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 4851–4875 of 6661 papers

Title	Date	Tasks	Status	Hype
Words are all you need? Language as an approximation for human similarity judgments	Jun 8, 2022	AllContrastive Learning	—Unverified	0
CO^3: Cooperative Unsupervised 3D Representation Learning for Autonomous Driving	Jun 8, 2022	Autonomous DrivingContrastive Learning	CodeCode Available	1
ConFUDA: Contrastive Fewshot Unsupervised Domain Adaptation for Medical Image Segmentation	Jun 8, 2022	Contrastive LearningDomain Adaptation	—Unverified	0
Mixed Graph Contrastive Network for Semi-Supervised Node Classification	Jun 6, 2022	ClassificationContrastive Learning	—Unverified	0
Contrastive Graph Multimodal Model for Text Classification in Videos	Jun 6, 2022	ClassificationContrastive Learning	—Unverified	0
Improving Contrastive Learning of Sentence Embeddings with Case-Augmented Positives and Retrieved Negatives	Jun 6, 2022	AttributeContrastive Learning	CodeCode Available	1
Bootstrapping Semi-supervised Medical Image Segmentation with Anatomical-aware Contrastive Distillation	Jun 6, 2022	Contrastive LearningImage Segmentation	CodeCode Available	1
Multimodal Contrastive Learning with LIMoE: the Language-Image Mixture of Experts	Jun 6, 2022	Contrastive LearningMixture-of-Experts	—Unverified	0
Consensus Learning for Cooperative Multi-Agent Reinforcement Learning	Jun 6, 2022	Contrastive LearningMulti-agent Reinforcement Learning	—Unverified	0
Semi-Supervised Learning for Mars Imagery Classification and Segmentation	Jun 5, 2022	ClassificationContrastive Learning	—Unverified	0
From t-SNE to UMAP with contrastive learning	Jun 3, 2022	Contrastive LearningRepresentation Learning	CodeCode Available	1
Integrating Prior Knowledge in Contrastive Learning with Kernel	Jun 3, 2022	Contrastive LearningData Augmentation	CodeCode Available	0
Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discrimination	Jun 3, 2022	Contrastive LearningGraph Representation Learning	CodeCode Available	1
Egocentric Video-Language Pretraining	Jun 3, 2022	Action RecognitionContrastive Learning	CodeCode Available	2
3D-Augmented Contrastive Knowledge Distillation for Image-based Object Pose Estimation	Jun 2, 2022	Contrastive LearningKnowledge Distillation	—Unverified	0
Understanding the Role of Nonlinearity in Training Dynamics of Contrastive Learning	Jun 2, 2022	Contrastive LearningSelf-Supervised Learning	—Unverified	0
Hyperspherical Consistency Regularization	Jun 2, 2022	Contrastive LearningSelf-Supervised Learning	CodeCode Available	1
Prefix Conditioning Unifies Language and Label Supervision	Jun 2, 2022	ClassificationContrastive Learning	—Unverified	0
Hard Negative Sampling Strategies for Contrastive Representation Learning	Jun 2, 2022	Contrastive LearningRepresentation Learning	—Unverified	0
Cross-lingual and Multilingual CLIP	Jun 1, 2022	Contrastive LearningImage-text Retrieval	CodeCode Available	2
Mitigating Dataset Artifacts in Natural Language Inference Through Automatic Contextual Data Augmentation and Learning Optimization	Jun 1, 2022	Contrastive LearningData Augmentation	—Unverified	0
Positive Unlabeled Contrastive Learning	Jun 1, 2022	Contrastive LearningPseudo Label	—Unverified	0
Multi-scale frequency separation network for image deblurring	Jun 1, 2022	Contrastive LearningDeblurring	—Unverified	0
Strongly Augmented Contrastive Clustering	Jun 1, 2022	ClusteringContrastive Learning	CodeCode Available	1
Augmentation Component Analysis: Modeling Similarity via the Augmentation Overlaps	Jun 1, 2022	Contrastive LearningDimensionality Reduction	CodeCode Available	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