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 401–410 of 6661 papers

Title	Date	Tasks	Status	Hype	Score
Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning	Feb 27, 2021	Anomaly DetectionContrastive Learning	CodeCode Available	1	5
A Self-Supervised Gait Encoding Approach with Locality-Awareness for 3D Skeleton Based Person Re-Identification	Sep 5, 2020	Contrastive LearningPerson Re-Identification	CodeCode Available	1	5
A Contrastive Cross-Channel Data Augmentation Framework for Aspect-based Sentiment Analysis	Apr 16, 2022	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	CodeCode Available	1	5
A Self-supervised Method for Entity Alignment	Jun 17, 2021	Contrastive LearningEntity Alignment	CodeCode Available	1	5
Contrastive Model Adaptation for Cross-Condition Robustness in Semantic Segmentation	Mar 9, 2023	Contrastive LearningDomain Adaptation	CodeCode Available	1	5
Contrastive Model Inversion for Data-Free Knowledge Distillation	May 18, 2021	Contrastive LearningData-free Knowledge Distillation	CodeCode Available	1	5
CaseGNN++: Graph Contrastive Learning for Legal Case Retrieval with Graph Augmentation	May 20, 2024	Contrastive LearningGraph Attention	CodeCode Available	1	5
Category Contrast for Unsupervised Domain Adaptation in Visual Tasks	Jun 5, 2021	Contrastive LearningDomain Adaptation	CodeCode Available	1	5
Contrastive Neural Processes for Self-Supervised Learning	Oct 24, 2021	Contrastive LearningData Augmentation	CodeCode Available	1	5
Contrastive Learning for Neural Topic Model	Oct 25, 2021	Contrastive Learningmodel	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