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 1831–1840 of 6661 papers

Title	Date	Tasks	Status	Hype	Score
Detect Rumors in Microblog Posts for Low-Resource Domains via Adversarial Contrastive Learning	Apr 18, 2022	Contrastive Learning	CodeCode Available	1	5
A Unified Framework for Microscopy Defocus Deblur with Multi-Pyramid Transformer and Contrastive Learning	Mar 5, 2024	Contrastive LearningTransfer Learning	CodeCode Available	1	5
DICNet: Deep Instance-Level Contrastive Network for Double Incomplete Multi-View Multi-Label Classification	Mar 15, 2023	Contrastive LearningMissing Labels	CodeCode Available	1	5
MoCo-CXR: MoCo Pretraining Improves Representation and Transferability of Chest X-ray Models	Oct 11, 2020	Contrastive Learningimage-classification	CodeCode Available	1	5
Low-rank Prompt Interaction for Continual Vision-Language Retrieval	Jan 24, 2025	Continual LearningContrastive Learning	CodeCode Available	1	5
UniVSE: Robust Visual Semantic Embeddings via Structured Semantic Representations	Apr 11, 2019	Contrastive LearningCross-Modal Retrieval	CodeCode Available	1	5
Low-Rank Similarity Mining for Multimodal Dataset Distillation	Jun 6, 2024	Contrastive LearningDataset Distillation	CodeCode Available	1	5
Low-resource Neural Machine Translation with Cross-modal Alignment	Oct 13, 2022	Contrastive Learningcross-modal alignment	CodeCode Available	1	5
Modeling Discriminative Representations for Out-of-Domain Detection with Supervised Contrastive Learning	May 29, 2021	Contrastive LearningOut of Distribution (OOD) Detection	CodeCode Available	1	5
Molecular Contrastive Learning of Representations via Graph Neural Networks	Feb 19, 2021	BIG-bench Machine LearningContrastive Learning	CodeCode Available	1	5

Show:10 25 50

← PrevPage 184 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