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 631–640 of 6661 papers

Title	Date	Tasks	Status	Hype	Score
Anatomical Invariance Modeling and Semantic Alignment for Self-supervised Learning in 3D Medical Image Analysis	Feb 11, 2023	Contrastive LearningImage Segmentation	CodeCode Available	1	5
CLOOB: Modern Hopfield Networks with InfoLOOB Outperform CLIP	Oct 21, 2021	Contrastive LearningSelf-Supervised Learning	CodeCode Available	1	5
CSGCL: Community-Strength-Enhanced Graph Contrastive Learning	May 8, 2023	AttributeContrastive Learning	CodeCode Available	1	5
Black-Box Attack against GAN-Generated Image Detector with Contrastive Perturbation	Nov 7, 2022	Contrastive LearningDecoder	CodeCode Available	1	5
Towards Cross-Table Masked Pretraining for Web Data Mining	Jul 10, 2023	Contrastive Learning	CodeCode Available	1	5
Black Box Few-Shot Adaptation for Vision-Language models	Apr 4, 2023	Contrastive LearningPrompt Learning	CodeCode Available	1	5
Deep Contrastive One-Class Time Series Anomaly Detection	Jul 4, 2022	Anomaly DetectionContrastive Learning	CodeCode Available	1	5
Blind Localization and Clustering of Anomalies in Textures	Apr 18, 2024	Anomaly DetectionAnomaly Localization	CodeCode Available	1	5
Anatomy-Constrained Contrastive Learning for Synthetic Segmentation without Ground-truth	Jul 12, 2021	AnatomyContrastive Learning	CodeCode Available	1	5
Data Augmenting Contrastive Learning of Speech Representations in the Time Domain	Jul 2, 2020	Contrastive LearningData Augmentation	CodeCode Available	1	5

Show:10 25 50

← PrevPage 64 of 667Next →

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