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 1026–1050 of 6661 papers

Title	Date	Tasks	Status	Hype	Score
FiGURe: Simple and Efficient Unsupervised Node Representations with Filter Augmentations	Oct 3, 2023	Contrastive Learning	CodeCode Available	1	5
Few-Shot Intent Detection via Contrastive Pre-Training and Fine-Tuning	Sep 13, 2021	Contrastive LearningIntent Detection	CodeCode Available	1	5
Contrastive Code Representation Learning	Jul 9, 2020	Clone DetectionContrastive Learning	CodeCode Available	1	5
Filtering, Distillation, and Hard Negatives for Vision-Language Pre-Training	Jan 5, 2023	Contrastive LearningText Spotting	CodeCode Available	1	5
Contrastive Collaborative Filtering for Cold-Start Item Recommendation	Feb 4, 2023	Collaborative FilteringContrastive Learning	CodeCode Available	1	5
Balanced Contrastive Learning for Long-Tailed Visual Recognition	Jul 19, 2022	Contrastive LearningImage Classification	CodeCode Available	1	5
Contrastive Denoising Score for Text-guided Latent Diffusion Image Editing	Nov 30, 2023	Contrastive LearningDenoising	CodeCode Available	1	5
A Brain Graph Foundation Model: Pre-Training and Prompt-Tuning for Any Atlas and Disorder	May 31, 2025	Contrastive LearningMeta-Learning	CodeCode Available	1	5
Contrastive Bayesian Analysis for Deep Metric Learning	Oct 10, 2022	Contrastive LearningMetric Learning	CodeCode Available	1	5
Few-shot Action Recognition with Prototype-centered Attentive Learning	Jan 20, 2021	Action RecognitionContrastive Learning	CodeCode Available	1	5
Finding Meaning in Points: Weakly Supervised Semantic Segmentation for Event Cameras	Jul 15, 2024	Contrastive LearningSegmentation	CodeCode Available	1	5
Contrasting Intra-Modal and Ranking Cross-Modal Hard Negatives to Enhance Visio-Linguistic Compositional Understanding	Jun 15, 2023	Contrastive Learningimage-classification	CodeCode Available	1	5
Bag of Instances Aggregation Boosts Self-supervised Distillation	Jul 4, 2021	Contrastive LearningLinear evaluation	CodeCode Available	1	5
FedIIC: Towards Robust Federated Learning for Class-Imbalanced Medical Image Classification	Jun 28, 2022	Contrastive LearningFederated Learning	CodeCode Available	1	5
BadHash: Invisible Backdoor Attacks against Deep Hashing with Clean Label	Jul 1, 2022	Adversarial AttackBackdoor Attack	CodeCode Available	1	5
BadCLIP: Dual-Embedding Guided Backdoor Attack on Multimodal Contrastive Learning	Nov 20, 2023	Backdoor AttackContrastive Learning	CodeCode Available	1	5
FedHCDR: Federated Cross-Domain Recommendation with Hypergraph Signal Decoupling	Mar 5, 2024	Contrastive LearningData Augmentation	CodeCode Available	1	5
CONTRASTE: Supervised Contrastive Pre-training With Aspect-based Prompts For Aspect Sentiment Triplet Extraction	Oct 24, 2023	Aspect Sentiment Triplet ExtractionAspect Term Extraction and Sentiment Classification	CodeCode Available	1	5
Contrast Everything: A Hierarchical Contrastive Framework for Medical Time-Series	Oct 21, 2023	Contrastive LearningEEG	CodeCode Available	1	5
Contrasting with Symile: Simple Model-Agnostic Representation Learning for Unlimited Modalities	Nov 1, 2024	Contrastive LearningRepresentation Learning	CodeCode Available	1	5
ContrastCAD: Contrastive Learning-based Representation Learning for Computer-Aided Design Models	Apr 2, 2024	Contrastive LearningData Augmentation	CodeCode Available	1	5
FLIP: Fine-grained Alignment between ID-based Models and Pretrained Language Models for CTR Prediction	Oct 30, 2023	Click-Through Rate PredictionContrastive Learning	CodeCode Available	1	5
FedACK: Federated Adversarial Contrastive Knowledge Distillation for Cross-Lingual and Cross-Model Social Bot Detection	Mar 10, 2023	Contrastive LearningKnowledge Distillation	CodeCode Available	1	5
FedX: Unsupervised Federated Learning with Cross Knowledge Distillation	Jul 19, 2022	Contrastive LearningFederated Learning	CodeCode Available	1	5
Adaptive Graph Contrastive Learning for Recommendation	May 18, 2023	Collaborative FilteringContrastive Learning	CodeCode Available	1	5

Show:10 25 50

← PrevPage 42 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