Contrastive Learning

Contrastive Learning is a deep learning technique for unsupervised representation learning. The goal is to learn a representation of data such that similar instances are close together in the representation space, while dissimilar instances are far apart.

It has been shown to be effective in various computer vision and natural language processing tasks, including image retrieval, zero-shot learning, and cross-modal retrieval. In these tasks, the learned representations can be used as features for downstream tasks such as classification and clustering.

(Image credit: Schroff et al. 2015)

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 6001–6025 of 6661 papers

Title	Date	Tasks	Status	Hype
Interventional Video Grounding with Dual Contrastive Learning	Jun 21, 2021	Causal InferenceContrastive Learning	CodeCode Available	0
Contrastive learning for natural language-based vehicle retrieval	Jun 20, 2021	Contrastive LearningRetrieval	CodeCode Available	0
Neighborhood Contrastive Learning for Novel Class Discovery	Jun 20, 2021	ClusteringContrastive Learning	CodeCode Available	1
Underwater Image Restoration via Contrastive Learning and a Real-world Dataset	Jun 20, 2021	BenchmarkingContrastive Learning	CodeCode Available	1
Global and Local Contrastive Self-Supervised Learning for Semantic Segmentation of HR Remote Sensing Images	Jun 20, 2021	Contrastive LearningSegmentation	—Unverified	0
Practical Assessment of Generalization Performance Robustness for Deep Networks via Contrastive Examples	Jun 20, 2021	Contrastive Learning	—Unverified	0
Mining Better Samples for Contrastive Learning of Temporal Correspondence	Jun 19, 2021	Contrastive Learning	—Unverified	0
Mol2Image: Improved Conditional Flow Models for Molecule to Image Synthesis	Jun 19, 2021	Contrastive LearningImage Generation	—Unverified	0
Progressive Unsupervised Learning for Visual Object Tracking	Jun 19, 2021	Contrastive LearningObject	—Unverified	0
Self-Supervised Video GANs: Learning for Appearance Consistency and Motion Coherency	Jun 19, 2021	Contrastive Learning	—Unverified	0
Spatio-temporal Contrastive Domain Adaptation for Action Recognition	Jun 19, 2021	Action RecognitionContrastive Learning	—Unverified	0
Exploring Heterogeneous Clues for Weakly-Supervised Audio-Visual Video Parsing	Jun 19, 2021	Contrastive Learning	—Unverified	0
TS2Vec: Towards Universal Representation of Time Series	Jun 19, 2021	Anomaly DetectionContrastive Learning	CodeCode Available	1
Source-free Domain Adaptation via Avatar Prototype Generation and Adaptation	Jun 18, 2021	Contrastive LearningDomain Adaptation	CodeCode Available	1
Residual Contrastive Learning for Image Reconstruction: Learning Transferable Representations from Noisy Images	Jun 18, 2021	Contrastive LearningDemosaicking	—Unverified	0
Self-supervised Video Representation Learning with Cross-Stream Prototypical Contrasting	Jun 18, 2021	Action RecognitionAction Recognition In Videos	CodeCode Available	1
Contrastive Learning of Generalized Game Representations	Jun 18, 2021	Contrastive LearningImage Classification	CodeCode Available	1
Novelty Detection via Contrastive Learning with Negative Data Augmentation	Jun 18, 2021	ClusteringContrastive Learning	—Unverified	0
Investigating the Role of Negatives in Contrastive Representation Learning	Jun 18, 2021	Contrastive LearningData Augmentation	—Unverified	0
A Self-supervised Method for Entity Alignment	Jun 17, 2021	Contrastive LearningEntity Alignment	CodeCode Available	1
Deep Contrastive Graph Representation via Adaptive Homotopy Learning	Jun 17, 2021	Contrastive Learning	—Unverified	0
Long-Short Temporal Contrastive Learning of Video Transformers	Jun 17, 2021	Action RecognitionContrastive Learning	—Unverified	0
Prototypical Graph Contrastive Learning	Jun 17, 2021	ClusteringContrastive Learning	CodeCode Available	1
Learning to Predict Visual Attributes in the Wild	Jun 17, 2021	AttributeContrastive Learning	—Unverified	0
MaCLR: Motion-aware Contrastive Learning of Representations for Videos	Jun 17, 2021	Action DetectionAction Recognition	CodeCode Available	0

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All datasets imagenet-1k 10,000 People - Human Pose Recognition Data CIFAR-10 STL-10

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	ResNet50	ImageNet Top-1 Accuracy	73.6	—	Unverified
2	ResNet50	ImageNet Top-1 Accuracy	73	—	Unverified
3	ResNet50	ImageNet Top-1 Accuracy	71.1	—	Unverified
4	ResNet50	ImageNet Top-1 Accuracy	69.3	—	Unverified
5	ResNet50 (v2)	ImageNet Top-1 Accuracy	67.6	—	Unverified
6	ResNet50 (v2)	ImageNet Top-1 Accuracy	63.8	—	Unverified
7	ResNet50	ImageNet Top-1 Accuracy	63.6	—	Unverified
8	ResNet50	ImageNet Top-1 Accuracy	61.5	—	Unverified
9	ResNet50	ImageNet Top-1 Accuracy	61.5	—	Unverified
10	ResNet50 (4×)	ImageNet Top-1 Accuracy	61.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	1	0..5sec	1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	IPCL (ResNet18)	Accuracy (Top-1)	84.77	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	IPCL (ResNet18)	Accuracy (Top-1)	85.55	—	Unverified