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 5651–5675 of 6661 papers

Title	Date	Tasks	Status	Hype
Self-Supervised Learning Disentangled Group Representation as Feature	Oct 28, 2021	ColorizationContrastive Learning	CodeCode Available	1
SCALP -- Supervised Contrastive Learning for Cardiopulmonary Disease Classification and Localization in Chest X-rays using Patient Metadata	Oct 27, 2021	Contrastive LearningData Augmentation	—Unverified	0
NIDA-CLIFGAN: Natural Infrastructure Damage Assessment through Efficient Classification Combining Contrastive Learning, Information Fusion and Generative Adversarial Networks	Oct 27, 2021	Computational EfficiencyContrastive Learning	—Unverified	0
Robust Contrastive Learning Using Negative Samples with Diminished Semantics	Oct 27, 2021	Contrastive LearningData Augmentation	CodeCode Available	1
GenURL: A General Framework for Unsupervised Representation Learning	Oct 27, 2021	Contrastive LearningDimensionality Reduction	—Unverified	0
An Explicit-Joint and Supervised-Contrastive Learning Framework for Few-Shot Intent Classification and Slot Filling	Oct 26, 2021	Contrastive Learningintent-classification	—Unverified	0
Deeper-GXX: Deepening Arbitrary GNNs	Oct 26, 2021	Contrastive LearningLink Prediction	—Unverified	0
Towards More Generalizable One-shot Visual Imitation Learning	Oct 26, 2021	Contrastive LearningImitation Learning	—Unverified	0
Contrastive Learning for Neural Topic Model	Oct 25, 2021	Contrastive Learningmodel	CodeCode Available	1
Image Quality Assessment using Contrastive Learning	Oct 25, 2021	Contrastive LearningImage Quality Assessment	CodeCode Available	1
CLLD: Contrastive Learning with Label Distance for Text Classification	Oct 25, 2021	ClassificationContrastive Learning	—Unverified	0
Contrastive Neural Processes for Self-Supervised Learning	Oct 24, 2021	Contrastive LearningData Augmentation	CodeCode Available	1
Multi-view Contrastive Graph Clustering	Oct 22, 2021	ClusteringContrastive Learning	CodeCode Available	1
CLOOB: Modern Hopfield Networks with InfoLOOB Outperform CLIP	Oct 21, 2021	Contrastive LearningSelf-Supervised Learning	CodeCode Available	1
No One Representation to Rule Them All: Overlapping Features of Training Methods	Oct 20, 2021	AllContrastive Learning	—Unverified	0
VLDeformer: Vision-Language Decomposed Transformer for Fast Cross-Modal Retrieval	Oct 20, 2021	Contrastive LearningCross-Modal Retrieval	—Unverified	0
Text-Based Person Search with Limited Data	Oct 20, 2021	BenchmarkingContrastive Learning	CodeCode Available	1
Empowering General-purpose User Representation with Full-life Cycle Behavior Modeling	Oct 20, 2021	Contrastive LearningDimensionality Reduction	—Unverified	0
Contrastive Document Representation Learning with Graph Attention Networks	Oct 20, 2021	Contrastive LearningDocument Classification	—Unverified	0
Improving Tail-Class Representation with Centroid Contrastive Learning	Oct 19, 2021	Contrastive Learningimage-classification	—Unverified	0
Momentum Contrastive Autoencoder: Using Contrastive Learning for Latent Space Distribution Matching in WAE	Oct 19, 2021	Contrastive LearningRepresentation Learning	—Unverified	0
Understanding Dimensional Collapse in Contrastive Self-supervised Learning	Oct 18, 2021	Contrastive LearningLearning Theory	CodeCode Available	1
Contrastive Learning of Visual-Semantic Embeddings	Oct 17, 2021	Contrastive Learningimage-classification	—Unverified	0
Exploring the Impact of Negative Samples of Contrastive Learning: A Case Study of Sentence Embedding	Oct 16, 2021	Contrastive LearningSentence	—Unverified	0
CONTaiNER: Few-Shot Named Entity Recognition via Contrastive Learning	Oct 16, 2021	Contrastive LearningFew-shot NER	—Unverified	0

Show:10 25 50

← PrevPage 227 of 267Next →

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