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

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Showing 721–730 of 6661 papers

Title	Date	Tasks	Status	Hype
CT4Rec: Simple yet Effective Consistency Training for Sequential Recommendation	Dec 13, 2021	Click-Through Rate PredictionContrastive Learning	CodeCode Available	1
3D Human Action Representation Learning via Cross-View Consistency Pursuit	Apr 29, 2021	Action RecognitionContrastive Learning	CodeCode Available	1
C3: Cross-instance guided Contrastive Clustering	Nov 14, 2022	ClusteringContrastive Learning	CodeCode Available	1
Adversarial Contrastive Learning via Asymmetric InfoNCE	Jul 18, 2022	Adversarial RobustnessContrastive Learning	CodeCode Available	1
DisCo: Remedy Self-supervised Learning on Lightweight Models with Distilled Contrastive Learning	Apr 19, 2021	Contrastive LearningRepresentation Learning	CodeCode Available	1
C3S3: Complementary Competition and Contrastive Selection for Semi-Supervised Medical Image Segmentation	Jun 9, 2025	Contrastive LearningDiagnostic	CodeCode Available	1
Disentangled and Controllable Face Image Generation via 3D Imitative-Contrastive Learning	Apr 24, 2020	Contrastive LearningDisentanglement	CodeCode Available	1
CaCo: Both Positive and Negative Samples are Directly Learnable via Cooperative-adversarial Contrastive Learning	Mar 27, 2022	Contrastive LearningSelf-Supervised Image Classification	CodeCode Available	1
Disentangled Contrastive Collaborative Filtering	May 4, 2023	Collaborative FilteringContrastive Learning	CodeCode Available	1
Contrastive Learning for Knowledge Tracing	Apr 25, 2022	Contrastive LearningData Augmentation	CodeCode Available	1

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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