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 3971–3980 of 6661 papers

Title	Date	Tasks	Status
INTRA: Interaction Relationship-aware Weakly Supervised Affordance Grounding	Sep 10, 2024	Contrastive LearningLanguage Modeling	—Unverified
Intra-Inter Subject Self-supervised Learning for Multivariate Cardiac Signals	Sep 18, 2021	Contrastive LearningSelf-Supervised Learning	—Unverified
Intuitive Access to Smartphone Settings Using Relevance Model Trained by Contrastive Learning	Jul 15, 2023	Contrastive LearningKnowledge Distillation	—Unverified
Invariance-adapted decomposition and Lasso-type contrastive learning	Oct 13, 2022	Contrastive LearningVocal Bursts Type Prediction	—Unverified
Invariant and consistent: Unsupervised representation learning for few-shot visual recognition	Nov 1, 2022	Contrastive LearningRepresentation Learning	—Unverified
InverTune: Removing Backdoors from Multimodal Contrastive Learning Models via Trigger Inversion and Activation Tuning	Jun 14, 2025	backdoor defenseContrastive Learning	—Unverified
Investigating Data Memorization in 3D Latent Diffusion Models for Medical Image Synthesis	Jul 3, 2023	Contrastive LearningImage Generation	—Unverified
Investigating Deep Neural Network Architecture and Feature Extraction Designs for Sensor-based Human Activity Recognition	Sep 26, 2023	Activity RecognitionContrastive Learning	—Unverified
Investigating Graph Structure Information for Entity Alignment with Dangling Cases	Apr 10, 2023	Contrastive LearningEntity Alignment	—Unverified
End-to-End Lyrics Recognition with Self-supervised Learning	Sep 26, 2022	Contrastive LearningDomain Generalization	—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