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 791–800 of 6661 papers

Title	Date	Tasks	Status	Hype	Score
CETN: Contrast-enhanced Through Network for CTR Prediction	Dec 15, 2023	Click-Through Rate PredictionContrastive Learning	CodeCode Available	1	5
ArtNeRF: A Stylized Neural Field for 3D-Aware Cartoonized Face Synthesis	Apr 21, 2024	3D-Aware Image SynthesisContrastive Learning	CodeCode Available	1	5
Adversarial Training of Self-supervised Monocular Depth Estimation against Physical-World Attacks	Jan 31, 2023	Adversarial RobustnessAutonomous Driving	CodeCode Available	1	5
Contrastive Prototypical Network with Wasserstein Confidence Penalty	Oct 21, 2022	Contrastive LearningFew-Shot Learning	CodeCode Available	1	5
ASCON: Anatomy-aware Supervised Contrastive Learning Framework for Low-dose CT Denoising	Jul 23, 2023	AnatomyComputed Tomography (CT)	CodeCode Available	1	5
Contrastive Representation Distillation	Oct 23, 2019	Contrastive LearningKnowledge Distillation	CodeCode Available	1	5
Co^2L: Contrastive Continual Learning	Jun 28, 2021	Continual LearningContrastive Learning	CodeCode Available	1	5
Contrastive Quantization with Code Memory for Unsupervised Image Retrieval	Sep 11, 2021	Contrastive LearningDeep Hashing	CodeCode Available	1	5
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
CODE: Contrastive Pre-training with Adversarial Fine-tuning for Zero-shot Expert Linking	Dec 14, 2020	Active LearningContrastive Learning	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