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 4421–4430 of 6661 papers

Title	Date	Tasks	Status	Hype
Unsupervised Cross-Modality Domain Adaptation for Vestibular Schwannoma Segmentation and Koos Grade Prediction based on Semi-Supervised Contrastive Learning	Oct 9, 2022	Contrastive LearningDomain Adaptation	CodeCode Available	0
InfoCSE: Information-aggregated Contrastive Learning of Sentence Embeddings	Oct 8, 2022	Contrastive LearningLanguage Modeling	CodeCode Available	1
SDA: Simple Discrete Augmentation for Contrastive Sentence Representation Learning	Oct 8, 2022	Contrastive LearningData Augmentation	CodeCode Available	0
Hierarchical Few-Shot Object Detection: Problem, Benchmark and Method	Oct 8, 2022	Contrastive LearningFew-Shot Object Detection	CodeCode Available	1
Revisiting Self-Supervised Contrastive Learning for Facial Expression Recognition	Oct 8, 2022	Contrastive LearningFacial Expression Recognition	CodeCode Available	1
SAICL: Student Modelling with Interaction-level Auxiliary Contrastive Tasks for Knowledge Tracing and Dropout Prediction	Oct 7, 2022	Contrastive LearningData Augmentation	—Unverified	0
Zero-shot stance detection based on cross-domain feature enhancement by contrastive learning	Oct 7, 2022	Contrastive LearningStance Detection	—Unverified	0
Unsupervised Semantic Representation Learning of Scientific Literature Based on Graph Attention Mechanism and Maximum Mutual Information	Oct 7, 2022	Contrastive LearningGraph Attention	—Unverified	0
Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative	Oct 7, 2022	Contrastive LearningFairness	CodeCode Available	1
Knowledge Injected Prompt Based Fine-tuning for Multi-label Few-shot ICD Coding	Oct 7, 2022	Contrastive LearningMedical Code Prediction	CodeCode Available	1

Show:10 25 50

← PrevPage 443 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