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 1701–1725 of 6661 papers

Title	Date	Tasks	Status	Hype	Score
Decoupled Contrastive Learning for Long-Tailed Recognition	Mar 10, 2024	Contrastive LearningRepresentation Learning	CodeCode Available	1	5
MA-GCL: Model Augmentation Tricks for Graph Contrastive Learning	Dec 14, 2022	Contrastive LearningData Augmentation	CodeCode Available	1	5
Data Poisoning based Backdoor Attacks to Contrastive Learning	Jan 1, 2024	Contrastive LearningData Poisoning	CodeCode Available	1	5
Manifold DivideMix: A Semi-Supervised Contrastive Learning Framework for Severe Label Noise	Aug 13, 2023	Contrastive Learning	CodeCode Available	1	5
Decoupled Adversarial Contrastive Learning for Self-supervised Adversarial Robustness	Jul 22, 2022	Adversarial RobustnessContrastive Learning	CodeCode Available	1	5
SLICER: Learning universal audio representations using low-resource self-supervised pre-training	Nov 2, 2022	Audio ClassificationClustering	CodeCode Available	1	5
Discriminative and Consistent Representation Distillation	Jul 16, 2024	Causal InferenceContrastive Learning	CodeCode Available	1	5
Company-as-Tribe: Company Financial Risk Assessment on Tribe-Style Graph with Hierarchical Graph Neural Networks	Jan 31, 2023	Contrastive LearningGraph Learning	CodeCode Available	1	5
SMiLE: Schema-augmented Multi-level Contrastive Learning for Knowledge Graph Link Prediction	Oct 10, 2022	Contrastive LearningKnowledge Graphs	CodeCode Available	1	5
MABEL: Attenuating Gender Bias using Textual Entailment Data	Oct 26, 2022	Contrastive LearningFairness	CodeCode Available	1	5
ISD: Self-Supervised Learning by Iterative Similarity Distillation	Dec 16, 2020	Contrastive LearningSelf-Supervised Learning	CodeCode Available	1	5
Joint Generative and Contrastive Learning for Unsupervised Person Re-identification	Dec 16, 2020	Contrastive LearningData Augmentation	CodeCode Available	1	5
Decoupled Contrastive Learning	Oct 13, 2021	Contrastive LearningSelf-Supervised Learning	CodeCode Available	1	5
DC-Seg: Disentangled Contrastive Learning for Brain Tumor Segmentation with Missing Modalities	May 17, 2025	Brain Tumor SegmentationContrastive Learning	CodeCode Available	1	5
Contrastive Pretraining for Echocardiography Segmentation with Limited Data	Jan 16, 2022	Contrastive LearningImage Segmentation	CodeCode Available	1	5
Soft Contrastive Learning for Visual Localization	Dec 1, 2020	Contrastive LearningImage Retrieval	CodeCode Available	1	5
Is Contrastive Learning Necessary? A Study of Data Augmentation vs Contrastive Learning in Sequential Recommendation	Mar 17, 2024	Contrastive LearningData Augmentation	CodeCode Available	1	5
Self-Supervised Pre-Training with Contrastive and Masked Autoencoder Methods for Dealing with Small Datasets in Deep Learning for Medical Imaging	Aug 12, 2023	Contrastive LearningDiagnostic	CodeCode Available	1	5
ItTakesTwo: Leveraging Peer Representations for Semi-supervised LiDAR Semantic Segmentation	Jul 9, 2024	Contrastive LearningLIDAR Semantic Segmentation	CodeCode Available	1	5
Joint Contrastive Learning with Infinite Possibilities	Sep 30, 2020	Contrastive Learning	CodeCode Available	1	5
Debiased Contrastive Learning	Jul 1, 2020	Contrastive LearningGeneralization Bounds	CodeCode Available	1	5
Debiased Contrastive Learning for Sequential Recommendation	Mar 21, 2023	Contrastive LearningData Augmentation	CodeCode Available	1	5
CLCC: Contrastive Learning for Color Constancy	Jun 9, 2021	Color ConstancyContrastive Learning	CodeCode Available	1	5
Jigsaw Clustering for Unsupervised Visual Representation Learning	Apr 1, 2021	ClusteringContrastive Learning	CodeCode Available	1	5
Community-Invariant Graph Contrastive Learning	May 2, 2024	Contrastive Learning	CodeCode Available	1	5

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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