Semantics, Computer architecture,
deep learning
BibRef
Wu, Y.[Yang],
Song, H.H.[Hui-Hui],
Liu, B.[Bo],
Zhang, K.[Kaihua],
Liu, D.[Dong],
Co-Salient Object Detection with Uncertainty-Aware Group
Exchange-Masking,
CVPR23(19639-19648)
IEEE DOI
2309
BibRef
Lee, M.[Minhyeok],
Park, C.[Chaewon],
Cho, S.[Suhwan],
Lee, S.Y.[Sang-Youn],
Superpixel Group-Correlation Network for Co-Saliency Detection,
ICIP22(806-810)
IEEE DOI
2211
Image segmentation, Benchmark testing, Feature extraction,
Task analysis, Co-saliency Detection, Superpixel Algorithm
BibRef
Yu, S.Y.[Si-Yue],
Xiao, J.[Jimin],
Zhang, B.F.[Bing-Feng],
Lim, E.G.[Eng Gee],
Democracy Does Matter:
Comprehensive Feature Mining for Co-Salient Object Detection,
CVPR22(969-978)
IEEE DOI
2210
Codes, Aggregates, Prototypes, Object detection, Interference,
Feature extraction, Recognition: detection, categorization,
grouping and shape analysis
BibRef
Stoian, I.S.[Ioana-Sabina],
Sandu, I.C.[Ionut-Catalin],
Voinea, D.[Daniel],
Popa, A.I.[Alin-Ionut],
Unstructured Object Matching using Co-Salient Region Segmentation,
IMW22(5047-5056)
IEEE DOI
2210
Deep learning, Image segmentation, Kinematics,
Search problems, Pattern recognition
BibRef
Fan, Q.[Qi],
Fan, D.P.[Deng-Ping],
Fu, H.[Huazhu],
Tang, C.K.[Chi-Keung],
Shao, L.[Ling],
Tai, Y.W.[Yu-Wing],
Group Collaborative Learning for Co-Salient Object Detection,
CVPR21(12283-12293)
IEEE DOI
2111
Codes, Computational modeling, Semantics,
Object detection, Benchmark testing, Collaborative work
BibRef
Qiao, J.Q.[Jia-Qing],
Sun, S.W.[Shao-Wei],
Xu, M.Z.[Ming-Zhu],
Li, Y.Q.[Yong-Qiang],
Liu, B.[Bing],
Co-Saliency Detection Via Unified Hierarchical Graph Neural Network
With Geometric Attention,
ICIP21(1349-1353)
IEEE DOI
2201
Image segmentation, Benchmark testing, Feature extraction,
Graph neural networks, Cognition, Image restoration, self-attention
BibRef
Fan, D.,
Lin, Z.,
Ji, G.,
Zhang, D.,
Fu, H.,
Cheng, M.,
Taking a Deeper Look at Co-Salient Object Detection,
CVPR20(2916-2926)
IEEE DOI
2008
Object detection, Adaptation models, Task analysis,
Computational modeling, Benchmark testing, Image color analysis, Semantics
BibRef
Hsu, K.J.[Kuang-Jui],
Lin, Y.Y.[Yen-Yu],
Chuang, Y.Y.[Yung-Yu],
DeepCO3: Deep Instance Co-Segmentation by Co-Peak Search and
Co-Saliency Detection,
CVPR19(8838-8847).
IEEE DOI
2002
BibRef
Chang, K.Y.[Kai-Yueh],
Liu, T.L.[Tyng-Luh],
Lai, S.H.[Shang-Hong],
From co-saliency to co-segmentation:
An efficient and fully unsupervised energy minimization model,
CVPR11(2129-2136).
IEEE DOI
1106
BibRef
Chapter on 2-D Region Segmentation Techniques, Snakes, Active Contours continues in
Semantic Segmentation, Label and Segment Together .