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 1531–1540 of 6661 papers

Title	Date	Tasks	Status	Hype	Score
Category Contrast for Unsupervised Domain Adaptation in Visual Tasks	Jun 5, 2021	Contrastive LearningDomain Adaptation	CodeCode Available	1	5
COPNER: Contrastive Learning with Prompt Guiding for Few-shot Named Entity Recognition	Oct 1, 2022	Contrastive Learningfew-shot-ner	CodeCode Available	1	5
Graph Contrastive Learning for Anomaly Detection	Aug 17, 2021	Anomaly DetectionBinary Classification	CodeCode Available	1	5
GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training	Jun 17, 2020	Contrastive LearningGeneral Classification	CodeCode Available	1	5
Knowledge-infused Contrastive Learning for Urban Imagery-based Socioeconomic Prediction	Feb 25, 2023	Contrastive LearningPrediction	CodeCode Available	1	5
Knowledge Injected Prompt Based Fine-tuning for Multi-label Few-shot ICD Coding	Oct 7, 2022	Contrastive LearningMedical Code Prediction	CodeCode Available	1	5
Composed Image Retrieval using Contrastive Learning and Task-oriented CLIP-based Features	Aug 22, 2023	Contrastive LearningImage Retrieval	CodeCode Available	1	5
Generalized Category Discovery with Large Language Models in the Loop	Dec 18, 2023	Active LearningContrastive Learning	CodeCode Available	1	5
Enhancing Text-based Knowledge Graph Completion with Zero-Shot Large Language Models: A Focus on Semantic Enhancement	Oct 12, 2023	Contrastive LearningData Augmentation	CodeCode Available	1	5
Language-Assisted Skeleton Action Understanding for Skeleton-Based Temporal Action Segmentation	Oct 31, 2024	Action SegmentationAction Understanding	CodeCode Available	1	5

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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