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 461–470 of 6661 papers

Title	Date	Tasks	Status	Hype
CSGCL: Community-Strength-Enhanced Graph Contrastive Learning	May 8, 2023	AttributeContrastive Learning	CodeCode Available	1
CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances	Jul 16, 2020	Anomaly DetectionContrastive Learning	CodeCode Available	1
Context-self contrastive pretraining for crop type semantic segmentation	Apr 9, 2021	Contrastive LearningSegmentation	CodeCode Available	1
CURL: Contrastive Unsupervised Representations for Reinforcement Learning	Apr 8, 2020	Atari GamesAtari Games 100k	CodeCode Available	1
AIRCHITECT v2: Learning the Hardware Accelerator Design Space through Unified Representations	Jan 17, 2025	Contrastive LearningNavigate	CodeCode Available	1
BCE-Net: Reliable Building Footprints Change Extraction based on Historical Map and Up-to-Date Images using Contrastive Learning	Apr 14, 2023	Change DetectionContrastive Learning	CodeCode Available	1
ACTION++: Improving Semi-supervised Medical Image Segmentation with Adaptive Anatomical Contrast	Apr 5, 2023	Contrastive LearningImage Segmentation	CodeCode Available	1
DACAD: Domain Adaptation Contrastive Learning for Anomaly Detection in Multivariate Time Series	Apr 17, 2024	Anomaly DetectionContrastive Learning	CodeCode Available	1
Data Augmenting Contrastive Learning of Speech Representations in the Time Domain	Jul 2, 2020	Contrastive LearningData Augmentation	CodeCode Available	1
A class-weighted supervised contrastive learning long-tailed bearing fault diagnosis approach using quadratic neural network	Sep 21, 2023	Contrastive LearningData Augmentation	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