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 4291–4300 of 6661 papers

Title	Date	Tasks	Status	Hype
A simple, efficient and scalable contrastive masked autoencoder for learning visual representations	Oct 30, 2022	Contrastive LearningSelf-Supervised Learning	CodeCode Available	1
Adaptive Speech Quality Aware Complex Neural Network for Acoustic Echo Cancellation with Supervised Contrastive Learning	Oct 30, 2022	Acoustic echo cancellationContrastive Learning	—Unverified	0
Image-free Domain Generalization via CLIP for 3D Hand Pose Estimation	Oct 30, 2022	3D Hand Pose EstimationContrastive Learning	—Unverified	0
Rare Wildlife Recognition with Self-Supervised Representation Learning	Oct 29, 2022	Contrastive LearningRepresentation Learning	CodeCode Available	0
Differentiable Data Augmentation for Contrastive Sentence Representation Learning	Oct 29, 2022	Contrastive LearningData Augmentation	CodeCode Available	1
Discriminative Speaker Representation via Contrastive Learning with Class-Aware Attention in Angular Space	Oct 29, 2022	Contrastive LearningSpeaker Verification	—Unverified	0
Speaker Representation Learning via Contrastive Loss with Maximal Speaker Separability	Oct 29, 2022	Contrastive LearningData Augmentation	CodeCode Available	1
DisenPOI: Disentangling Sequential and Geographical Influence for Point-of-Interest Recommendation	Oct 29, 2022	Contrastive LearningDisentanglement	CodeCode Available	1
Pair DETR: Contrastive Learning Speeds Up DETR Training	Oct 29, 2022	Contrastive LearningDecoder	—Unverified	0
Improving the Modality Representation with Multi-View Contrastive Learning for Multimodal Sentiment Analysis	Oct 28, 2022	Contrastive LearningMultimodal Sentiment Analysis	—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