Hu, X.[Xiang],
Li, T.[Teng],
Zhou, T.[Tong],
Peng, Y.X.[Yuan-Xi],
Deep Spatial-Spectral Subspace Clustering for Hyperspectral Images
Based on Contrastive Learning,
RS(13), No. 21, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Hassanin, M.[Mohammed],
Radwan, I.[Ibrahim],
Khan, S.[Salman],
Tahtali, M.[Murat],
Learning discriminative representations for multi-label image
recognition,
JVCIR(83), 2022, pp. 103448.
Elsevier DOI
2202
Multi-label recognition, Multi-label-contrastive learning,
Contrastive representation, Deep learning
BibRef
Dave, I.[Ishan],
Gupta, R.[Rohit],
Rizve, M.N.[Mamshad Nayeem],
Shah, M.[Mubarak],
TCLR: Temporal contrastive learning for video representation,
CVIU(219), 2022, pp. 103406.
Elsevier DOI
2205
Self-Supervised Learning, Action Recognition, Video Representation
BibRef
Li, Y.F.[Yun-Fan],
Yang, M.X.[Mou-Xing],
Peng, D.Z.[De-Zhong],
Li, T.H.[Tai-Hao],
Huang, J.T.[Jian-Tao],
Peng, X.[Xi],
Twin Contrastive Learning for Online Clustering,
IJCV(130), No. 9, September 2022, pp. 2205-2221.
Springer DOI
2208
BibRef
Zhu, H.[He],
Yu, S.[Shan],
Retaining Diverse Information in Contrastive Learning Through
Multiple Projectors,
SPLetters(29), 2022, pp. 1789-1793.
IEEE DOI
2209
Visualization, Training, Task analysis, Representation learning,
Feature extraction, Periodic structures, Indexes, projector mining
BibRef
Huo, X.Y.[Xin-Yue],
Xie, L.X.[Ling-Xi],
Wei, L.H.[Long-Hui],
Zhang, X.P.[Xiao-Peng],
Chen, X.[Xin],
Li, H.[Hao],
Yang, Z.J.[Zi-Jie],
Zhou, W.G.[Wen-Gang],
Li, H.Q.[Hou-Qiang],
Tian, Q.[Qi],
Heterogeneous Contrastive Learning:
Encoding Spatial Information for Compact Visual Representations,
MultMed(24), 2022, pp. 4224-4235.
IEEE DOI
2209
Pretraining -- improve efficiency.
Feature extraction, Semantics, Head, Contrastive learning,
pre-training, spatial information
BibRef
Liu, C.F.[Chen-Fang],
Sun, H.[Hao],
Xu, Y.J.[Yan-Jie],
Kuang, G.Y.[Gang-Yao],
Multi-Source Remote Sensing Pretraining Based on Contrastive
Self-Supervised Learning,
RS(14), No. 18, 2022, pp. xx-yy.
DOI Link
2209
BibRef
Xu, H.H.[Hao-Hang],
Xiong, H.K.[Hong-Kai],
Qi, G.J.[Guo-Jun],
K-Shot Contrastive Learning of Visual Features With Multiple Instance
Augmentations,
PAMI(44), No. 11, November 2022, pp. 8694-8700.
IEEE DOI
2210
Task analysis, Visualization, Training,
Eigenvalues and eigenfunctions, Dictionaries, contrastive learning
BibRef
Zhu, Y.S.[Yi-Sheng],
Shuai, H.[Hui],
Liu, G.C.[Guang-Can],
Liu, Q.S.[Qing-Shan],
Self-Supervised Video Representation Learning Using Improved
Instance-Wise Contrastive Learning and Deep Clustering,
CirSysVideo(32), No. 10, October 2022, pp. 6741-6752.
IEEE DOI
2210
Task analysis, Representation learning, Visualization,
Integrated circuit modeling, Training, Spatiotemporal phenomena,
deep clustering
BibRef
Peng, R.[Rui],
Zhao, W.Z.[Wen-Zhi],
Li, K.Y.[Kai-Yuan],
Ji, F.C.[Feng-Cheng],
Rong, C.X.[Cai-Xia],
Continual Contrastive Learning for Cross-Dataset Scene Classification,
RS(14), No. 20, 2022, pp. xx-yy.
DOI Link
2211
BibRef
Wang, Y.[Yu],
Lin, J.Y.[Jing-Yang],
Cai, Q.[Qi],
Pan, Y.W.[Ying-Wei],
Yao, T.[Ting],
Chao, H.Y.[Hong-Yang],
Mei, T.[Tao],
A Low Rank Promoting Prior for Unsupervised Contrastive Learning,
PAMI(45), No. 3, March 2023, pp. 2667-2681.
IEEE DOI
2302
Training, Task analysis, Probabilistic logic, Feature extraction,
Optimization, Annotations, Unsupervised learning,
unsupervised pre-training
BibRef
Xu, X.Y.[Xin-Yi],
Deng, C.[Cheng],
Xie, Y.C.[Yao-Chen],
Ji, S.W.[Shui-Wang],
Group Contrastive Self-Supervised Learning on Graphs,
PAMI(45), No. 3, March 2023, pp. 3169-3180.
IEEE DOI
2302
Task analysis, Proteins, Aggregates, Mutual information, Generators,
Upper bound, Optimization, Graph neural networks,
self-supervised learning
BibRef
Zhu, J.H.[Jin-Hua],
Xia, Y.[Yingce],
Wu, L.J.[Li-Jun],
Deng, J.J.[Jia-Jun],
Zhou, W.G.[Wen-Gang],
Qin, T.[Tao],
Liu, T.Y.[Tie-Yan],
Li, H.Q.[Hou-Qiang],
Masked Contrastive Representation Learning for Reinforcement Learning,
PAMI(45), No. 3, March 2023, pp. 3421-3433.
IEEE DOI
2302
Transformers, Training, Task analysis, Representation learning,
Convolutional neural networks, Image reconstruction, Games, transformer
BibRef
Xu, H.H.[Hao-Hang],
Zhang, X.P.[Xiao-Peng],
Li, H.[Hao],
Xie, L.X.[Ling-Xi],
Dai, W.R.[Wen-Rui],
Xiong, H.K.[Hong-Kai],
Tian, Q.[Qi],
Seed the Views: Hierarchical Semantic Alignment for Contrastive
Representation Learning,
PAMI(45), No. 3, March 2023, pp. 3753-3767.
IEEE DOI
2302
Task analysis, Training, Generators, Feature extraction, Semantics,
Representation learning, Image reconstruction, contrastive learning
BibRef
Hu, P.[Peng],
Zhu, H.Y.[Hong-Yuan],
Lin, J.[Jie],
Peng, D.Z.[De-Zhong],
Zhao, Y.P.[Yin-Ping],
Peng, X.[Xi],
Unsupervised Contrastive Cross-Modal Hashing,
PAMI(45), No. 3, March 2023, pp. 3877-3889.
IEEE DOI
2302
Semantics, Bridges, Optimization, Correlation, Task analysis, Degradation,
Binary codes, Common hamming space, unsupervised cross-modal hashing
BibRef
Xia, W.[Wei],
Wang, T.X.[Tian-Xiu],
Gao, Q.X.[Quan-Xue],
Yang, M.[Ming],
Gao, X.B.[Xin-Bo],
Graph Embedding Contrastive Multi-Modal Representation Learning for
Clustering,
IP(32), 2023, pp. 1170-1183.
IEEE DOI
2302
Representation learning, Technological innovation, Deep learning,
Correlation, Clustering methods, Transformers, Telecommunications,
self-supervision
BibRef
Chen, Z.L.[Ze-Lin],
Lin, K.Y.[Kun-Yu],
Zheng, W.S.[Wei-Shi],
Consistent Intra-Video Contrastive Learning With Asynchronous
Long-Term Memory Bank,
CirSysVideo(33), No. 3, March 2023, pp. 1168-1180.
IEEE DOI
2303
Videos, Task analysis, Graphics processing units, Semantics,
Representation learning, Memory management, Intra-video actions, self-attention
BibRef
Fang, U.[Uno],
Li, J.X.[Jian-Xin],
Lu, X.Q.[Xue-Quan],
Mian, A.[Ajmal],
Gu, Z.Q.[Zhao-Quan],
Robust image clustering via context-aware contrastive graph learning,
PR(138), 2023, pp. 109340.
Elsevier DOI
2303
Supervised clustering, Graph convolution network,
Contrastive graph learning, Graph view generation
BibRef
Qin, J.[Jinchun],
Zhao, H.R.[Hong-Rui],
Spatial-Spectral-Associative Contrastive Learning for Satellite
Hyperspectral Image Classification with Transformers,
RS(15), No. 6, 2023, pp. 1612.
DOI Link
2304
BibRef
Zhang, Y.[Yupei],
Xu, Y.[Yunan],
Wei, S.[Shuangshuang],
Wang, Y.F.[Yi-Fei],
Li, Y.X.[Yu-Xin],
Shang, X.[Xuequn],
Doubly contrastive representation learning for federated image
recognition,
PR(139), 2023, pp. 109507.
Elsevier DOI
2304
Image recognition, Doubly contrastive learning,
Federated machine learning, Representation learning,
Non-IID data classification
BibRef
Deng, X.Z.[Xiao-Zhi],
Huang, D.[Dong],
Chen, D.H.[Ding-Hua],
Wang, C.D.[Chang-Dong],
Lai, J.H.[Jian-Huang],
Strongly augmented contrastive clustering,
PR(139), 2023, pp. 109470.
Elsevier DOI
2304
Data clustering, Deep clustering, Image clustering,
Contrastive learning, Deep neural network
BibRef
Wei, R.[Rukai],
Liu, Y.[Yu],
Song, J.K.[Jing-Kuan],
Xie, Y.Z.[Yan-Zhao],
Zhou, K.[Ke],
Deep debiased contrastive hashing,
PR(139), 2023, pp. 109483.
Elsevier DOI
2304
Learning to hash, Contrastive learning,
Instance discrimination, EM Algorithm, Neighborhood discovery
BibRef
Luo, Z.F.[Zhen-Fei],
Dong, Y.X.[Yi-Xiang],
Zheng, Q.H.[Qing-Hua],
Liu, H.[Huan],
Luo, M.[Minnan],
Dual-channel graph contrastive learning for self-supervised
graph-level representation learning,
PR(139), 2023, pp. 109448.
Elsevier DOI
2304
Contrastive learning, Graph representation learning,
Graph neural networks, Graph classification
BibRef
Wang, X.[Xiao],
Qi, G.J.[Guo-Jun],
Contrastive Learning With Stronger Augmentations,
PAMI(45), No. 5, May 2023, pp. 5549-5560.
IEEE DOI
2304
Task analysis, Self-supervised learning, Representation learning,
Prototypes, Visualization, Training, Supervised learning,
self-supervised learning
BibRef
Zhang, Z.[Zehua],
Sun, S.L.[Shi-Lin],
Ma, G.X.[Gui-Xiang],
Zhong, C.M.[Cai-Ming],
Line graph contrastive learning for link prediction,
PR(140), 2023, pp. 109537.
Elsevier DOI
2305
Line graph, Contrastive learning, Link prediction,
Node classification, Mutual information
BibRef
Wei, Y.K.[Yi-Kang],
Yang, L.[Liu],
Han, Y.[Yahong],
Hu, Q.H.[Qing-Hua],
Multi-Source Collaborative Contrastive Learning for Decentralized
Domain Adaptation,
CirSysVideo(33), No. 5, May 2023, pp. 2202-2216.
IEEE DOI
2305
Adaptation models, Feature extraction, Data models, Collaboration,
Data mining, Training, Bridges, Multi-source domain adaptation,
contrastive learning
BibRef
Li, Z.Y.[Zhi-Yuan],
Ralescu, A.[Anca],
Generalized self-supervised contrastive learning with bregman
divergence for image recognition,
PRL(171), 2023, pp. 155-161.
Elsevier DOI
2306
Bregman divergence, Self-supervised learning,
Contrastive learning, Probabilistic distance, Image representation
BibRef
Zhang, Y.H.[Yu-Hang],
Zhang, X.P.[Xiao-Peng],
Li, J.[Jie],
Qiu, R.C.[Robert C.],
Xu, H.H.[Hao-Hang],
Tian, Q.[Qi],
Semi-Supervised Contrastive Learning With Similarity Co-Calibration,
MultMed(25), 2023, pp. 1749-1759.
IEEE DOI
2306
Predictive models, Semisupervised learning, Data models, Training,
Entropy, Labeling, Prototypes, Semi-supervised learning,
similarity co-calibration
BibRef
Lee, W.[Wonju],
Byun, S.Y.[Seok-Yong],
Park, M.J.[Min-Je],
Unsupervised soft-to-hard hashing with contrastive learning,
CVIU(233), 2023, pp. 103713.
Elsevier DOI
2307
Unsupervised hashing, Contrastive learning, Greedy back-propagation
BibRef
Miao, J.X.[Jia-Xing],
Cao, F.L.[Fei-Long],
Li, M.[Ming],
Yang, B.[Bing],
Ye, H.L.[Hai-Liang],
Triplet teaching graph contrastive networks with self-evolving
adaptive augmentation,
PR(142), 2023, pp. 109687.
Elsevier DOI
2307
Contrastive learning, Graph representation learning,
Graph augmentation, Node classification
BibRef
Li, J.H.[Jin-Hui],
Li, X.R.[Xiao-Run],
Yan, Y.F.[Yun-Feng],
Unlocking the Potential of Data Augmentation in Contrastive Learning
for Hyperspectral Image Classification,
RS(15), No. 12, 2023, pp. xx-yy.
DOI Link
2307
BibRef
Wang, J.[Jing],
Tian, S.[Sirui],
Feng, X.L.[Xiao-Lin],
Zhang, B.[Bo],
Wu, F.[Fan],
Zhang, H.[Hong],
Wang, C.[Chao],
Locality Preserving Property Constrained Contrastive Learning for
Object Classification in SAR Imagery,
RS(15), No. 14, 2023, pp. 3697.
DOI Link
2307
BibRef
Guo, H.J.[Hui-Jie],
Shi, L.[Lei],
Contrastive learning with semantic consistency constraint,
IVC(136), 2023, pp. 104754.
Elsevier DOI
2308
Representation learning, Contrastive learning, Semantic consistency
BibRef
Han, A.[Aiyang],
Geng, C.X.[Chuan-Xing],
Chen, S.C.[Song-Can],
Universum-Inspired Supervised Contrastive Learning,
IP(32), 2023, pp. 4275-4286.
IEEE DOI
2308
Data models, Training, Robustness, Reliability theory,
Loss measurement, Visualization, Task analysis, mixup
BibRef
Cho, J.[Junhee],
Ko, Y.J.[Young-Joong],
Dicer: Dialogue-Centric Representation for Knowledge-Grounded
Dialogue through Contrastive Learning,
PRL(172), 2023, pp. 151-157.
Elsevier DOI
2309
Knowledge-grounded dialogue system, Contrastive learning, Negative sampling loss
BibRef
Wang, X.[Xiao],
Huang, Y.H.[Yu-Hang],
Zeng, D.[Dan],
Qi, G.J.[Guo-Jun],
CaCo: Both Positive and Negative Samples are Directly Learnable via
Cooperative-Adversarial Contrastive Learning,
PAMI(45), No. 9, September 2023, pp. 10718-10730.
IEEE DOI
2309
BibRef
Tang, H.[Hao],
Sun, G.[Guolei],
Sebe, N.[Nicu],
Van Gool, L.J.[Luc J.],
Edge Guided GANs With Multi-Scale Contrastive Learning for Semantic
Image Synthesis,
PAMI(45), No. 12, December 2023, pp. 14435-14452.
IEEE DOI
2311
BibRef
Zhao, Y.X.[Yun-Xiao],
Bai, L.[Liang],
Contrastive clustering with a graph consistency constraint,
PR(146), 2024, pp. 110032.
Elsevier DOI
2311
Contrastive learning, Contrastive clustering,
Graph consistency constraint, Clustering uncertainty
BibRef
Xia, W.[Wei],
Wang, Q.Q.[Qian-Qian],
Gao, Q.X.[Quan-Xue],
Yang, M.[Ming],
Gao, X.B.[Xin-Bo],
Self-Consistent Contrastive Attributed Graph Clustering With
Pseudo-Label Prompt,
MultMed(25), 2023, pp. 6665-6677.
IEEE DOI
2311
BibRef
Cheng, H.Y.[Hao-Yang],
Li, H.L.[Hong-Liang],
Wu, Q.B.[Qing-Bo],
Qiu, H.Q.[He-Qian],
Zhang, X.L.[Xiao-Liang],
Meng, F.M.[Fan-Man],
Zhao, T.J.[Tai-Jin],
Disturbed Augmentation Invariance for Unsupervised Visual
Representation Learning,
CirSysVideo(33), No. 11, November 2023, pp. 6924-6938.
IEEE DOI
2311
Variation on Contrastive Learning
BibRef
Lin, H.[Huibin],
Zhang, C.Y.[Chun-Yang],
Wang, S.P.[Shi-Ping],
Guo, W.Z.[Wen-Zhong],
A Probabilistic Contrastive Framework for Semi-Supervised Learning,
MultMed(25), 2023, pp. 8767-8779.
IEEE DOI
2312
BibRef
Qing, Z.W.[Zhi-Wu],
Huang, Z.Y.[Zi-Yuan],
Zhang, S.W.[Shi-Wei],
Tang, M.Q.[Ming-Qian],
Gao, C.X.[Chang-Xin],
Jin, R.[Rong],
Ang, M.H.[Marcelo H.],
Sang, N.[Nong],
ParamCrop: Parametric Cubic Cropping for Video Contrastive Learning,
MultMed(25), 2023, pp. 9002-9014.
IEEE DOI
2312
BibRef
Li, Y.[Yiyue],
Qian, G.W.[Guang-Wu],
Jiang, X.S.[Xiao-Shuang],
Jiang, Z.K.[Ze-Kun],
Wen, W.[Wen],
Zhang, S.T.[Shao-Ting],
Li, K.[Kang],
Lao, Q.C.[Qi-Cheng],
Hierarchical-Instance Contrastive Learning for Minority Detection on
Imbalanced Medical Datasets,
MedImg(43), No. 1, January 2024, pp. 416-426.
IEEE DOI
2401
BibRef
Feng, X.[Xin],
Ji, H.[Haobo],
Pei, W.J.[Wen-Jie],
Li, J.X.[Jin-Xing],
Lu, G.M.[Guang-Ming],
Zhang, D.[David],
U²-Former: Nested U-Shaped Transformer for Image Restoration via
Multi-View Contrastive Learning,
CirSysVideo(34), No. 1, January 2024, pp. 168-181.
IEEE DOI
2401
BibRef
Bao, P.[Peng],
Li, J.[Jianian],
Yan, R.[Rong],
Liu, Z.Y.[Zhong-Yi],
Dynamic Graph Contrastive Learning via Maximize Temporal Consistency,
PR(148), 2024, pp. 110144.
Elsevier DOI
2402
Contrastive learning, Dynamic graph, Temporal information
BibRef
Bu, W.X.[Wei-Xin],
Cao, X.F.[Xiao-Feng],
Zheng, Y.Z.[Yi-Zhen],
Pan, S.R.[Shi-Rui],
Improving Augmentation Consistency for Graph Contrastive Learning,
PR(148), 2024, pp. 110182.
Elsevier DOI Code:
WWW Link.
2402
Graph contrastive learning, Augmentation consistency
BibRef
Zhou, Q.[Qian],
Wang, Q.Q.[Qian-Qian],
Gao, Q.X.[Quan-Xue],
Yang, M.[Ming],
Gao, X.B.[Xin-Bo],
Unsupervised Discriminative Feature Selection via Contrastive Graph
Learning,
IP(33), 2024, pp. 972-986.
IEEE DOI
2402
Feature extraction, Sparse matrices, Self-supervised learning,
Data models, Telecommunications, Spatial databases, Redundancy,
unsupervised feature selection
BibRef
Li, H.T.[Hao-Tian],
Jin, H.[Hui],
Research on Personalized AEB Strategies Based on Self-Supervised
Contrastive Learning,
ITS(25), No. 2, February 2024, pp. 1303-1316.
IEEE DOI
2402
Vehicles, Safety, Data models, Collision avoidance, Brakes,
Analytical models, Predictive models, Driving style,
AEB strategy
BibRef
Sammani, F.[Fawaz],
Joukovsky, B.[Boris],
Deligiannis, N.[Nikos],
Visualizing and Understanding Contrastive Learning,
IP(33), 2024, pp. 541-555.
IEEE DOI
2402
Data models, Task analysis, Measurement, Computational modeling,
Image classification, Data augmentation, Adaptation models,
explaining similarity networks
BibRef
Zhang, X.D.[Xiao-Dian],
Gao, K.[Kun],
Wang, J.W.[Jun-Wei],
Wang, P.Y.[Peng-Yu],
Hu, Z.[Zibo],
Yang, Z.J.[Zhi-Jia],
Zhao, X.B.[Xia-Bin],
Li, W.[Wei],
Target Detection Adapting to Spectral Variability in Multi-Temporal
Hyperspectral Images Using Implicit Contrastive Learning,
RS(16), No. 4, 2024, pp. 718.
DOI Link
2402
BibRef
Gao, Y.[Yuan],
Li, X.[Xin],
Hui, Y.[Yan],
Rethinking Graph Contrastive Learning: An Efficient Single-View
Approach via Instance Discrimination,
MultMed(26), 2024, pp. 3616-3625.
IEEE DOI
2402
Training, Measurement, Costs, Graph neural networks,
Computational modeling, Estimation, Task analysis, uniformity
BibRef
Zhang, Y.F.[Yi-Fei],
Liu, C.[Chang],
Zhou, Y.[Yu],
Wang, W.P.[Wei-Ping],
Ye, Q.X.[Qi-Xiang],
Ji, X.Y.[Xiang-Yang],
Beyond Instance Discrimination: Relation-Aware Contrastive
Self-Supervised Learning,
MultMed(26), 2024, pp. 4628-4640.
IEEE DOI
2403
Interpolation, Self-supervised learning, Task analysis, Semantics,
Visualization, Semisupervised learning, Representation learning,
self-supervised learning
BibRef
Lin, L.[Lilang],
Zhang, J.H.[Jia-Hang],
Liu, J.Y.[Jia-Ying],
Mutual Information Driven Equivariant Contrastive Learning for 3D
Action Representation Learning,
IP(33), 2024, pp. 1883-1897.
IEEE DOI
2403
Self-supervised learning, Skeleton, Task analysis,
Representation learning, Data models, contrastive learning
BibRef
Xu, H.[Huali],
Liu, L.[Li],
Zhi, S.F.[Shuai-Feng],
Fu, S.J.[Shao-Jing],
Su, Z.[Zhuo],
Cheng, M.M.[Ming-Ming],
Liu, Y.X.[Yong-Xiang],
Enhancing Information Maximization with Distance-Aware Contrastive
Learning for Source-Free Cross-Domain Few-Shot Learning,
IP(33), 2024, pp. 2058-2073.
IEEE DOI Code:
WWW Link.
2403
Task analysis, Data models, Self-supervised learning, Training,
Computational modeling, Adaptation models, Predictive models,
transductive learning
BibRef
Lv, Y.Q.[Yun-Qiu],
Zhang, J.[Jing],
Barnes, N.M.[Nick M.],
Dai, Y.C.[Yu-Chao],
Weakly-Supervised Contrastive Learning for Unsupervised Object
Discovery,
IP(33), 2024, pp. 2689-2702.
IEEE DOI Code:
WWW Link.
2404
Self-supervised learning, Semantics, Task analysis, Representation learning,
Principal component analysis, principal component analysis
BibRef
Sun, S.[Shiding],
Wang, B.[Bo],
Tian, Y.J.[Ying-Jie],
Decoupled representation for multi-view learning,
PR(151), 2024, pp. 110377.
Elsevier DOI
2404
Multi-view learning, Representation learning,
Information bottleneck, Contrastive learning
BibRef
Li, J.Y.[Jing-Yao],
Chen, P.[Pengguang],
Yu, S.[Shaozuo],
Liu, S.[Shu],
Jia, J.Y.[Jia-Ya],
BAL: Balancing Diversity and Novelty for Active Learning,
PAMI(46), No. 5, May 2024, pp. 3653-3664.
IEEE DOI
2404
Task analysis, Labeling, Uncertainty, Feature extraction,
Measurement uncertainty, Image color analysis, Benchmark testing,
contrastive learning
BibRef
Lee, S.[Soohong],
Lee, S.H.[Sang-Ho],
Lee, J.[Jaehwan],
Lee, W.[Woojin],
Son, Y.[Youngdoo],
Graph contrastive learning with consistency regularization,
PRL(181), 2024, pp. 43-49.
Elsevier DOI
2405
Contrastive learning, Class collision, Consistency regularization,
Graph representation learning, Graph neural network
BibRef
Liu, Y.[Yue],
Zan, X.Z.[Xiang-Zhen],
Li, X.B.[Xian-Bin],
Liu, W.B.[Wen-Bin],
Fang, G.[Gang],
Contrastive visual clustering for improving instance-level
contrastive learning as a plugin,
PR(154), 2024, pp. 110631.
Elsevier DOI Code:
WWW Link.
2406
Self-supervised learning, Contrastive learning, Deep clustering
BibRef
Liu, A.[Aohan],
Guo, Y.C.[Yu-Chen],
Yong, J.H.[Jun-Hai],
Xu, F.[Feng],
Multi-Grained Radiology Report Generation With Sentence-Level
Image-Language Contrastive Learning,
MedImg(43), No. 7, July 2024, pp. 2657-2669.
IEEE DOI
2407
Self-supervised learning, Decoding, Radiology, Biomedical imaging,
Task analysis, Training, Reinforcement learning, multi-grained
BibRef
Liu, Y.B.[Yi-Bing],
Tian, C.X.[Chris Xing],
Li, H.L.[Hao-Liang],
Wang, S.Q.[Shi-Qi],
Generalization Beyond Feature Alignment:
Concept Activation-Guided Contrastive Learning,
IP(33), 2024, pp. 4377-4390.
IEEE DOI
2408
Neurons, Training, Visualization, Vectors, Representation learning,
Analytical models, Dogs, Domain generalization, neuron activation,
concept contrast
BibRef
Du, C.Q.[Chao-Qun],
Wang, Y.L.[Yu-Lin],
Song, S.[Shiji],
Huang, G.[Gao],
Probabilistic Contrastive Learning for Long-Tailed Visual Recognition,
PAMI(46), No. 9, September 2024, pp. 5890-5904.
IEEE DOI
2408
Self-supervised learning, Data models, Training, Tail, Task analysis,
Probabilistic logic, Head, Contrastive learning,
semi-supervised learning
BibRef
Wang, B.[Bohua],
Tian, Z.Q.[Zhi-Qiang],
Ye, A.[Aixue],
Wen, F.[Feng],
Du, S.[Shaoyi],
Gao, Y.[Yue],
Generative Variational-Contrastive Learning for Self-Supervised Point
Cloud Representation,
PAMI(46), No. 9, September 2024, pp. 6154-6166.
IEEE DOI
2408
Feature extraction, Self-supervised learning,
Point cloud compression, Synthetic data, Task analysis,
variational inference
BibRef
Wu, C.Z.[Cheng-Zhi],
Pfrommer, J.[Julius],
Zhou, M.Y.[Ming-Yuan],
Beyerer, J.[Jürgen],
Self-Supervised Generative-Contrastive Learning of Multi-Modal
Euclidean Input for 3D Shape Latent Representations:
A Dynamic Switching Approach,
MultMed(26), 2024, pp. 8432-8441.
IEEE DOI
2408
Shape, Switches, Image reconstruction, Training, Decoding,
Task analysis, Self-supervised learning, contrastive learning,
dynamic switching
BibRef
Wu, H.[Hefeng],
Chen, W.F.[Wei-Feng],
Liu, Z.B.[Zhi-Bin],
Chen, T.S.[Tian-Shui],
Chen, Z.G.[Zhi-Guang],
Lin, L.[Liang],
Contrastive Transformer Learning With Proximity Data Generation for
Text-Based Person Search,
CirSysVideo(34), No. 8, August 2024, pp. 7005-7016.
IEEE DOI
2408
Transformers, Task analysis, Feature extraction, Data models,
Visualization, Training, Semantics, Text-based person search,
proximity data generation
BibRef
Yi, Y.Y.[Yuan-Yuan],
Zeng, G.[Guolei],
Ren, B.[Bocheng],
Yang, L.T.[Laurence T.],
Chai, B.[Bin],
Li, Y.X.[Yu-Xin],
Prototype rectification for zero-shot learning,
PR(156), 2024, pp. 110750.
Elsevier DOI
2408
Zero-shot learning, Image recognition, Meta-learning,
Contrastive learning, Manifold alignment
BibRef
Gao, C.[Chen],
Zhang, X.[Xuan],
Jin, Z.[Zhi],
Shang, W.Y.[Wei-Yi],
Ma, Y.[Yubin],
Li, L.[Linyu],
Ding, Z.[Zishuo],
Liang, Y.Q.[Yu-Qin],
Few-shot relational triple extraction with hierarchical prototype
optimization,
PR(156), 2024, pp. 110779.
Elsevier DOI
2408
Few-shot learning, Relational triple extraction,
Hierarchical prototype optimization, Contrastive learning, Prototype network
BibRef
Zhang, H.L.[Hong-Liang],
Chen, S.[Shuo],
Luo, L.[Lei],
Yang, J.[Jiang],
Few-shot learning with long-tailed labels,
PR(156), 2024, pp. 110806.
Elsevier DOI
2408
Few-shot learning, Long-tailed labels, Contrastive learning,
Semi-supervised learning, Weighted random sampling
BibRef
Wang, Y.M.[Yi-Ming],
Chang, D.X.[Dong-Xia],
Fu, Z.Q.[Zhi-Qiang],
Wen, J.[Jie],
Zhao, Y.[Yao],
Partially View-Aligned Representation Learning via Cross-View Graph
Contrastive Network,
CirSysVideo(34), No. 8, August 2024, pp. 7272-7283.
IEEE DOI
2408
Representation learning, Self-supervised learning, Task analysis,
Correlation, Measurement, Visualization,
contrastive learning
BibRef
Liu, X.[Xin],
Qian, B.[Biao],
Liu, H.P.[Hai-Peng],
Guo, D.[Dan],
Wang, Y.[Yang],
Wang, M.[Meng],
Seeking False Hard Negatives for Graph Contrastive Learning,
CirSysVideo(34), No. 8, August 2024, pp. 7454-7466.
IEEE DOI
2408
Message passing, Self-supervised learning,
Benchmark testing, Training, Task analysis, message passing
BibRef
Yu, B.[Bin],
Hou, Y.H.[Yong-Hong],
Guo, Z.H.[Zi-Hui],
Gao, Z.Y.[Zhi-Yi],
Li, Y.Y.[Yue-Yang],
FTAN: Frame-to-frame temporal alignment network with contrastive
learning for few-shot action recognition,
IVC(149), 2024, pp. 105159.
Elsevier DOI
2408
Few-shot action recognition, Distance metric,
Temporal alignment, Contrastive objectives
BibRef
Ayuba, D.L.[Daniel La'ah],
Guillemaut, J.Y.[Jean-Yves],
Marti-Cardona, B.[Belen],
Mendez, O.[Oscar],
HyperKon: A Self-Supervised Contrastive Network for Hyperspectral
Image Analysis,
RS(16), No. 18, 2024, pp. 3399.
DOI Link
2410
BibRef
Meng, L.H.[Ling-Huan],
Wang, C.[Chuang],
Training Dynamics of Nonlinear Contrastive Learning Model in the High
Dimensional Limit,
SPLetters(31), 2024, pp. 2535-2539.
IEEE DOI
2410
Training, Data models, Mathematical models, Analytical models,
Contrastive learning, Vectors, Stability criteria,
large system limit
BibRef
Cui, J.Q.[Jie-Quan],
Zhong, Z.S.[Zhi-Sheng],
Tian, Z.T.[Zhuo-Tao],
Liu, S.[Shu],
Yu, B.[Bei],
Jia, J.Y.[Jia-Ya],
Generalized Parametric Contrastive Learning,
PAMI(46), No. 12, December 2024, pp. 7463-7474.
IEEE DOI
2411
Training, Robustness, Task analysis, Semantic segmentation,
Benchmark testing, Transforms, Transformers,
semantic segmentation
BibRef
Qian, S.S.[Sheng-Sheng],
Xue, D.[Dizhan],
Hu, J.[Jun],
Zhang, H.W.[Huai-Wen],
Xu, C.S.[Chang-Sheng],
Nonparametric Clustering-Guided Cross-View Contrastive Learning for
Partially View-Aligned Representation Learning,
IP(33), 2024, pp. 6158-6172.
IEEE DOI
2411
Representation learning, Contrastive learning, Semantics, Costs, Robustness,
Gaussian mixture model, Faces, Data models, nonparametric clustering
BibRef
Yuan, R.[Ruiwen],
Tang, Y.Q.[Yong-Qiang],
Wu, Y.J.[Ya-Jing],
Niu, J.H.[Jing-Hao],
Zhang, W.[Wensheng],
Semi-Supervised Graph Structure Learning via Dual Reinforcement of
Label and Prior Structure,
Cyber(54), No. 11, November 2024, pp. 6943-6956.
IEEE DOI
2411
Contrastive learning, Task analysis, Correlation, Optimization,
Noise measurement, Topology, Mutual information,
graph structure learning (GSL)
BibRef
Huang, D.[Dong],
Deng, X.Z.[Xiao-Zhi],
Chen, D.H.[Ding-Hua],
Wen, Z.[Zihao],
Sun, W.J.[Wei-Jun],
Wang, C.D.[Chang-Dong],
Lai, J.H.[Jian-Huang],
Deep Clustering With Hybrid-Grained Contrastive and Discriminative
Learning,
CirSysVideo(34), No. 10, October 2024, pp. 9472-9483.
IEEE DOI Code:
WWW Link.
2411
Feature extraction, Representation learning, Semantics,
Clustering methods, Clustering algorithms, Prototypes, granularity
BibRef
Shen, C.C.[Cheng-Chao],
Chen, J.Z.[Jian-Zhong],
Wang, S.[Shu],
Kuang, H.[Hulin],
Liu, J.[Jin],
Wang, J.X.[Jian-Xin],
Asymmetric patch sampling for contrastive learning,
PR(158), 2025, pp. 111012.
Elsevier DOI Code:
WWW Link.
2411
Contrastive learning, Unsupervised learning,
Self-supervised learning, Representation learning, Deep learning
BibRef
Long, X.Z.[Xian-Zhong],
Peng, C.[Chen],
Li, Y.[Yun],
MNN: Mixed nearest-neighbors for self-supervised learning,
PR(158), 2025, pp. 110998.
Elsevier DOI Code:
WWW Link.
2411
Self-supervised learning, K-nearest neighbors,
Contrastive learning, Image mixture, Momentum encoder
BibRef
Zhang, J.Q.[Jia-Qiang],
Chen, S.C.[Song-Can],
Topology reorganized graph contrastive learning with mitigating
semantic drift,
PR(159), 2025, pp. 111160.
Elsevier DOI
2412
Graph neural network, Self-supervised learning,
Contrastive learning, Node representation learning
BibRef
Li, D.[Deng],
Zhang, J.[Jianguang],
Wu, K.[Kunhong],
Shi, Y.C.[Yu-Cheng],
Han, Y.[Yahong],
Pseudo-label refinement via hierarchical contrastive learning for
source-free unsupervised domain adaptation,
PRL(186), 2024, pp. 236-242.
Elsevier DOI
2412
Unsupervised domain adaptation, Self-supervised learning,
Contrastive learning, Pseudo labeling
BibRef
Guan, R.[Ren],
Wang, Y.F.[Yi-Fei],
Liu, X.Y.[Xin-Yuan],
Chen, B.[Bin],
Zhu, J.[Jihua],
Dual Contrastive Label Enhancement,
PR(160), 2025, pp. 111183.
Elsevier DOI
2501
Label distribution learning, Label enhancement, Contrastive learning
BibRef
Wang, T.B.[Tong-Bo],
Huang, H.[Hua],
Future Feature-Based Supervised Contrastive Learning for Streaming
Perception,
CirSysVideo(34), No. 12, December 2024, pp. 13611-13625.
IEEE DOI
2501
Streaming media, Object detection, Contrastive learning,
Feature extraction, Accuracy, Task analysis, Real-time systems,
appearance features
BibRef
Quan, Q.[Quan],
Yao, Q.S.[Qing-Song],
Zhu, H.Q.[He-Qin],
Zhou, S.K.[S. Kevin],
IGU-Aug: Information-Guided Unsupervised Augmentation and Pixel-Wise
Contrastive Learning for Medical Image Analysis,
MedImg(44), No. 1, January 2025, pp. 154-164.
IEEE DOI Code:
WWW Link.
2501
Contrastive learning, Task analysis, Data augmentation, Semantics,
Training, Feature extraction, Image segmentation, segmentation
BibRef
Xuan, S.Y.[Shi-Yu],
Yang, M.[Ming],
Zhang, S.L.[Shi-Liang],
Incremental Model Enhancement via Memory-based Contrastive Learning,
IJCV(133), No. 1, January 2025, pp. 65-83.
Springer DOI
2501
BibRef
Deng, H.J.[Hao-Jin],
Yang, Y.M.[Yi-Min],
Context-Enriched Contrastive Loss: Enhancing Presentation of Inherent
Sample Connections in Contrastive Learning Framework,
MultMed(27), 2025, pp. 429-441.
IEEE DOI
2501
Contrastive learning, Training, Convergence, Head, Robustness,
Distortion, Supervised learning, Computational modeling,
self-supervised learning
BibRef
Liang, Z.[Zhuomin],
Bai, L.[Liang],
Fan, J.Y.[Jin-Yu],
Yang, X.[Xian],
Liang, J.[Jiye],
Contrastive Learning With Enhancing Detailed Information for
Pre-Training Vision Transformer,
CirSysVideo(35), No. 1, January 2025, pp. 219-231.
IEEE DOI
2502
Contrastive learning, Image representation, Transformers, Training,
Feature extraction, Supervised learning, Contrastive learning,
representation learning
BibRef
Xie, Y.[Yu],
Luo, L.[Lianhang],
Cao, T.[Tianpei],
Yu, B.[Bin],
Qin, A.K.,
Contrastive Learning Network for Unsupervised Graph Matching,
CirSysVideo(35), No. 1, January 2025, pp. 643-656.
IEEE DOI
2502
Contrastive learning, Feature extraction, Training,
Noise measurement, Unsupervised learning, Generators,
contrastive learning
BibRef
Ouahab, A.[Achraf],
Ben Ahmed, O.[Olfa],
ProtoMed: Prototypical networks with auxiliary regularization for
few-shot medical image classification,
IVC(154), 2025, pp. 105337.
Elsevier DOI
2502
Medical image, Few shot learning, Rare diseases, Deep learning,
Classification, Meta-learning, Contrastive learning
BibRef
Chen, X.Y.[Xue-Yuan],
Li, S.Z.[Shang-Zhe],
Liu, R.M.[Ruo-Mei],
Shi, B.[Bowen],
Liu, J.H.[Jia-Heng],
Wu, J.[Junran],
Xu, K.[Ke],
Molecular graph contrastive learning with line graph,
PR(162), 2025, pp. 111380.
Elsevier DOI
2503
Molecular pre-training, Graph contrastive learning,
Dual-helix graph encoder, Hard negative samples, Transfer learning
BibRef
Qin, P.[Peng],
Lu, Y.C.[Yao-Chun],
Chen, W.F.[Wei-Fu],
Li, D.F.[De-Fang],
Feng, G.C.[Guo-Can],
AAGCN: An adaptive data augmentation for graph contrastive learning,
PR(163), 2025, pp. 111471.
Elsevier DOI
2503
Graph augmentation, Graph contrastive learning, Graph semi-supervised learning
BibRef
Li, H.X.[Hai-Xiang],
Fang, M.[Min],
Li, X.[Xiao],
Chen, B.[Bo],
Wang, G.Z.[Gui-Zhi],
Hierarchical multi-granular multi-label contrastive learning,
PR(164), 2025, pp. 111567.
Elsevier DOI
2504
Multi-label learning, Contrastive learning, Label enhancement
BibRef
Lin, H.[Huibin],
Zhang, C.Y.[Chun-Yang],
Chen, C.L.P.[C. L. Philip],
Contextual Distribution Alignment via Correlation Contrasting for
Domain Generalization,
CirSysVideo(35), No. 4, April 2025, pp. 3619-3632.
IEEE DOI
2504
Semantics, Correlation, Feature extraction, Contrastive learning,
Prototypes, Data augmentation
BibRef
Stival, L.[Leandro],
da Silva-Torres, R.[Ricardo],
Pedrini, H.[Helio],
Semantically-Aware Contrastive Learning for multispectral remote
sensing images,
PandRS(223), 2025, pp. 173-187.
Elsevier DOI Code:
WWW Link.
2504
Remote sensing images, Self-supervised learning,
Multi-spectral image, Semantic information, Contrastive learning
BibRef
He, Y.T.[Yu-Ting],
Wang, B.[Boyu],
Ge, R.J.[Rong-Jun],
Chen, Y.[Yang],
Yang, G.[Guanyu],
Li, S.[Shuo],
Homeomorphism Prior for False Positive and Negative Problem in
Medical Image Dense Contrastive Representation Learning,
PAMI(47), No. 5, May 2025, pp. 4122-413.9
IEEE DOI
2504
Biomedical imaging, Semantics, Reliability, Topology,
Feature extraction, Representation learning, Deformation,
correspondence problem
BibRef
Long, F.[Fei],
Xiong, H.R.[Hao-Ren],
Hu, H.[Hang],
Qian, C.[Cheng],
Sang, J.[Jun],
A diabetic retinopathy classification method based on image-text
contrastive learning,
PRL(193), 2025, pp. 142-148.
Elsevier DOI
2505
Medical image, Diabetic retinopathy, Deep learning
BibRef
Liu, X.Y.[Xiao-Yu],
Zhou, B.[Beitong],
Yue, Z.[Zuogong],
Cheng, C.[Cheng],
PLReMix: Combating Noisy Labels with Pseudo-Label Relaxed Contrastive
Representation Learning,
WACV25(6517-6527)
IEEE DOI Code:
WWW Link.
2505
Representation learning, Codes, Filtering, Computational modeling,
Semantics, Noise measurement, Reliability, Optimization, contrastive learning
BibRef
Sun, J.R.[Jia-Rui],
Akcal, M.U.[M. Ugur],
Chowdhary, G.[Girish],
Zhang, W.[Wei],
MOOSS: Mask-Enhanced Temporal Contrastive Learning for Smooth State
Evolution in Visual Reinforcement Learning,
WACV25(6719-6729)
IEEE DOI
2505
Visualization, Correlation, High dimensional data, Reinforcement learning,
Contrastive learning, Benchmark testing, Data mining
BibRef
Servant, L.[Logan],
Clément, M.[Michaël],
Wendling, L.[Laurent],
Kurtz, C.[Camille],
Contrastive Learning of Image Representations Guided by Spatial
Relations,
WACV25(2124-2133)
IEEE DOI Code:
WWW Link.
2505
Training, Representation learning, Visualization, Source coding,
Semantics, Image retrieval, Image representation,
Question answering (information retrieval)
BibRef
Zeng, D.[Dewen],
Wu, Y.W.[Ya-Wen],
Hu, X.R.[Xin-Rong],
Xu, X.W.[Xiao-Wei],
Shi, Y.[Yiyu],
Contrastive Learning with Synthetic Positives,
ECCV24(XXXVII: 430-447).
Springer DOI
2412
BibRef
Kumar, Y.[Yogesh],
Marttinen, P.[Pekka],
Improving Medical Multi-modal Contrastive Learning with Expert
Annotations,
ECCV24(XX: 468-486).
Springer DOI
2412
BibRef
Sardari, F.[Faegheh],
Mustafa, A.[Armin],
Jackson, P.J.B.[Philip J. B.],
Hilton, A.[Adrian],
Coleaf: A Contrastive-collaborative Learning Framework for Weakly
Supervised Audio-visual Video Parsing,
ECCV24(XI: 1-17).
Springer DOI
2412
BibRef
Sasaya, T.[Tenta],
Yamamoto, S.[Shintaro],
Ida, T.[Takashi],
Takimoto, T.[Takahiro],
Contrastive Learning Using Synthetic Images Generated from Real Images,
ACCV24(VII: 167-184).
Springer DOI
2412
BibRef
Yang, H.[Hunmin],
Jeong, J.[Jongoh],
Yoon, K.J.[Kuk-Jin],
Prompt-driven Contrastive Learning for Transferable Adversarial Attacks,
ECCV24(XLIII: 36-53).
Springer DOI
2412
BibRef
Long, Z.J.[Zi-Jun],
Zhuang, L.P.[Li-Ping],
Killick, G.[George],
McCreadie, R.[Richard],
Aragon-Camarasa, G.[Gerardo],
Henderson, P.[Paul],
Understanding and Mitigating Human-labelling Errors in Supervised
Contrastive Learning,
ECCV24(LIV: 435-454).
Springer DOI
2412
BibRef
Ramachandran, A.[Akshat],
Kundu, S.[Souvik],
Krishna, T.[Tushar],
CLAMP-VIT: Contrastive Data-free Learning for Adaptive Post-training
Quantization of VITs,
ECCV24(LXVII: 307-325).
Springer DOI
2412
BibRef
Wang, L.[Lei],
Koniusz, P.[Piotr],
Gedeon, T.[Tom],
Zheng, L.[Liang],
Adaptive Multi-head Contrastive Learning,
ECCV24(LXIX: 404-421).
Springer DOI
2412
BibRef
Nguyen, T.[Thong],
Bin, Y.[Yi],
Wu, X.B.[Xiao-Bao],
Dong, X.[Xinshuai],
Hu, Z.Y.[Zhi-Yuan],
Le, K.[Khoi],
Nguyen, C.D.[Cong-Duy],
Ng, S.K.[See-Kiong],
Tuan, L.A.[Luu Anh],
Meta-optimized Angular Margin Contrastive Framework for Video-language
Representation Learning,
ECCV24(LXXX: 77-98).
Springer DOI
2412
BibRef
Kokilepersaud, K.[Kiran],
Yarici, Y.[Yavuz],
Prabhushankar, M.[Mohit],
Al Regib, G.[Ghassan],
Taxes are All You Need: Integration Of Taxonomical Hierarchy
Relationships Into the Contrastive Loss,
ICIP24(270-276)
IEEE DOI
2411
Representation learning, Semantics, Taxonomy, Finance,
Contrastive learning, Birds, Contrastive Learning, Taxonomies
BibRef
Mirzaei, H.[Hossein],
Nafez, M.[Mojtaba],
Jafari, M.[Mohammad],
Soltani, M.B.[Mohammad Bagher],
Azizmalayeri, M.[Mohammad],
Habibi, J.[Jafar],
Sabokrou, M.[Mohammad],
Rohban, M.H.[Mohammad Hossein],
Universal Novelty Detection Through Adaptive Contrastive Learning,
CVPR24(22914-22923)
IEEE DOI
2410
Training, Contrastive learning, Detectors, Switches,
Machine learning, Benchmark testing, Probabilistic logic,
distribution shift
BibRef
Li, Z.W.[Zhao-Wen],
Zhu, Y.[Yousong],
Chen, Z.Y.[Zhi-Yang],
Gao, Z.X.[Zong-Xin],
Zhao, R.[Rui],
Zhao, C.Y.[Chao-Yang],
Tang, M.[Ming],
Wang, J.Q.[Jin-Qiao],
Self-Supervised Representation Learning from Arbitrary Scenarios,
CVPR24(22967-22977)
IEEE DOI
2410
Training, Representation learning, Visualization,
Contrastive learning, Interference, Robustness
BibRef
Zhuo, J.M.[Jia-Ming],
Qin, F.Y.[Fei-Yang],
Cui, C.[Can],
Fu, K.[Kun],
Niu, B.X.[Bing-Xin],
Wang, M.Z.[Meng-Zhu],
Guo, Y.F.[Yuan-Fang],
Wang, C.[Chuan],
Wang, Z.[Zhen],
Cao, X.C.[Xiao-Chun],
Yang, L.[Liang],
Improving Graph Contrastive Learning via Adaptive Positive Sampling,
CVPR24(23179-23187)
IEEE DOI
2410
Heating systems, Scalability, Contrastive learning, Robustness,
Optimization
BibRef
Gao, Z.[Zheng],
Feng, C.[Chen],
Patras, I.[Ioannis],
Self-Supervised Representation Learning with Cross-Context Learning
between Global and Hypercolumn Features,
WACV24(1762-1772)
IEEE DOI
2404
Representation learning, Computational modeling, Semantics,
Self-supervised learning, Task analysis, Context modeling,
Image recognition and understanding
BibRef
Pang, Z.S.[Zong-Shang],
Nakashima, Y.[Yuta],
Otani, M.[Mayu],
Nagahara, H.[Hajime],
Revisiting Pixel-Level Contrastive Pre-Training on Scene Images,
WACV24(1773-1782)
IEEE DOI
2404
Training, Semantic segmentation, Semantics, Crops,
Self-supervised learning, Object detection, Algorithms,
Image recognition and understanding
BibRef
Yap, B.P.[Boon Peng],
Ng, B.K.[Beng Koon],
Group-wise Contrastive Bottleneck for Weakly-Supervised Visual
Representation Learning,
WACV24(2235-2244)
IEEE DOI
2404
Representation learning, Visualization, Shape,
Image color analysis, Semantics, Self-supervised learning
BibRef
Zhang, Y.Z.[Yun-Zhe],
Lu, Y.[Yao],
Xuan, Q.[Qi],
How Does Contrastive Learning Organize Images?,
VAQuality24(497-506)
IEEE DOI
2404
Measurement, Codes, Self-supervised learning, Boosting
BibRef
Wang, J.F.[Jin-Feng],
Song, S.[Sifan],
Su, J.[Jionglong],
Zhou, S.K.[S. Kevin],
Distortion-Disentangled Contrastive Learning,
WACV24(75-85)
IEEE DOI
2404
Training, Representation learning, Adaptation models,
Memory management, Self-supervised learning, Distortion
BibRef
Seifi, S.[Soroush],
Reino, D.O.[Daniel Olmeda],
Chumerin, N.[Nikolay],
Aljundi, R.[Rahaf],
OOD Aware Supervised Contrastive Learning,
WACV24(1945-1955)
IEEE DOI
2404
Training, Representation learning, Prototypes,
Self-supervised learning, Detectors, Benchmark testing, Algorithms,
Image recognition and understanding
BibRef
Chin, Z.Y.[Zhi-Yi],
Jiang, C.M.[Chieh-Ming],
Huang, C.C.[Ching-Chun],
Chen, P.Y.[Pin-Yu],
Chiu, W.C.[Wei-Chen],
Masking Improves Contrastive Self-Supervised Learning for ConvNets,
and Saliency Tells You Where,
WACV24(2749-2758)
IEEE DOI Code:
WWW Link.
2404
Training, Codes, Self-supervised learning, Transformers,
Tokenization, Convolutional neural networks, Algorithms
BibRef
Estepa, I.G.[Imanol González],
Rodríguez-de-Vera, J.M.[Jesús M.],
Nagarajan, B.[Bhalaji],
Radeva, P.[Petia],
Good Fences Make Good Neighbours,
VIPriors23(216-226)
IEEE DOI
2401
BibRef
Singh, K.P.[Kunal Pratap],
Salvador, J.[Jordi],
Weihs, L.[Luca],
Kembhavi, A.[Aniruddha],
Scene Graph Contrastive Learning for Embodied Navigation,
ICCV23(10850-10860)
IEEE DOI
2401
BibRef
Wang, G.D.[Guo-Dong],
Wang, Y.H.[Yun-Hong],
Qin, J.[Jie],
Zhang, D.M.[Dong-Ming],
Bao, X.[Xiuguo],
Huang, D.[Di],
Unilaterally Aggregated Contrastive Learning with Hierarchical
Augmentation for Anomaly Detection,
ICCV23(6865-6874)
IEEE DOI
2401
BibRef
Quan, S.J.[Sheng-Jiang],
Hirano, M.[Masahiro],
Yamakawa, Y.[Yuji],
Semantic Information in Contrastive Learning,
ICCV23(5663-5673)
IEEE DOI Code:
WWW Link.
2401
BibRef
Hou, C.K.[Cheng-Kai],
Zhang, J.[Jieyu],
Wang, H.[Haonan],
Zhou, T.Y.[Tian-Yi],
Subclass-balancing Contrastive Learning for Long-tailed Recognition,
ICCV23(5372-5384)
IEEE DOI Code:
WWW Link.
2401
BibRef
Zang, Z.L.[Ze-Lin],
Shang, L.[Lei],
Yang, S.[Senqiao],
Wang, F.[Fei],
Sun, B.[Baigui],
Xie, X.[Xuansong],
Li, S.Z.[Stan Z.],
Boosting Novel Category Discovery Over Domains with Soft Contrastive
Learning and All in One Classifier,
ICCV23(11824-11833)
IEEE DOI
2401
BibRef
Zhao, G.Q.[Gui-Qin],
Wang, W.Q.[Wei-Qiang],
Change Detection for Remote Sensing Images based on Semantic
Prototypes and Contrastive Learning,
ICIP23(865-869)
IEEE DOI
2312
BibRef
Zhao, C.[Chuang],
Ling, H.[Hefei],
Lu, S.J.[Shi-Jie],
Shi, Y.X.[Yu-Xuan],
Li, P.[Ping],
Cao, Q.[Qiang],
Improve Unsupervised Deep Hashing Via Masked Contrastive Learning,
ICIP23(785-789)
IEEE DOI
2312
BibRef
Higa, K.[Kyota],
Yamaguchi, M.[Masahiro],
Hosoi, T.[Toshinori],
ICCL: Self-Supervised Intra- and Cross-Modal Contrastive Learning
with 2D-3D Pairs for 3D Scene Understanding,
ICIP23(1085-1089)
IEEE DOI
2312
BibRef
Huang, Q.Y.[Qun-Yue],
Fang, B.[Bin],
Ai, X.[Xi],
A Global-Local Contrastive Learning Framework for Video Captioning,
ICIP23(2410-2414)
IEEE DOI
2312
BibRef
Xia, S.Y.[Shi-Yu],
Lv, J.Q.[Jia-Qi],
Xu, N.[Ning],
Niu, G.[Gang],
Geng, X.[Xin],
Towards Effective Visual Representations for Partial-Label Learning,
CVPR23(15589-15598)
IEEE DOI
2309
BibRef
Zhou, B.T.[Bei-Tong],
Lu, J.[Jing],
Liu, K.[Kerui],
Xu, Y.L.[Yun-Lu],
Cheng, Z.Z.[Zhan-Zhan],
Niu, Y.[Yi],
HyperMatch: Noise-Tolerant Semi-Supervised Learning via Relaxed
Contrastive Constraint,
CVPR23(24017-24026)
IEEE DOI
2309
BibRef
Fan, R.[Rizhao],
Poggi, M.[Matteo],
Mattoccia, S.[Stefano],
Contrastive Learning for Depth Prediction,
E2EAD23(3226-3237)
IEEE DOI
2309
BibRef
Ge, S.W.[Song-Wei],
Mishra, S.[Shlok],
Kornblith, S.[Simon],
Li, C.L.[Chun-Liang],
Jacobs, D.[David],
Hyperbolic Contrastive Learning for Visual Representations beyond
Objects,
CVPR23(6840-6849)
IEEE DOI
2309
BibRef
Sarto, S.[Sara],
Barraco, M.[Manuele],
Cornia, M.[Marcella],
Baraldi, L.[Lorenzo],
Cucchiara, R.[Rita],
Positive-Augmented Contrastive Learning for Image and Video
Captioning Evaluation,
CVPR23(6914-6924)
IEEE DOI
2309
BibRef
Pu, N.[Nan],
Zhong, Z.[Zhun],
Sebe, N.[Nicu],
Dynamic Conceptional Contrastive Learning for Generalized Category
Discovery,
CVPR23(7579-7588)
IEEE DOI
2309
BibRef
Chen, Y.X.[Yu-Xiao],
Yuan, J.B.[Jian-Bo],
Tian, Y.[Yu],
Geng, S.J.[Shi-Jie],
Li, X.Y.[Xin-Yu],
Zhou, D.[Ding],
Metaxas, D.N.[Dimitris N.],
Yang, H.X.[Hong-Xia],
Revisiting Multimodal Representation in Contrastive Learning:
From Patch and Token Embeddings to Finite Discrete Tokens,
CVPR23(15095-15104)
IEEE DOI
2309
BibRef
Wu, J.L.[Jian-Long],
Yang, H.Z.[Hao-Zhe],
Gan, T.[Tian],
Ding, N.[Ning],
Jiang, F.[Feijun],
Nie, L.Q.[Li-Qiang],
CHMATCH: Contrastive Hierarchical Matching and Robust Adaptive
Threshold Boosted Semi-Supervised Learning,
CVPR23(15762-15772)
IEEE DOI
2309
BibRef
Kim, T.[Taekyung],
Das, D.[Debasmit],
Choi, S.[Seokeon],
Jeong, M.[Minki],
Yang, S.[Seunghan],
Yun, S.[Sungrack],
Kim, C.[Changick],
Neural Transformation Network to Generate Diverse Views for
Contrastive Learning,
L3D-IVU23(4901-4911)
IEEE DOI
2309
BibRef
Hager, P.[Paul],
Menten, M.J.[Martin J.],
Rueckert, D.[Daniel],
Best of Both Worlds: Multimodal Contrastive Learning with Tabular and
Imaging Data,
CVPR23(23924-23935)
IEEE DOI
2309
BibRef
Jang, T.[Taeuk],
Wang, X.Q.[Xiao-Qian],
Difficulty-Based Sampling for Debiased Contrastive Representation
Learning,
CVPR23(24039-24048)
IEEE DOI
2309
BibRef
Bayrooti, J.[Jasmine],
Goodman, N.[Noah],
Tamkin, A.[Alex],
Multispectral Contrastive Learning with Viewmaker Networks,
PBVS23(440-448)
IEEE DOI
2309
BibRef
Feng, C.[Chen],
Patras, I.[Ioannis],
MaskCon: Masked Contrastive Learning for Coarse-Labelled Dataset,
CVPR23(19913-19922)
IEEE DOI
2309
BibRef
Gupta, R.[Rohit],
Roy, A.[Anirban],
Christensen, C.[Claire],
Kim, S.J.[Su-Jeong],
Gerard, S.[Sarah],
Cincebeaux, M.[Madeline],
Divakaran, A.[Ajay],
Grindal, T.[Todd],
Shah, M.[Mubarak],
Class Prototypes based Contrastive Learning for Classifying
Multi-Label and Fine-Grained Educational Videos,
CVPR23(19923-19933)
IEEE DOI
2309
BibRef
Yao, Y.S.[Yu-Shi],
Ye, C.[Chang],
He, J.F.[Jun-Feng],
Elsayed, G.F.[Gamaleldin F.],
Teacher-generated spatial-attention labels boost robustness and
accuracy of contrastive models,
CVPR23(23282-23291)
IEEE DOI
2309
BibRef
Zhang, C.H.[Chun-Hui],
Chen, Y.X.[Yi-Xiong],
Liu, L.[Li],
Liu, Q.[Qiong],
Zhou, X.[Xi],
HICO: Hierarchical Contrastive Learning for Ultrasound Video Model
Pretraining,
ACCV22(VI:3-20).
Springer DOI
2307
BibRef
Liu, Y.[Yuan],
Chen, J.C.[Jia-Cheng],
Wu, H.[Hao],
Moquad: Motion-focused Quadruple Construction for Video Contrastive
Learning,
SelfLearn22(20-38).
Springer DOI
2304
BibRef
Emami, H.[Hajar],
Dong, M.[Ming],
Glide-Hurst, C.[Carri],
CL-GAN: Contrastive Learning-based Generative Adversarial Network for
Modality Transfer with Limited Paired Data,
MCV22(527-542).
Springer DOI
2304
BibRef
Park, J.[Jongjin],
Yun, S.[Sukmin],
Jeong, J.[Jongheon],
Shin, J.[Jinwoo],
Opencos: Contrastive Semi-supervised Learning for Handling Open-set
Unlabeled Data,
LLID22(134-149).
Springer DOI
2304
BibRef
Ward, I.R.[Isaac Ronald],
Moore, C.[Charles],
Pak, K.[Kai],
Chen, J.[Jingdao],
Goh, E.[Edwin],
Improving Contrastive Learning on Visually Homogeneous Mars Rover
Images,
AI4Space22(170-185).
Springer DOI
2304
BibRef
Tang, P.W.[Peng-Wei],
Tang, H.Y.[Hua-Yi],
Wang, W.[Wei],
Liu, Y.[Yong],
Safe Contrastive Clustering,
MMMod23(I: 294-305).
Springer DOI
2304
BibRef
Gong, F.[Fucai],
Xie, Y.C.[Yu-Chen],
Jiang, L.[Le],
Chen, K.M.[Ke-Ming],
Liu, Y.X.[Yun-Xin],
Ye, X.Z.[Xiao-Zhou],
Ye, O.[Ouyang],
A Proposal-Improved Few-Shot Embedding Model with Contrastive Learning,
MMMod23(II: 202-214).
Springer DOI
2304
BibRef
Rosberg, F.[Felix],
Englund, C.[Cristofer],
Comparing Facial Expressions for Face Swapping Evaluation with
Supervised Contrastive Representation Learning,
FG21(01-05)
IEEE DOI
2303
Representation learning, Data privacy, Face recognition,
Gesture recognition, Data collection
BibRef
Li, T.H.[Tian-Hong],
Fan, L.J.[Li-Jie],
Yuan, Y.[Yuan],
He, H.[Hao],
Tian, Y.[Yonglong],
Feris, R.S.[Rogerio S.],
Indyk, P.[Piotr],
Katabi, D.[Dina],
Addressing Feature Suppression in Unsupervised Visual Representations,
WACV23(1411-1420)
IEEE DOI
2302
In Contrastive Learning.
Learning systems, Visualization, Force, Machine learning,
Linear programming, Task analysis,
algorithms (including transfer)
BibRef
Miyai, A.[Atsuyuki],
Yu, Q.[Qing],
Ikami, D.[Daiki],
Irie, G.[Go],
Aizawa, K.[Kiyoharu],
Rethinking Rotation in Self-Supervised Contrastive Learning:
Adaptive Positive or Negative Data Augmentation,
WACV23(2808-2817)
IEEE DOI
2302
Codes, Semantics, Task analysis,
Algorithms: Machine learning architectures, formulations,
visual reasoning
BibRef
Denize, J.[Julien],
Rabarisoa, J.[Jaonary],
Orcesi, A.[Astrid],
Hérault, R.[Romain],
Canu, S.[Stéphane],
Similarity Contrastive Estimation for Self-Supervised Soft
Contrastive Learning,
WACV23(2705-2715)
IEEE DOI
2302
Training, Representation learning, Protocols, Source coding,
Semantics, Estimation, Self-supervised learning,
visual reasoning
BibRef
Ben Saad, A.[Ahmed],
Prokopetc, K.[Kristina],
Kherroubi, J.[Josselin],
Davy, A.[Axel],
Courtois, A.[Adrien],
Facciolo, G.[Gabriele],
Improving Pixel-Level Contrastive Learning by Leveraging Exogenous
Depth Information,
WACV23(2379-2388)
IEEE DOI
2302
Training, Representation learning, Image segmentation, Shape,
Semantics, Estimation, Crops,
Remote Sensing
BibRef
Lin, Z.[Zudi],
Bas, E.[Erhan],
Singh, K.Y.[Kunwar Yashraj],
Swaminathan, G.[Gurumurthy],
Bhotika, R.[Rahul],
Relaxing Contrastiveness in Multimodal Representation Learning,
WACV23(2226-2235)
IEEE DOI
2302
Representation learning, Radiography, Costs, Semantics, MIMICs,
Radiology, Applications: Biomedical/healthcare/medicine,
Vision + language and/or other modalities
BibRef
Mo, S.T.[Shen-Tong],
Sun, Z.[Zhun],
Li, C.[Chao],
Representation Disentanglement in Generative Models with Contrastive
Learning,
WACV23(1531-1540)
IEEE DOI
2302
Scalability, Training data, Benchmark testing,
Generative adversarial networks, Generators, Task analysis,
visual reasoning
BibRef
Nag, S.[Sayak],
Goldstein, O.[Orpaz],
Roy-Chowdhury, A.K.[Amit K.],
Semantics Guided Contrastive Learning of Transformers for Zero-shot
Temporal Activity Detection,
WACV23(6232-6242)
IEEE DOI
2302
Training, Location awareness, Visualization, Adaptation models,
Computational modeling, Semantics, Manuals
BibRef
Noguchi, C.[Chihiro],
Tanizawa, T.[Toshihiro],
Ego-Vehicle Action Recognition based on Semi-Supervised Contrastive
Learning,
WACV23(5977-5987)
IEEE DOI
2302
Training, Supervised learning, Training data, Focusing, Cameras, Safety,
Robotics
BibRef
Shirekar, O.K.[Ojas Kishorkumar],
Singh, A.[Anuj],
Jamali-Rad, H.[Hadi],
Self-Attention Message Passing for Contrastive Few-Shot Learning,
WACV23(5414-5425)
IEEE DOI
2302
Deep learning, Codes, Message passing, Benchmark testing,
Graph neural networks, Data models,
and algorithms (including transfer)
BibRef
Feng, C.[Chen],
Patras, I.[Ioannis],
Adaptive Soft Contrastive Learning,
ICPR22(2721-2727)
IEEE DOI
2212
Representation learning, Visualization, Memory management,
Self-supervised learning, Transforms, Benchmark testing, Entropy
BibRef
Lee, H.[Hyunsub],
Choi, H.[Heeyoul],
Partitioning Image Representation in Contrastive Learning,
ICPR22(2864-2870)
IEEE DOI
2212
Image representation, Task analysis
BibRef
Lee, J.[Joonseok],
Joe, S.[Seongho],
Park, K.[Kyoungwon],
Kim, B.[Bogun],
Kang, H.[Hoyoung],
Park, J.[Jaeseon],
Gwon, Y.[Youngjune],
Shuffle and Divide: Contrastive Learning for Long Text,
ICPR22(2935-2941)
IEEE DOI
2212
Couplings, Text categorization, Clustering algorithms,
Self-supervised learning, Transformers, Classification algorithms
BibRef
Joe, S.[Seongho],
Kim, B.[Byoungjip],
Kang, H.[Hoyoung],
Park, K.[Kyoungwon],
Kim, B.[Bogun],
Park, J.[Jaeseon],
Lee, J.[Joonseok],
Gwon, Y.[Youngjune],
ContraCluster: Learning to Classify without Labels by Contrastive
Self-Supervision and Prototype-Based Semi-Supervision,
ICPR22(4685-4692)
IEEE DOI
2212
Representation learning, Pipelines, Prototypes,
Self-supervised learning, Benchmark testing, Noise measurement
BibRef
Jain, A.[Anurag],
Verma, Y.[Yashaswi],
Cross-modal Retrieval Using Contrastive Learning of Visual-Semantic
Embeddings,
ICPR22(4693-4699)
IEEE DOI
2212
Training, Adaptation models, Codes, Reproducibility of results,
Task analysis, Pattern matching, Image classification
BibRef
Wei, J.T.[Jiu-Tong],
Luo, G.[Guan],
Li, B.[Bing],
Hu, W.M.[Wei-Ming],
Inter-Intra Cross-Modality Self-Supervised Video Representation
Learning by Contrastive Clustering,
ICPR22(4815-4821)
IEEE DOI
2212
Representation learning, Visualization, Correlation, Semantics,
Self-supervised learning, Encoding
BibRef
Song, D.M.[Dan-Ming],
Gao, Y.P.[Yi-Peng],
Yan, J.K.[Jun-Kai],
Sun, W.[Wei],
Zheng, W.S.[Wei-Shi],
Space-correlated Contrastive Representation Learning with Multiple
Instances,
ICPR22(4715-4721)
IEEE DOI
2212
Learning systems, Representation learning, Image segmentation,
Semantics, Object detection, Data mining, Task analysis
BibRef
Yang, Z.Y.[Zheng-Yuan],
Liu, J.G.[Jin-Gen],
Huang, J.[Jing],
He, X.D.[Xiao-Dong],
Mei, T.[Tao],
Xu, C.L.[Chen-Liang],
Luo, J.B.[Jie-Bo],
Cross-modal Contrastive Distillation for Instructional Activity
Anticipation,
ICPR22(5002-5009)
IEEE DOI
2212
Charge coupled devices, Visualization, Semantics,
Natural languages, Benchmark testing, Data mining, Task analysis
BibRef
Wang, H.Q.[Hao-Qing],
Deng, Z.H.[Zhi-Hong],
Contrastive Prototypical Network with Wasserstein Confidence Penalty,
ECCV22(XIX:665-682).
Springer DOI
2211
BibRef
Müller, P.[Philip],
Kaissis, G.[Georgios],
Zou, C.[Congyu],
Rueckert, D.[Daniel],
Joint Learning of Localized Representations from Medical Images and
Reports,
ECCV22(XXVI:685-701).
Springer DOI
2211
BibRef
Li, Z.Q.[Zi-Qiang],
Wang, C.Y.[Chao-Yue],
Zheng, H.L.[He-Liang],
Zhang, J.[Jing],
Li, B.[Bin],
FakeCLR: Exploring Contrastive Learning for Solving Latent
Discontinuity in Data-Efficient GANs,
ECCV22(XV:598-615).
Springer DOI
2211
WWW Link.
BibRef
Li, Y.H.[Yu-Heng],
Li, Y.J.[Yi-Jun],
Lu, J.W.[Jing-Wan],
Shechtman, E.[Eli],
Lee, Y.J.[Yong Jae],
Singh, K.K.[Krishna Kumar],
Contrastive Learning for Diverse Disentangled Foreground Generation,
ECCV22(XVI:334-351).
Springer DOI
2211
BibRef
Wang, X.[Xi],
Fu, X.Y.[Xue-Yang],
Zhu, Y.R.[Yu-Rui],
Zha, Z.J.[Zheng-Jun],
JPEG Artifacts Removal via Contrastive Representation Learning,
ECCV22(XVII:615-631).
Springer DOI
2211
BibRef
Reiß, S.[Simon],
Seibold, C.[Constantin],
Freytag, A.[Alexander],
Rodner, E.[Erik],
Stiefelhagen, R.[Rainer],
Graph-Constrained Contrastive Regularization for Semi-weakly Volumetric
Segmentation,
ECCV22(XXI:401-419).
Springer DOI
2211
BibRef
Zhang, L.F.[Lin-Feng],
Chen, X.[Xin],
Zhang, J.[Junbo],
Dong, R.[Runpei],
Ma, K.[Kaisheng],
Contrastive Deep Supervision,
ECCV22(XXVI:1-19).
Springer DOI
2211
BibRef
Ci, Y.Z.[Yuan-Zheng],
Lin, C.[Chen],
Bai, L.[Lei],
Ouyang, W.L.[Wan-Li],
Fast-MoCo: Boost Momentum-Based Contrastive Learning with Combinatorial
Patches,
ECCV22(XXVI:290-306).
Springer DOI
2211
BibRef
Kahana, J.[Jonathan],
Hoshen, Y.[Yedid],
A Contrastive Objective for Learning Disentangled Representations,
ECCV22(XXVI:579-595).
Springer DOI
2211
BibRef
Tang, S.X.[Shi-Xiang],
Zhu, F.[Feng],
Bai, L.[Lei],
Zhao, R.[Rui],
Wang, C.Y.[Chen-Yu],
Ouyang, W.L.[Wan-Li],
Unifying Visual Contrastive Learning for Object Recognition from a
Graph Perspective,
ECCV22(XXVI:649-667).
Springer DOI
2211
BibRef
Yeh, C.H.[Chun-Hsiao],
Hong, C.Y.[Cheng-Yao],
Hsu, Y.C.[Yen-Chi],
Liu, T.L.[Tyng-Luh],
Chen, Y.[Yubei],
Le Cun, Y.L.[Yann L.],
Decoupled Contrastive Learning,
ECCV22(XXVI:668-684).
Springer DOI
2211
BibRef
Tang, S.X.[Shi-Xiang],
Zhu, F.[Feng],
Bai, L.[Lei],
Zhao, R.[Rui],
Ouyang, W.L.[Wan-Li],
Relative Contrastive Loss for Unsupervised Representation Learning,
ECCV22(XXVII:1-18).
Springer DOI
2211
BibRef
Moskalev, A.[Artem],
Sosnovik, I.[Ivan],
Fischer, V.[Volker],
Smeulders, A.[Arnold],
Contrasting Quadratic Assignments for Set-Based Representation Learning,
ECCV22(XXVII:88-104).
Springer DOI
2211
BibRef
Zhang, C.N.[Chao-Ning],
Zhang, K.[Kang],
Zhang, C.S.[Chen-Shuang],
Niu, A.[Axi],
Feng, J.[Jiu],
Yoo, C.D.[Chang D.],
Kweon, I.S.[In So],
Decoupled Adversarial Contrastive Learning for Self-supervised
Adversarial Robustness,
ECCV22(XXX:725-742).
Springer DOI
2211
BibRef
Xu, Y.F.[Yu-Fei],
Zhang, Q.M.[Qi-Ming],
Zhang, J.[Jing],
Tao, D.C.[Da-Cheng],
RegionCL: Exploring Contrastive Region Pairs for Self-supervised
Representation Learning,
ECCV22(XXXIII:477-494).
Springer DOI
2211
BibRef
Xiao, F.[Fanyi],
Tighe, J.[Joseph],
Modolo, D.[Davide],
MaCLR: Motion-Aware Contrastive Learning of Representations for Videos,
ECCV22(XXXV:353-370).
Springer DOI
2211
BibRef
Ni, J.C.[Jing-Cheng],
Zhou, N.[Nan],
Qin, J.[Jie],
Wu, Q.[Qian],
Liu, J.Q.[Jun-Qi],
Li, B.X.[Bo-Xun],
Huang, D.[Di],
Motion Sensitive Contrastive Learning for Self-Supervised Video
Representation,
ECCV22(XXXV:457-474).
Springer DOI
2211
BibRef
Wang, H.R.[Hao-Ran],
He, D.L.[Dong-Liang],
Wu, W.H.[Wen-Hao],
Xia, B.Y.[Bo-Yang],
Yang, M.[Min],
Li, F.[Fu],
Yu, Y.L.[Yun-Long],
Ji, Z.[Zhong],
Ding, E.[Errui],
Wang, J.D.[Jing-Dong],
CODER: Coupled Diversity-Sensitive Momentum Contrastive Learning for
Image-Text Retrieval,
ECCV22(XXXVI:700-716).
Springer DOI
2211
BibRef
Jiang, B.[Bo],
Krim, H.[Hamid],
Wu, T.F.[Tian-Fu],
Cansever, D.[Derya],
Refining Self-Supervised Learning in Imaging: Beyond Linear Metric,
ICIP22(76-80)
IEEE DOI
2211
Training, Manifolds, Correlation, Fuses, Refining, Imaging,
Self-Supervised learning, Contrastive Learning, Jaccard Index, Non-linearity
BibRef
Shang, Y.Z.[Yu-Zhang],
Xu, D.[Dan],
Zong, Z.L.[Zi-Liang],
Nie, L.Q.[Li-Qiang],
Yan, Y.[Yan],
Network Binarization via Contrastive Learning,
ECCV22(XI:586-602).
Springer DOI
2211
BibRef
Li, M.Z.[Ming-Zhe],
Zhang, H.B.[Hong-Bo],
Lei, Q.[Qing],
Fan, Z.W.[Zong-Wen],
Liu, J.H.[Jing-Hua],
Du, J.X.[Ji-Xiang],
Pairwise Contrastive Learning Network for Action Quality Assessment,
ECCV22(IV:457-473).
Springer DOI
2211
BibRef
Yu, Q.Y.[Qi-Ying],
Lou, J.M.[Jie-Ming],
Zhan, X.Y.[Xian-Yuan],
Li, Q.Z.[Qi-Zhang],
Zuo, W.M.[Wang-Meng],
Liu, Y.[Yang],
Liu, J.J.[Jing-Jing],
Adversarial Contrastive Learning via Asymmetric InfoNCE,
ECCV22(V:53-69).
Springer DOI
2211
BibRef
Peng, X.Y.[Xiang-Yu],
Wang, K.[Kai],
Zhu, Z.[Zheng],
Wang, M.[Mang],
You, Y.[Yang],
Crafting Better Contrastive Views for Siamese Representation Learning,
CVPR22(16010-16019)
IEEE DOI
2210
Representation learning, Training, Location awareness,
Image segmentation, Semantics, Crops, Representation learning,
Self- semi- meta- unsupervised learning
BibRef
Ding, S.R.[Shuang-Rui],
Li, M.[Maomao],
Yang, T.Y.[Tian-Yu],
Qian, R.[Rui],
Xu, H.H.[Hao-Hang],
Chen, Q.Y.[Qing-Yi],
Wang, J.[Jue],
Xiong, H.K.[Hong-Kai],
Motion-aware Contrastive Video Representation Learning via
Foreground-background Merging,
CVPR22(9706-9716)
IEEE DOI
2210
Representation learning, Image color analysis, Merging, Semantics,
Resists, Detectors, Self- semi- meta- Representation learning
BibRef
Guo, Y.F.[Yuan-Fan],
Xu, M.H.[Ming-Hao],
Li, J.[Jiawen],
Ni, B.B.[Bing-Bing],
Zhu, X.Y.[Xuan-Yu],
Sun, Z.B.[Zhen-Bang],
Xu, Y.[Yi],
HCSC: Hierarchical Contrastive Selective Coding,
CVPR22(9696-9705)
IEEE DOI
2210
WWW Link. Representation learning, Codes, Computational modeling, Semantics,
Prototypes, Image representation, Self- semi- meta- Representation learning
BibRef
Tan, C.[Cheng],
Gao, Z.Y.[Zhang-Yang],
Wu, L.R.[Li-Rong],
Li, S.Y.[Si-Yuan],
Li, S.Z.[Stan Z.],
Hyperspherical Consistency Regularization,
CVPR22(7234-7245)
IEEE DOI
2210
Deep learning, Training, Geometry, Supervised learning,
Self-supervised learning, Semisupervised learning,
Vision applications and systems
BibRef
Ko, D.[Dohwan],
Choi, J.[Joonmyung],
Ko, J.[Juyeon],
Noh, S.[Shinyeong],
On, K.W.[Kyoung-Woon],
Kim, E.S.[Eun-Sol],
Kim, H.W.J.[Hyun-Woo J.],
Video-Text Representation Learning via Differentiable Weak Temporal
Alignment,
CVPR22(5006-5015)
IEEE DOI
2210
Code, Contrastive Learning.
WWW Link. Representation learning, Codes, Computational modeling,
Self-supervised learning, Data models,
Self- semi- meta- Video analysis and understanding
BibRef
Dorkenwald, M.[Michael],
Xiao, F.[Fanyi],
Brattoli, B.[Biagio],
Tighe, J.[Joseph],
Modolo, D.[Davide],
SCVRL: Shuffled Contrastive Video Representation Learning,
L3D-IVU22(4131-4140)
IEEE DOI
2210
Representation learning, Visualization, Semantics,
Self-supervised learning, Benchmark testing, Transformers
BibRef
Taleb, A.[Aiham],
Kirchler, M.[Matthias],
Monti, R.[Remo],
Lippert, C.[Christoph],
ContIG: Self-supervised Multimodal Contrastive Learning for Medical
Imaging with Genetics,
CVPR22(20876-20889)
IEEE DOI
2210
Deep learning, Adaptation models, Costs, Design methodology,
Computational modeling, Genomics, Medical,
Vision applications and systems
BibRef
Dong, X.[Xiao],
Zhan, X.[Xunlin],
Wu, Y.X.[Yang-Xin],
Wei, Y.C.[Yun-Chao],
Kampffmeyer, M.C.[Michael C.],
Wei, X.Y.[Xiao-Yong],
Lu, M.[Minlong],
Wang, Y.[Yaowei],
Liang, X.D.[Xiao-Dan],
M5Product: Self-harmonized Contrastive Learning for E-commercial
Multi-modal Pretraining,
CVPR22(21220-21230)
IEEE DOI
2210
Representation learning, Adaptation models, Codes,
Computational modeling, Semantics, Transformers,
BibRef
Zhao, B.[Bing],
Li, J.[Jun],
Zhu, H.[Hong],
CoDo: Contrastive Learning with Downstream Background Invariance for
Detection,
L3D-IVU22(4195-4200)
IEEE DOI
2210
Representation learning, Visualization, Transfer learning,
Supervised learning, Pipelines, Object detection, Self-supervised learning
BibRef
Zhang, C.N.[Chao-Ning],
Zhang, K.[Kang],
Pham, T.X.[Trung X.],
Niu, A.[Axi],
Qiao, Z.[Zhinan],
Yoo, C.D.[Chang D.],
Kweon, I.S.[In So],
Dual Temperature Helps Contrastive Learning Without Many Negative
Samples: Towards Understanding and Simplifying MoCo,
CVPR22(14421-14430)
IEEE DOI
2210
Dictionaries, Temperature, Codes, Temperature control,
Queueing analysis, Self- semi- meta- unsupervised learning
BibRef
Son, J.[Jeany],
Contrastive Learning for Space-time Correspondence via Self-cycle
Consistency,
CVPR22(14659-14668)
IEEE DOI
2210
Training, Uncertainty, Government, Self-supervised learning,
Filtering algorithms, Probabilistic logic, Bayes methods,
grouping and shape analysis
BibRef
Cole, E.[Elijah],
Yang, X.[Xuan],
Wilber, K.[Kimberly],
Aodha, O.M.[Oisin Mac],
Belongie, S.[Serge],
When Does Contrastive Visual Representation Learning Work?,
CVPR22(01-10)
IEEE DOI
2210
Representation learning, Training, Visualization, Protocols,
Supervised learning, Self-supervised learning,
Transfer/low-shot/long-tail learning
BibRef
Wang, Z.T.[Zhen-Ting],
Zhai, J.[Juan],
Ma, S.Q.[Shi-Qing],
BppAttack: Stealthy and Efficient Trojan Attacks against Deep Neural
Networks via Image Quantization and Contrastive Adversarial Learning,
CVPR22(15054-15063)
IEEE DOI
2210
Training, Deep learning, Quantization (signal), Codes,
Neural networks, Visual systems, Adversarial attack and defense
BibRef
Wang, H.Q.[Hao-Qing],
Guo, X.[Xun],
Deng, Z.[ZhiHong],
Lu, Y.[Yan],
Rethinking Minimal Sufficient Representation in Contrastive Learning,
CVPR22(16020-16029)
IEEE DOI
2210
Training, Representation learning, Degradation,
Self-supervised learning, Transformers,
Self- semi- meta- Representation learning
BibRef
Yi, L.[Li],
Liu, S.[Sheng],
She, Q.[Qi],
McLeod, A.I.[A. Ian],
Wang, B.[Boyu],
On Learning Contrastive Representations for Learning with Noisy
Labels,
CVPR22(16661-16670)
IEEE DOI
2210
Representation learning, Deep learning, Ethics, Neural networks,
Entropy, Noise robustness, Representation learning,
privacy and ethics in vision
BibRef
Chen, C.[Cheng],
Tan, Z.S.[Zhen-Shan],
Cheng, Q.R.[Qing-Rong],
Jiang, X.[Xin],
Liu, Q.[Qun],
Zhu, Y.D.[Yu-Dong],
Gu, X.D.[Xiao-Dong],
UTC: A Unified Transformer with Inter-Task Contrastive Learning for
Visual Dialog,
CVPR22(18082-18091)
IEEE DOI
2210
Training, Representation learning, Visualization, Correlation,
Transformers, Machine learning
BibRef
Yang, J.W.[Jian-Wei],
Li, C.Y.[Chun-Yuan],
Zhang, P.C.[Peng-Chuan],
Xiao, B.[Bin],
Liu, C.[Ce],
Yuan, L.[Lu],
Gao, J.F.[Jian-Feng],
Unified Contrastive Learning in Image-Text-Label Space,
CVPR22(19141-19151)
IEEE DOI
2210
Representation learning, Visualization, Image recognition,
Soft sensors, Supervised learning, Transfer learning,
Representation learning
BibRef
Chuang, C.Y.[Ching-Yao],
Hjelm, R.D.[R. Devon],
Wang, X.[Xin],
Vineet, V.[Vibhav],
Joshi, N.[Neel],
Torralba, A.[Antonio],
Jegelka, S.[Stefanie],
Song, Y.[Yale],
Robust Contrastive Learning against Noisy Views,
CVPR22(16649-16660)
IEEE DOI
2210
Representation learning, Loss measurement, Robustness,
Noise measurement, Mutual information,
Machine learning
BibRef
Zhang, J.[Junbo],
Ma, K.S.[Kai-Sheng],
Rethinking the Augmentation Module in Contrastive Learning: Learning
Hierarchical Augmentation Invariance with Expanded Views,
CVPR22(16629-16638)
IEEE DOI
2210
Training, Representation learning, Transforms, Benchmark testing,
Data models, Representation learning, Self- semi- meta- unsupervised learning
BibRef
Zheng, M.H.[Ming-Hang],
Huang, Y.J.[Yan-Jie],
Chen, Q.C.[Qing-Chao],
Peng, Y.X.[Yu-Xin],
Liu, Y.[Yang],
Weakly Supervised Temporal Sentence Grounding with Gaussian-based
Contrastive Proposal Learning,
CVPR22(15534-15543)
IEEE DOI
2210
Training, Location awareness, Codes, Grounding, Natural languages,
Recognition: detection,
Video analysis and understanding
BibRef
Park, J.[Jungin],
Lee, J.Y.[Ji-Young],
Kim, I.J.[Ig-Jae],
Sohn, K.H.[Kwang-Hoon],
Probabilistic Representations for Video Contrastive Learning,
CVPR22(14691-14701)
IEEE DOI
2210
Representation learning, Uncertainty, Stochastic processes,
Self-supervised learning, Gaussian distribution,
Video analysis and understanding
BibRef
Li, S.K.[Shi-Kun],
Xia, X.B.[Xiao-Bo],
Ge, S.M.[Shi-Ming],
Liu, T.L.[Tong-Liang],
Selective-Supervised Contrastive Learning with Noisy Labels,
CVPR22(316-325)
IEEE DOI
2210
Representation learning, Training data, Object detection,
Robustness, Noise measurement, Task analysis, Machine learning,
Self- semi- meta- unsupervised learning
BibRef
Bian, Z.X.[Zhang-Xing],
Jabri, A.[Allan],
Efros, A.A.[Alexei A.],
Owens, A.[Andrew],
Learning Pixel Trajectories with Multiscale Contrastive Random Walks,
CVPR22(6498-6509)
IEEE DOI
2210
Computational modeling, Self-supervised learning,
Object segmentation, Search problems, Trajectory, Motion and tracking
BibRef
Zhu, J.G.[Jiang-Gang],
Wang, Z.[Zheng],
Chen, J.J.[Jing-Jing],
Chen, Y.P.P.[Yi-Ping Phoebe],
Jiang, Y.G.[Yu-Gang],
Balanced Contrastive Learning for Long-Tailed Visual Recognition,
CVPR22(6898-6907)
IEEE DOI
2210
Representation learning, Learning systems, Geometry, Visualization,
Tail, Benchmark testing, Transfer/low-shot/long-tail learning
BibRef
Li, T.H.[Tian-Hong],
Cao, P.[Peng],
Yuan, Y.[Yuan],
Fan, L.J.[Li-Jie],
Yang, Y.Z.[Yu-Zhe],
Feris, R.S.[Rogerio S.],
Indyk, P.[Piotr],
Katabi, D.[Dina],
Targeted Supervised Contrastive Learning for Long-Tailed Recognition,
CVPR22(6908-6918)
IEEE DOI
2210
Training, Target recognition, Tail, Performance gain,
Task analysis, Transfer/low-shot/long-tail learning
BibRef
Yao, X.F.[Xu-Feng],
Bai, Y.[Yang],
Zhang, X.Y.[Xin-Yun],
Zhang, Y.C.[Yue-Chen],
Sun, Q.[Qi],
Chen, R.[Ran],
Li, R.[Ruiyu],
Yu, B.[Bei],
PCL: Proxy-based Contrastive Learning for Domain Generalization,
CVPR22(7087-7097)
IEEE DOI
2210
Training, Representation learning, Learning systems,
Computational modeling, Semantics, Benchmark testing,
Representation learning
BibRef
Yu, E.[En],
Li, Z.[Zhuoling],
Han, S.[Shoudong],
Towards Discriminative Representation: Multi-view Trajectory
Contrastive Learning for Online Multi-object Tracking,
CVPR22(8824-8833)
IEEE DOI
2210
Representation learning, Measurement, Bridges, Target tracking,
Costs, Feature extraction, Motion and tracking,
Representation learning
BibRef
Karim, N.[Nazmul],
Rizve, M.N.[Mamshad Nayeem],
Rahnavard, N.[Nazanin],
Mian, A.[Ajmal],
Shah, M.[Mubarak],
UNICON: Combating Label Noise Through Uniform Selection and
Contrastive Learning,
CVPR22(9666-9676)
IEEE DOI
2210
Training, Representation learning, Deep learning, Neural networks,
Semisupervised learning, Probabilistic logic,
Self- semi- meta- Representation learning
BibRef
Ye, Z.S.[Ze-Sheng],
Yao, L.[Lina],
Contrastive Conditional Neural Processes,
CVPR22(9677-9686)
IEEE DOI
2210
Representation learning, Pipelines, Stochastic processes,
Estimation, Probabilistic logic, Hybrid power systems,
Transfer/low-shot/long-tail learning
BibRef
Afham, M.[Mohamed],
Dissanayake, I.[Isuru],
Dissanayake, D.[Dinithi],
Dharmasiri, A.[Amaya],
Thilakarathna, K.[Kanchana],
Rodrigo, R.[Ranga],
CrossPoint: Self-Supervised Cross-Modal Contrastive Learning for 3D
Point Cloud Understanding,
CVPR22(9892-9902)
IEEE DOI
2210
Point cloud compression, Representation learning, Training,
Image segmentation, Visualization, Self-supervised learning,
Transfer/low-shot/long-tail learning
BibRef
Pillai, V.[Vipin],
Koohpayegani, S.A.[Soroush Abbasi],
Ouligian, A.[Ashley],
Fong, D.[Dennis],
Pirsiavash, H.[Hamed],
Consistent Explanations by Contrastive Learning,
CVPR22(10203-10212)
IEEE DOI
2210
Training, Heating systems, Deep learning, Annotations,
Neural networks, Self-supervised learning,
Self- semi- meta- unsupervised learning
BibRef
Park, S.[Sungho],
Lee, J.[Jewook],
Lee, P.[Pilhyeon],
Hwang, S.[Sunhee],
Kim, D.[Dohyung],
Byun, H.R.[Hye-Ran],
Fair Contrastive Learning for Facial Attribute Classification,
CVPR22(10379-10388)
IEEE DOI
2210
Representation learning, Degradation, Visualization, Ethics,
Philosophical considerations, Face recognition, Transparency,
privacy and ethics in vision
BibRef
Li, J.C.[Jia-Cheng],
Chen, C.[Chang],
Xiong, Z.W.[Zhi-Wei],
Contextual Outpainting with Object-Level Contrastive Learning,
CVPR22(11441-11450)
IEEE DOI
2210
Bridges, Training, Visualization, Correlation, Shape, Semantics, Layout,
Image and video synthesis and generation, Low-level vision, Visual reasoning
BibRef
Wang, X.[Xuehui],
Zhao, K.[Kai],
Zhang, R.X.[Rui-Xin],
Ding, S.H.[Shou-Hong],
Wang, Y.[Yan],
Shen, W.[Wei],
ContrastMask: Contrastive Learning to Segment Every Thing,
CVPR22(11594-11603)
IEEE DOI
2210
Annotations, Computational modeling,
Task analysis, Optimization, Segmentation, grouping and shape analysis
BibRef
Wu, H.[Huisi],
Wang, Z.Z.[Zhao-Ze],
Song, Y.Y.[You-Yi],
Yang, L.[Lin],
Qin, J.[Jing],
Cross-patch Dense Contrastive Learning for Semi-supervised
Segmentation of Cellular Nuclei in Histopathologic Images,
CVPR22(11656-11665)
IEEE DOI
2210
Knowledge engineering, Image segmentation, Shape, Training data,
Feature extraction, Minimization, Entropy, Segmentation,
Self- semi- meta- unsupervised learning
BibRef
Meng, J.[Jian],
Yang, L.[Li],
Shin, J.[Jinwoo],
Fan, D.L.[De-Liang],
Seo, J.S.[Jae-Sun],
Contrastive Dual Gating: Learning Sparse Features With Contrastive
Learning,
CVPR22(12247-12255)
IEEE DOI
2210
Heuristic algorithms, Computational modeling,
Supervised learning, Termination of employment,
Self- semi- meta- unsupervised learning
BibRef
Zou, Y.H.[Yun-Hao],
Fu, Y.[Ying],
Estimating Fine-Grained Noise Model via Contrastive Learning,
CVPR22(12672-12681)
IEEE DOI
2210
Computational modeling, Pipelines, Estimation, Training data,
Predictive models, Data models, Sensors,
Low-level vision
BibRef
Chen, M.H.[Ming-Hao],
Wei, F.Y.[Fang-Yun],
Li, C.[Chong],
Cai, D.[Deng],
Frame-wise Action Representations for Long Videos via Sequence
Contrastive Learning,
CVPR22(13791-13800)
IEEE DOI
2210
Representation learning, Training, Codes, Self-supervised learning,
Gaussian distribution,
Self- semi- meta- unsupervised learning
BibRef
Yuan, L.Z.[Liang-Zhe],
Qian, R.[Rui],
Cui, Y.[Yin],
Gong, B.Q.[Bo-Qing],
Schroff, F.[Florian],
Yang, M.H.[Ming-Hsuan],
Adam, H.[Hartwig],
Liu, T.[Ting],
Contextualized Spatio-Temporal Contrastive Learning with
Self-Supervision,
CVPR22(13957-13966)
IEEE DOI
2210
Representation learning, Location awareness,
Self-supervised learning, Transforms,
Self- semi- meta- unsupervised learning
BibRef
Wang, J.[Jue],
Bertasius, G.[Gedas],
Tran, D.[Du],
Torresani, L.[Lorenzo],
Long-Short Temporal Contrastive Learning of Video Transformers,
CVPR22(13990-14000)
IEEE DOI
2210
Representation learning, Image recognition,
Benchmark testing, Transformers,
Self- semi- meta- unsupervised learning
BibRef
Yan, J.[Jiexi],
Luo, L.[Lei],
Xu, C.H.[Cheng-Hao],
Deng, C.[Cheng],
Huang, H.[Heng],
Noise Is Also Useful:
Negative Correlation-Steered Latent Contrastive Learning,
CVPR22(31-40)
IEEE DOI
2210
Training, Deep learning, Correlation, Neural networks,
Extraterrestrial measurements, Information filters, Data models,
Self- semi- meta- unsupervised learning
BibRef
Yang, J.W.[Jian-Wei],
Bisk, Y.[Yonatan],
Gao, J.F.[Jian-Feng],
TACo: Token-aware Cascade Contrastive Learning for Video-Text
Alignment,
ICCV21(11542-11552)
IEEE DOI
2203
Location awareness, Representation learning, Visualization,
Protocols, Pipelines, Benchmark testing, Syntactics,
BibRef
Zheng, M.K.[Ming-Kai],
Wang, F.[Fei],
You, S.[Shan],
Qian, C.[Chen],
Zhang, C.S.[Chang-Shui],
Wang, X.G.[Xiao-Gang],
Xu, C.[Chang],
Weakly Supervised Contrastive Learning,
ICCV21(10022-10031)
IEEE DOI
2203
Representation learning, Visualization, Head, Transfer learning,
Semisupervised learning, Labeling, Representation learning,
Transfer/Low-shot/Semi/Unsupervised Learning
BibRef
Diba, A.[Ali],
Sharma, V.[Vivek],
Safdari, R.[Reza],
Lotfi, D.[Dariush],
Sarfraz, M.S.[M. Saquib],
Stiefelhagen, R.[Rainer],
Van Gool, L.J.[Luc J.],
Vi2CLR: Video and Image for Visual Contrastive Learning of
Representation,
ICCV21(1482-1492)
IEEE DOI
2203
Representation learning, Visualization, Image recognition,
Pipelines, Transfer learning, Supervised learning,
Representation learning
BibRef
Zhong, Z.[Zhun],
Fini, E.[Enrico],
Roy, S.[Subhankar],
Luo, Z.M.[Zhi-Ming],
Ricci, E.[Elisa],
Sebe, N.[Nicu],
Neighborhood Contrastive Learning for Novel Class Discovery,
CVPR21(10862-10870)
IEEE DOI
2111
Aggregates, Feature extraction,
Task analysis
BibRef
Kodama, Y.[Yuto],
Wang, Y.[Yinan],
Kawakami, R.[Rei],
Naemura, T.[Takeshi],
Open-set Recognition with Supervised Contrastive Learning,
MVA21(1-5)
DOI Link
2109
Training, Computer aided instruction,
Training data, Feature extraction, Extraterrestrial measurements, Task analysis
BibRef
Ghosh, A.[Aritra],
Lan, A.[Andrew],
Contrastive Learning Improves Model Robustness Under Label Noise,
LLID21(2697-2702)
IEEE DOI
2109
Training, Visualization, Training data,
Semisupervised learning, Robustness
BibRef
Rai, N.[Nishant],
Adeli, E.[Ehsan],
Lee, K.H.[Kuan-Hui],
Gaidon, A.[Adrien],
Niebles, J.C.[Juan Carlos],
CoCon: Cooperative-Contrastive Learning,
HVU21(3379-3388)
IEEE DOI
2109
Visualization, Semantics, Performance gain,
Noise measurement, Labeling
BibRef
Xie, E.[Enze],
Ding, J.[Jian],
Wang, W.H.[Wen-Hai],
Zhan, X.H.[Xiao-Hang],
Xu, H.[Hang],
Sun, P.[Peize],
Li, Z.G.[Zhen-Guo],
Luo, P.[Ping],
DetCo: Unsupervised Contrastive Learning for Object Detection,
ICCV21(8372-8381)
IEEE DOI
2203
Object detection, Detectors, Feature extraction, Task analysis,
Image classification, Detection and localization in 2D and 3D
BibRef
Wang, P.[Peng],
Han, K.[Kai],
Wei, X.S.[Xiu-Shen],
Zhang, L.[Lei],
Wang, L.[Lei],
Contrastive Learning based Hybrid Networks for Long-Tailed Image
Classification,
CVPR21(943-952)
IEEE DOI
2111
Network structure being composed of a supervised contrastive loss to
learn image representations and a cross-entropy loss to learn
classifiers.
Training, Memory management,
Graphics processing units, Image representation, Proposals
BibRef
Kuang, H.F.[Hao-Fei],
Zhu, Y.[Yi],
Zhang, Z.[Zhi],
Li, X.Y.[Xin-Yu],
Tighe, J.[Joseph],
Schwertfeger, S.[Sören],
Stachniss, C.[Cyrill],
Li, M.[Mu],
Video Contrastive Learning with Global Context,
CVEU21(3188-3188)
IEEE DOI
2112
Training, Location awareness, Learning systems, Visualization,
Conferences
BibRef
Lee, K.S.[Kwot Sin],
Tran, N.T.[Ngoc-Trung],
Cheung, N.M.[Ngai-Man],
InfoMax-GAN: Improved Adversarial Image Generation via Information
Maximization and Contrastive Learning,
WACV21(3941-3951)
IEEE DOI
2106
Training, Image synthesis, Generative adversarial networks,
Reproducibility of results, Libraries, Generators, Tuning
BibRef
Shao, H.[Huan],
Yuan, Z.Q.[Zhao-Quan],
Peng, X.[Xiao],
Wu, X.[Xiao],
Contrastive Learning in Frequency Domain for Non-I.I.D. Image
Classification,
MMMod21(I:111-122).
Springer DOI
2106
Not Independent and Identically Distributed.
BibRef
Zhu, R.[Rui],
Zhao, B.C.[Bing-Chen],
Liu, J.G.[Jin-Gen],
Sun, Z.L.[Zheng-Long],
Chen, C.W.[Chang Wen],
Improving Contrastive Learning by Visualizing Feature Transformation,
ICCV21(10286-10295)
IEEE DOI
2203
Contrastive learning, which aims at minimizing the distance between
positive pairs while maximizing that of negative ones.
Training, Representation learning, Interpolation, Extrapolation,
Visualization, Computational modeling, Representation learning,
Transfer/Low-shot/Semi/Unsupervised Learning
BibRef
Yüksel, O.K.[Oguz Kaan],
Simsar, E.[Enis],
Er, E.G.[Ezgi Gülperi],
Yanardag, P.[Pinar],
LatentCLR: A Contrastive Learning Approach for Unsupervised Discovery
of Interpretable Directions,
ICCV21(14243-14252)
IEEE DOI
2203
Image synthesis, Annotations, Computational modeling, Semantics,
Manuals, Aerospace electronics, Image and video synthesis,
Neural generative models
BibRef
Kinakh, V.[Vitaliy],
Taran, O.[Olga],
Voloshynovskiy, S.[Svyatoslav],
ScatSimCLR: Self-Supervised Contrastive Learning with Pretext Task
Regularization for Small-Scale Datasets,
VIPriors21(1098-1106)
IEEE DOI
2112
Training, Adaptation models, Computational modeling, Estimation
BibRef
Dwibedi, D.[Debidatta],
Aytar, Y.[Yusuf],
Tompson, J.[Jonathan],
Sermanet, P.[Pierre],
Zisserman, A.[Andrew],
With a Little Help from My Friends: Nearest-Neighbor Contrastive
Learning of Visual Representations,
ICCV21(9568-9577)
IEEE DOI
2203
Training, Visualization, Protocols, Transfer learning,
Supervised learning, Semantics, Representation learning,
Transfer/Low-shot/Semi/Unsupervised Learning
BibRef
Cui, J.Q.[Jie-Quan],
Zhong, Z.S.[Zhi-Sheng],
Liu, S.[Shu],
Yu, B.[Bei],
Jia, J.Y.[Jia-Ya],
Parametric Contrastive Learning,
ICCV21(695-704)
IEEE DOI
2203
Adaptation models, Image recognition, Codes, Benchmark testing,
Optimization, Recognition and classification, Representation learning
BibRef
Islam, A.[Ashraful],
Chen, C.F.[Chun-Fu],
Panda, R.[Rameswar],
Karlinsky, L.[Leonid],
Radke, R.[Richard],
Feris, R.S.[Rogerio S.],
A Broad Study on the Transferability of Visual Representations with
Contrastive Learning,
ICCV21(8825-8835)
IEEE DOI
2203
Representation learning, Visualization, Adaptation models,
Analytical models, Computational modeling, Transfer learning,
Representation learning
BibRef
Wang, J.[Jin],
Jiang, B.[Bo],
Zero-Shot Learning via Contrastive Learning on Dual Knowledge Graphs,
GSP-CV21(885-892)
IEEE DOI
2112
Knowledge engineering, Learning systems,
Correlation, Semantics, Benchmark testing
BibRef
Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Multiple Kernel Learning, MKL .