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

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Showing 1511–1520 of 6661 papers

Title	Date	Tasks	Status	Hype
Contrast, Stylize and Adapt: Unsupervised Contrastive Learning Framework for Domain Adaptive Semantic Segmentation	Jun 15, 2023	Contrastive LearningDomain Adaptation	CodeCode Available	1
Contrast then Memorize: Semantic Neighbor Retrieval-Enhanced Inductive Multimodal Knowledge Graph Completion	Jul 3, 2024	Contrastive LearningKnowledge Graph Completion	CodeCode Available	1
CoRTX: Contrastive Framework for Real-time Explanation	Mar 5, 2023	Contrastive Learning	CodeCode Available	1
ContrastVAE: Contrastive Variational AutoEncoder for Sequential Recommendation	Aug 27, 2022	Contrastive LearningRecommendation Systems	CodeCode Available	1
CARLA: Self-supervised Contrastive Representation Learning for Time Series Anomaly Detection	Aug 18, 2023	Anomaly DetectionContrastive Learning	CodeCode Available	1
Multi-level Cross-view Contrastive Learning for Knowledge-aware Recommender System	Apr 19, 2022	Contrastive LearningData Augmentation	CodeCode Available	1
Multimodal Clustering Networks for Self-supervised Learning from Unlabeled Videos	Apr 26, 2021	Action LocalizationClustering	CodeCode Available	1
Multimodal contrastive learning for spatial gene expression prediction using histology images	Jul 11, 2024	Contrastive Learningwhole slide images	CodeCode Available	1
Does Zero-Shot Reinforcement Learning Exist?	Sep 29, 2022	Contrastive Learningreinforcement-learning	CodeCode Available	1
Domain-invariant Similarity Activation Map Contrastive Learning for Retrieval-based Long-term Visual Localization	Sep 16, 2020	Autonomous DrivingContrastive Learning	CodeCode Available	1

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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