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 831–840 of 6661 papers

Title	Date	Tasks	Status	Hype	Score
BCE-Net: Reliable Building Footprints Change Extraction based on Historical Map and Up-to-Date Images using Contrastive Learning	Apr 14, 2023	Change DetectionContrastive Learning	CodeCode Available	1	5
CoLA: Weakly-Supervised Temporal Action Localization with Snippet Contrastive Learning	Mar 30, 2021	Action LocalizationCoLA	CodeCode Available	1	5
A Simple Contrastive Learning Objective for Alleviating Neural Text Degeneration	May 5, 2022	Contrastive LearningDialogue Generation	CodeCode Available	1	5
DTCLMapper: Dual Temporal Consistent Learning for Vectorized HD Map Construction	May 9, 2024	Contrastive LearningScene Understanding	CodeCode Available	1	5
A simple, efficient and scalable contrastive masked autoencoder for learning visual representations	Oct 30, 2022	Contrastive LearningSelf-Supervised Learning	CodeCode Available	1	5
CLAMP-ViT: Contrastive Data-Free Learning for Adaptive Post-Training Quantization of ViTs	Jul 7, 2024	Contrastive Learningobject-detection	CodeCode Available	1	5
A Broad Study on the Transferability of Visual Representations with Contrastive Learning	Mar 24, 2021	Contrastive LearningLinear evaluation	CodeCode Available	1	5
CLAP: Isolating Content from Style through Contrastive Learning with Augmented Prompts	Nov 28, 2023	Contrastive LearningData Augmentation	CodeCode Available	1	5
Cross-Domain Sentiment Classification with Contrastive Learning and Mutual Information Maximization	Oct 30, 2020	Contrastive LearningGeneral Classification	CodeCode Available	1	5
DRIM: Learning Disentangled Representations from Incomplete Multimodal Healthcare Data	Sep 25, 2024	Contrastive LearningPrognosis	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