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 3231–3240 of 6661 papers

Title	Date	Tasks	Status	Hype
Weakly-supervised positional contrastive learning: application to cirrhosis classification	Jul 10, 2023	ClassificationContrastive Learning	CodeCode Available	1
Graph Contrastive Learning with Multi-Objective for Personalized Product Retrieval in Taobao Search	Jul 10, 2023	Collaborative FilteringContrastive Learning	—Unverified	0
Generalizing Graph ODE for Learning Complex System Dynamics across Environments	Jul 10, 2023	Contrastive LearningPhysical Simulations	—Unverified	0
CognitiveNet: Enriching Foundation Models with Emotions and Awareness	Jul 9, 2023	Contrastive LearningImage Classification	—Unverified	0
DEDUCE: Multi-head attention decoupled contrastive learning to discover cancer subtypes based on multi-omics data	Jul 9, 2023	Contrastive Learning	CodeCode Available	0
FILM: How can Few-Shot Image Classification Benefit from Pre-Trained Language Models?	Jul 9, 2023	Contrastive LearningFew-Shot Image Classification	—Unverified	0
ECL: Class-Enhancement Contrastive Learning for Long-tailed Skin Lesion Classification	Jul 9, 2023	Contrastive LearningLesion Classification	CodeCode Available	1
End-to-End Supervised Multilabel Contrastive Learning	Jul 8, 2023	Contrastive Learningimage-classification	CodeCode Available	0
Discovering Hierarchical Achievements in Reinforcement Learning via Contrastive Learning	Jul 7, 2023	Contrastive Learningreinforcement-learning	CodeCode Available	1
AdaptiveRec: Adaptively Construct Pairs for Contrastive Learning in Sequential Recommendation	Jul 7, 2023	Contrastive LearningRecommendation Systems	—Unverified	0

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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