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 641–650 of 6661 papers

Title	Date	Tasks	Status	Hype	Score
Co2L: Contrastive Continual Learning	Jan 1, 2021	Continual LearningContrastive Learning	CodeCode Available	1	5
Co^2L: Contrastive Continual Learning	Jun 28, 2021	Continual LearningContrastive 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
Boosting Contrastive Self-Supervised Learning with False Negative Cancellation	Nov 23, 2020	Contrastive LearningRepresentation Learning	CodeCode Available	1	5
COARSE3D: Class-Prototypes for Contrastive Learning in Weakly-Supervised 3D Point Cloud Segmentation	Oct 4, 2022	3D Semantic SegmentationContrastive Learning	CodeCode Available	1	5
Boosting Few-Shot Classification with View-Learnable Contrastive Learning	Jul 20, 2021	ClassificationContrastive Learning	CodeCode Available	1	5
Data Augmentation-free Unsupervised Learning for 3D Point Cloud Understanding	Oct 6, 2022	3D Object ClassificationContrastive Learning	CodeCode Available	1	5
Data Poisoning based Backdoor Attacks to Contrastive Learning	Jan 1, 2024	Contrastive LearningData Poisoning	CodeCode Available	1	5
Debiased Contrastive Learning for Sequential Recommendation	Mar 21, 2023	Contrastive LearningData Augmentation	CodeCode Available	1	5
CLAD: Robust Audio Deepfake Detection Against Manipulation Attacks with Contrastive Learning	Apr 24, 2024	Audio Deepfake DetectionContrastive 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