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 1971–1980 of 6661 papers

Title	Date	Tasks	Status	Score
Discriminative Representation learning via Attention-Enhanced Contrastive Learning for Short Text Clustering	Jan 7, 2025	ClusteringContrastive Learning	CodeCode Available	5
MOOSS: Mask-Enhanced Temporal Contrastive Learning for Smooth State Evolution in Visual Reinforcement Learning	Sep 2, 2024	Contrastive Learninggraph construction	CodeCode Available	5
Morality is Non-Binary: Building a Pluralist Moral Sentence Embedding Space using Contrastive Learning	Jan 30, 2024	Contrastive LearningEthics	CodeCode Available	5
COCO-OLAC: A Benchmark for Occluded Panoptic Segmentation and Image Understanding	Sep 19, 2024	Contrastive LearningPanoptic Segmentation	CodeCode Available	5
MSCDA: Multi-level Semantic-guided Contrast Improves Unsupervised Domain Adaptation for Breast MRI Segmentation in Small Datasets	Jan 4, 2023	Contrastive LearningDomain Adaptation	CodeCode Available	5
Molecular Graph Contrastive Learning with Line Graph	Jan 15, 2025	AttributeContrastive Learning	CodeCode Available	5
Discovering Global False Negatives On the Fly for Self-supervised Contrastive Learning	Feb 28, 2025	Contrastive Learning	CodeCode Available	5
MolPLA: A Molecular Pretraining Framework for Learning Cores, R-Groups and their Linker Joints	Jan 30, 2024	Contrastive LearningMolecular Property Prediction	CodeCode Available	5
MoMA: Momentum Contrastive Learning with Multi-head Attention-based Knowledge Distillation for Histopathology Image Analysis	Aug 31, 2023	Contrastive LearningKnowledge Distillation	CodeCode Available	5
Supervised Contrastive Learning for Detecting Anomalous Driving Behaviours from Multimodal Videos	Sep 9, 2021	Anomaly DetectionContrastive Learning	CodeCode Available	5

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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