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 1731–1740 of 6661 papers

Title	Date	Tasks	Status	Hype
Cleora: A Simple, Strong and Scalable Graph Embedding Scheme	Feb 3, 2021	Contrastive LearningCPU	CodeCode Available	1
NeMo: Neural Mesh Models of Contrastive Features for Robust 3D Pose Estimation	Jan 29, 2021	3D geometry3D Pose Estimation	CodeCode Available	1
Understanding and Achieving Efficient Robustness with Adversarial Supervised Contrastive Learning	Jan 25, 2021	Contrastive Learning	CodeCode Available	1
Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning	Jan 25, 2021	Anomaly DetectionAnomaly Detection In Surveillance Videos	CodeCode Available	1
Few-shot Action Recognition with Prototype-centered Attentive Learning	Jan 20, 2021	Action RecognitionContrastive Learning	CodeCode Available	1
TCLR: Temporal Contrastive Learning for Video Representation	Jan 20, 2021	Action ClassificationAction Recognition	CodeCode Available	1
Scaling Deep Contrastive Learning Batch Size under Memory Limited Setup	Jan 18, 2021	Contrastive LearningGPU	CodeCode Available	1
Label Contrastive Coding based Graph Neural Network for Graph Classification	Jan 14, 2021	ClassificationContrastive Learning	CodeCode Available	1
Big Self-Supervised Models Advance Medical Image Classification	Jan 13, 2021	ClassificationContrastive Learning	CodeCode Available	1
Cross-Modal Contrastive Learning for Text-to-Image Generation	Jan 12, 2021	Contrastive LearningGenerative Adversarial Network	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