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 6251–6275 of 6661 papers

Title	Date	Tasks	Status	Hype
Adversarial Examples can be Effective Data Augmentation for Unsupervised Machine Learning	Mar 2, 2021	BIG-bench Machine LearningContrastive Learning	CodeCode Available	0
Partially View-aligned Representation Learning with Noise-robust Contrastive Loss	Mar 1, 2021	ClusteringContrastive Learning	CodeCode Available	1
Panoramic Panoptic Segmentation: Towards Complete Surrounding Understanding via Unsupervised Contrastive Learning	Mar 1, 2021	Contrastive LearningPanoptic Segmentation	CodeCode Available	1
Fool Me Once: Robust Selective Segmentation via Out-of-Distribution Detection with Contrastive Learning	Mar 1, 2021	Contrastive LearningData Augmentation	—Unverified	0
Using contrastive learning to improve the performance of steganalysis schemes	Mar 1, 2021	Contrastive LearningSteganalysis	—Unverified	0
Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning	Feb 27, 2021	Anomaly DetectionContrastive Learning	CodeCode Available	1
Consistent Assignment for Representation Learning	Feb 26, 2021	ClusteringContrastive Learning	—Unverified	0
A Primer on Contrastive Pretraining in Language Processing: Methods, Lessons Learned and Perspectives	Feb 25, 2021	Contrastive LearningLanguage Modeling	—Unverified	0
Towards Robust Graph Contrastive Learning	Feb 25, 2021	Adversarial RobustnessContrastive Learning	—Unverified	0
Provably Improved Context-Based Offline Meta-RL with Attention and Contrastive Learning	Feb 22, 2021	Contrastive LearningMeta-Learning	—Unverified	0
MedAug: Contrastive learning leveraging patient metadata improves representations for chest X-ray interpretation	Feb 21, 2021	Contrastive Learning	—Unverified	0
Learning Disentangled Representation by Exploiting Pretrained Generative Models: A Contrastive Learning View	Feb 21, 2021	Contrastive LearningDisentanglement	CodeCode Available	1
On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning	Feb 20, 2021	Adversarial AttackAdversarial Robustness	CodeCode Available	1
Molecular Contrastive Learning of Representations via Graph Neural Networks	Feb 19, 2021	BIG-bench Machine LearningContrastive Learning	CodeCode Available	1
CUPR: Contrastive Unsupervised Learning for Person Re-identification	Feb 18, 2021	ClusteringContrastive Learning	—Unverified	0
Contrastive Learning Inverts the Data Generating Process	Feb 17, 2021	Contrastive LearningDisentanglement	CodeCode Available	1
S2-BNN: Bridging the Gap Between Self-Supervised Real and 1-bit Neural Networks via Guided Distribution Calibration	Feb 17, 2021	Contrastive LearningSelf-Supervised Learning	CodeCode Available	1
Dissecting Supervised Contrastive Learning	Feb 17, 2021	Contrastive Learning	CodeCode Available	0
COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretraining	Feb 16, 2021	Contrastive LearningGPU	CodeCode Available	1
Self-Supervised Multisensor Change Detection	Feb 12, 2021	BIG-bench Machine LearningChange Detection	—Unverified	0
Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regularized Fine-Tuning	Feb 12, 2021	Contrastive Learningimage-classification	CodeCode Available	1
Large-Scale Representation Learning on Graphs via Bootstrapping	Feb 12, 2021	Contrastive LearningGraph Representation Learning	CodeCode Available	1
Semantically-Conditioned Negative Samples for Efficient Contrastive Learning	Feb 12, 2021	Contrastive LearningKnowledge Distillation	—Unverified	0
CDPAM: Contrastive learning for perceptual audio similarity	Feb 9, 2021	Contrastive LearningSpeech Enhancement	CodeCode Available	1
Negative Data Augmentation	Feb 9, 2021	Action RecognitionAnomaly Detection	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