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 1361–1370 of 6661 papers

Title	Date	Tasks	Status	Hype
Contrastive Learning of Musical Representations	Mar 17, 2021	Contrastive LearningLinear evaluation	CodeCode Available	1
Intent Contrastive Learning with Cross Subsequences for Sequential Recommendation	Oct 22, 2023	Contrastive LearningData Augmentation	CodeCode Available	1
Contrastive Learning with Cross-Modal Knowledge Mining for Multimodal Human Activity Recognition	May 20, 2022	Activity RecognitionContrastive Learning	CodeCode Available	1
Differentiable Data Augmentation for Contrastive Sentence Representation Learning	Oct 29, 2022	Contrastive LearningData Augmentation	CodeCode Available	1
Digging into contrastive learning for robust depth estimation with diffusion models	Apr 15, 2024	Contrastive LearningDenoising	CodeCode Available	1
Network Comparison with Interpretable Contrastive Network Representation Learning	May 25, 2020	Contrastive LearningRepresentation Learning	CodeCode Available	1
Does Learning from Decentralized Non-IID Unlabeled Data Benefit from Self Supervision?	Oct 20, 2022	Contrastive LearningRepresentation Learning	CodeCode Available	1
Contrastive Learning of Sentence Embeddings from Scratch	May 24, 2023	Contrastive LearningNatural Language Inference	CodeCode Available	1
An Interactive Multi-modal Query Answering System with Retrieval-Augmented Large Language Models	Jul 5, 2024	Answer GenerationContrastive Learning	CodeCode Available	1
DetCo: Unsupervised Contrastive Learning for Object Detection	Feb 9, 2021	Contrastive Learningimage-classification	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