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 2001–2010 of 6661 papers

Title	Date	Tasks	Status
DRAMA: Diverse Augmentation from Large Language Models to Smaller Dense Retrievers	Feb 25, 2025	Contrastive Learning	—Unverified
DrasCLR: A Self-supervised Framework of Learning Disease-related and Anatomy-specific Representation for 3D Medical Images	Feb 21, 2023	AnatomyContrastive Learning	—Unverified
CO3: Low-resource Contrastive Co-training for Generative Conversational Query Rewrite	Mar 18, 2024	Contrastive LearningData Augmentation	—Unverified
DreamGrasp: Zero-Shot 3D Multi-Object Reconstruction from Partial-View Images for Robotic Manipulation	Jul 8, 2025	3D geometry3D Reconstruction	—Unverified
Distilling Structured Knowledge for Text-Based Relational Reasoning	Nov 1, 2020	Contrastive LearningKnowledge Distillation	—Unverified
DreamingV2: Reinforcement Learning with Discrete World Models without Reconstruction	Mar 1, 2022	Contrastive LearningModel-based Reinforcement Learning	—Unverified
A two-steps approach to improve the performance of Android malware detectors	May 17, 2022	Android Malware DetectionBinary Classification	—Unverified
AlexU-AIC at Arabic Hate Speech 2022: Contrast to Classify	Jul 18, 2022	Contrastive LearningMulti-Task Learning	—Unverified
Feature Normalization Prevents Collapse of Non-contrastive Learning Dynamics	Sep 28, 2023	Computational EfficiencyContrastive Learning	—Unverified
Features-over-the-Air: Contrastive Learning Enabled Cooperative Edge Inference	Apr 17, 2023	Contrastive LearningImage Retrieval	—Unverified

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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