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 551–575 of 6661 papers

Title	Date	Tasks	Status	Hype
Learning to Embed Time Series Patches Independently	Dec 27, 2023	Contrastive LearningRepresentation Learning	CodeCode Available	1
Soft Contrastive Learning for Time Series	Dec 27, 2023	Anomaly DetectionContrastive Learning	CodeCode Available	1
A Unified Generative Framework for Realistic Lidar Simulation in Autonomous Driving Systems	Dec 25, 2023	Autonomous DrivingContrastive Learning	CodeCode Available	1
A Multi-Modal Contrastive Diffusion Model for Therapeutic Peptide Generation	Dec 25, 2023	Contrastive LearningDiversity	CodeCode Available	1
TimesURL: Self-supervised Contrastive Learning for Universal Time Series Representation Learning	Dec 25, 2023	Anomaly DetectionContrastive Learning	CodeCode Available	1
Token-Level Contrastive Learning with Modality-Aware Prompting for Multimodal Intent Recognition	Dec 22, 2023	Contrastive LearningIntent Recognition	CodeCode Available	1
Energy-based learning algorithms for analog computing: a comparative study	Dec 22, 2023	Contrastive Learning	CodeCode Available	1
Towards More Faithful Natural Language Explanation Using Multi-Level Contrastive Learning in VQA	Dec 21, 2023	Contrastive Learningcounterfactual	CodeCode Available	1
DVIS++: Improved Decoupled Framework for Universal Video Segmentation	Dec 20, 2023	Contrastive LearningDenoising	CodeCode Available	1
Emotion Rendering for Conversational Speech Synthesis with Heterogeneous Graph-Based Context Modeling	Dec 19, 2023	Contrastive LearningSpeech Synthesis	CodeCode Available	1
Object-Aware Domain Generalization for Object Detection	Dec 19, 2023	Autonomous DrivingContrastive Learning	CodeCode Available	1
Knowledge Graph Error Detection with Contrastive Confidence Adaption	Dec 19, 2023	Contrastive LearningKnowledge Graphs	CodeCode Available	1
ContraNovo: A Contrastive Learning Approach to Enhance De Novo Peptide Sequencing	Dec 18, 2023	Contrastive Learningde novo peptide sequencing	CodeCode Available	1
Frequency Spectrum is More Effective for Multimodal Representation and Fusion: A Multimodal Spectrum Rumor Detector	Dec 18, 2023	Contrastive Learning	CodeCode Available	1
Generalized Category Discovery with Large Language Models in the Loop	Dec 18, 2023	Active LearningContrastive Learning	CodeCode Available	1
SeGA: Preference-Aware Self-Contrastive Learning with Prompts for Anomalous User Detection on Twitter	Dec 17, 2023	Contrastive LearningMisinformation	CodeCode Available	1
Rethinking Dimensional Rationale in Graph Contrastive Learning from Causal Perspective	Dec 16, 2023	Contrastive LearningMeta-Learning	CodeCode Available	1
CETN: Contrast-enhanced Through Network for CTR Prediction	Dec 15, 2023	Click-Through Rate PredictionContrastive Learning	CodeCode Available	1
Multi-Modality is All You Need for Transferable Recommender Systems	Dec 15, 2023	AllContrastive Learning	CodeCode Available	1
Stethoscope-guided Supervised Contrastive Learning for Cross-domain Adaptation on Respiratory Sound Classification	Dec 15, 2023	Audio ClassificationContrastive Learning	CodeCode Available	1
CLIP-guided Federated Learning on Heterogeneous and Long-Tailed Data	Dec 14, 2023	Contrastive LearningFederated Learning	CodeCode Available	1
Patch-wise Graph Contrastive Learning for Image Translation	Dec 13, 2023	Contrastive LearningGraph Neural Network	CodeCode Available	1
Toward Real Text Manipulation Detection: New Dataset and New Solution	Dec 12, 2023	Contrastive Learning	CodeCode Available	1
Transformer-based No-Reference Image Quality Assessment via Supervised Contrastive Learning	Dec 12, 2023	Contrastive LearningImage Quality Assessment	CodeCode Available	1
Hallucination Augmented Contrastive Learning for Multimodal Large Language Model	Dec 12, 2023	Contrastive LearningHallucination	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