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 991–1000 of 6661 papers

Title	Date	Tasks	Status	Hype
MA-GCL: Model Augmentation Tricks for Graph Contrastive Learning	Dec 14, 2022	Contrastive LearningData Augmentation	CodeCode Available	1
Understanding Zero-Shot Adversarial Robustness for Large-Scale Models	Dec 14, 2022	Adversarial RobustnessContrastive Learning	CodeCode Available	1
On the Evolution of (Hateful) Memes by Means of Multimodal Contrastive Learning	Dec 13, 2022	Contrastive Learning	CodeCode Available	1
Masked autoencoders are effective solution to transformer data-hungry	Dec 12, 2022	Contrastive LearningInductive Bias	CodeCode Available	1
ALSO: Automotive Lidar Self-supervision by Occupancy estimation	Dec 12, 2022	Autonomous DrivingContrastive Learning	CodeCode Available	1
YoloCurvSeg: You Only Label One Noisy Skeleton for Vessel-style Curvilinear Structure Segmentation	Dec 11, 2022	Contrastive LearningImage Generation	CodeCode Available	1
Untargeted Attack against Federated Recommendation Systems via Poisonous Item Embeddings and the Defense	Dec 11, 2022	Contrastive LearningRecommendation Systems	CodeCode Available	1
Transductive Linear Probing: A Novel Framework for Few-Shot Node Classification	Dec 11, 2022	ClassificationContrastive Learning	CodeCode Available	1
Open Vocabulary Semantic Segmentation with Patch Aligned Contrastive Learning	Dec 9, 2022	Contrastive Learningimage-classification	CodeCode Available	1
Generating and Weighting Semantically Consistent Sample Pairs for Ultrasound Contrastive Learning	Dec 8, 2022	Cancer ClassificationContrastive Learning	CodeCode Available	1

Show:10 25 50

← PrevPage 100 of 667Next →

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