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 4826–4850 of 6661 papers

Title	Date	Tasks	Status	Hype
Evaluation of Contrastive Learning with Various Code Representations for Code Clone Detection	Jun 17, 2022	Clone DetectionCode Summarization	—Unverified	0
MET: Masked Encoding for Tabular Data	Jun 17, 2022	Contrastive LearningRepresentation Learning	CodeCode Available	1
DU-Net based Unsupervised Contrastive Learning for Cancer Segmentation in Histology Images	Jun 17, 2022	Contrastive LearningData Augmentation	—Unverified	0
Learning Fair Representation via Distributional Contrastive Disentanglement	Jun 17, 2022	Contrastive LearningDisentanglement	CodeCode Available	1
VLMixer: Unpaired Vision-Language Pre-training via Cross-Modal CutMix	Jun 17, 2022	Contrastive Learningcross-modal alignment	—Unverified	0
Beyond Supervised vs. Unsupervised: Representative Benchmarking and Analysis of Image Representation Learning	Jun 16, 2022	BenchmarkingClustering	CodeCode Available	0
NCAGC: A Neighborhood Contrast Framework for Attributed Graph Clustering	Jun 16, 2022	ClusteringContrastive Learning	CodeCode Available	1
Volumetric Supervised Contrastive Learning for Seismic Semantic Segmentation	Jun 16, 2022	Contrastive LearningPosition	—Unverified	0
Let Invariant Rationale Discovery Inspire Graph Contrastive Learning	Jun 16, 2022	Contrastive Learning	CodeCode Available	1
Text-Aware End-to-end Mispronunciation Detection and Diagnosis	Jun 15, 2022	Contrastive LearningPhoneme Recognition	CodeCode Available	1
Contrastive Learning as Goal-Conditioned Reinforcement Learning	Jun 15, 2022	Contrastive LearningData Augmentation	—Unverified	0
Discrete Contrastive Diffusion for Cross-Modal Music and Image Generation	Jun 15, 2022	Contrastive LearningDenoising	CodeCode Available	1
Label-enhanced Prototypical Network with Contrastive Learning for Multi-label Few-shot Aspect Category Detection	Jun 14, 2022	Aspect Category DetectionContrastive Learning	—Unverified	0
Towards a Solution to Bongard Problems: A Causal Approach	Jun 14, 2022	Contrastive Learningreinforcement-learning	—Unverified	0
On Finite-Sample Identifiability of Contrastive Learning-Based Nonlinear Independent Component Analysis	Jun 14, 2022	Contrastive LearningDisentanglement	—Unverified	0
Self-Supervised Representation Learning With MUlti-Segmental Informational Coding (MUSIC)	Jun 13, 2022	Contrastive LearningRepresentation Learning	—Unverified	0
Contrastive Learning for Unsupervised Domain Adaptation of Time Series	Jun 13, 2022	Contrastive LearningDomain Adaptation	CodeCode Available	1
Transductive CLIP with Class-Conditional Contrastive Learning	Jun 13, 2022	Contrastive LearningPseudo Label	—Unverified	0
GLIPv2: Unifying Localization and Vision-Language Understanding	Jun 12, 2022	2D Object DetectionContrastive Learning	CodeCode Available	4
Is Self-Supervised Learning More Robust Than Supervised Learning?	Jun 10, 2022	Contrastive LearningData Augmentation	—Unverified	0
ClamNet: Using contrastive learning with variable depth Unets for medical image segmentation	Jun 10, 2022	Computed Tomography (CT)Contrastive Learning	—Unverified	0
STNDT: Modeling Neural Population Activity with a Spatiotemporal Transformer	Jun 9, 2022	Contrastive Learning	—Unverified	0
COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning	Jun 9, 2022	Contrastive LearningGraph Representation Learning	CodeCode Available	1
I'm Me, We're Us, and I'm Us: Tri-directional Contrastive Learning on Hypergraphs	Jun 9, 2022	Contrastive LearningData Augmentation	CodeCode Available	1
An Empirical Study on Disentanglement of Negative-free Contrastive Learning	Jun 9, 2022	Contrastive LearningDisentanglement	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