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 1451–1475 of 6661 papers

Title	Date	Tasks	Status	Hype
Masked Spectrogram Modeling using Masked Autoencoders for Learning General-purpose Audio Representation	Apr 26, 2022	Contrastive LearningSelf-Supervised Learning	CodeCode Available	1
Distance-based Hyperspherical Classification for Multi-source Open-Set Domain Adaptation	Jul 5, 2021	Contrastive LearningDomain Adaptation	CodeCode Available	1
Contrastive Prototypical Network with Wasserstein Confidence Penalty	Oct 21, 2022	Contrastive LearningFew-Shot Learning	CodeCode Available	1
Contrastive Quantization with Code Memory for Unsupervised Image Retrieval	Sep 11, 2021	Contrastive LearningDeep Hashing	CodeCode Available	1
Disentangled and Controllable Face Image Generation via 3D Imitative-Contrastive Learning	Apr 24, 2020	Contrastive LearningDisentanglement	CodeCode Available	1
Contrastive Trajectory Similarity Learning with Dual-Feature Attention	Oct 11, 2022	Contrastive LearningTrajectory Modeling	CodeCode Available	1
Contrastive Registration for Unsupervised Medical Image Segmentation	Nov 17, 2020	Contrastive LearningImage Segmentation	CodeCode Available	1
CaCo: Both Positive and Negative Samples are Directly Learnable via Cooperative-adversarial Contrastive Learning	Mar 27, 2022	Contrastive LearningSelf-Supervised Image Classification	CodeCode Available	1
Contrastive Representation Distillation	Oct 23, 2019	Contrastive LearningKnowledge Distillation	CodeCode Available	1
MCSE: Multimodal Contrastive Learning of Sentence Embeddings	Apr 22, 2022	Contrastive LearningSemantic Textual Similarity	CodeCode Available	1
Disentangled Causal Embedding With Contrastive Learning For Recommender System	Feb 7, 2023	Contrastive LearningRecommendation Systems	CodeCode Available	1
Contrastive Test-Time Adaptation	Apr 21, 2022	Contrastive LearningDomain Adaptation	CodeCode Available	1
Contrastive Representation Learning for Exemplar-Guided Paraphrase Generation	Sep 3, 2021	Contrastive LearningDecoder	CodeCode Available	1
CALDA: Improving Multi-Source Time Series Domain Adaptation with Contrastive Adversarial Learning	Sep 30, 2021	Activity RecognitionContrastive Learning	CodeCode Available	1
Contrastive Representation Learning for Dynamic Link Prediction in Temporal Networks	Aug 22, 2024	Contrastive LearningDynamic Link Prediction	CodeCode Available	1
Memory Augmented Multi-Instance Contrastive Predictive Coding for Sequential Recommendation	Sep 1, 2021	Contrastive LearningSequential Recommendation	CodeCode Available	1
Data Poisoning Attacks Against Multimodal Encoders	Sep 30, 2022	Contrastive LearningData Poisoning	CodeCode Available	1
Contrastive Representation Learning for Gaze Estimation	Oct 24, 2022	Contrastive LearningData Augmentation	CodeCode Available	1
Metadata-Induced Contrastive Learning for Zero-Shot Multi-Label Text Classification	Feb 11, 2022	Contrastive LearningMulti Label Text Classification	CodeCode Available	1
MetaMask: Revisiting Dimensional Confounder for Self-Supervised Learning	Sep 16, 2022	Contrastive LearningMeta-Learning	CodeCode Available	1
Compositional Exemplars for In-context Learning	Feb 11, 2023	Code GenerationContrastive Learning	CodeCode Available	1
Contrastive Retrospection: honing in on critical steps for rapid learning and generalization in RL	Oct 12, 2022	Contrastive LearningOut-of-Distribution Generalization	CodeCode Available	1
Contrastive Tuning: A Little Help to Make Masked Autoencoders Forget	Apr 20, 2023	ClusteringContrastive Learning	CodeCode Available	1
A picture of the space of typical learnable tasks	Oct 31, 2022	Contrastive LearningMeta-Learning	CodeCode Available	1
Disentangled Contrastive Collaborative Filtering	May 4, 2023	Collaborative FilteringContrastive Learning	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