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 5426–5450 of 6661 papers

Title	Date	Tasks	Status	Hype
Sparse and Complete Latent Organization for Geospatial Semantic Segmentation	Jan 1, 2022	Contrastive LearningSemantic Segmentation	—Unverified	0
One-Bit Active Query With Contrastive Pairs	Jan 1, 2022	Active LearningContrastive Learning	—Unverified	0
Noise Is Also Useful: Negative Correlation-Steered Latent Contrastive Learning	Jan 1, 2022	Contrastive LearningDiversity	—Unverified	0
A Hybrid Egocentric Activity Anticipation Framework via Memory-Augmented Recurrent and One-Shot Representation Forecasting	Jan 1, 2022	Contrastive Learning	—Unverified	0
Align Representations With Base: A New Approach to Self-Supervised Learning	Jan 1, 2022	Contrastive LearningSelf-Supervised Learning	—Unverified	0
Contrastive Learning for Unsupervised Video Highlight Detection	Jan 1, 2022	Contrastive LearningHighlight Detection	—Unverified	0
Representation Learning via Consistent Assignment of Views to Clusters	Dec 31, 2021	ClusteringContrastive Learning	CodeCode Available	0
Contrastive Fine-grained Class Clustering via Generative Adversarial Networks	Dec 30, 2021	ClusteringContrastive Learning	CodeCode Available	1
Contrastive Learning of Semantic and Visual Representations for Text Tracking	Dec 30, 2021	Contrastive Learning	CodeCode Available	0
Frequency-Aware Contrastive Learning for Neural Machine Translation	Dec 29, 2021	Contrastive LearningDiversity	—Unverified	0
Dual Contrastive Learning for General Face Forgery Detection	Dec 27, 2021	Contrastive Learning	—Unverified	0
Multi-Variant Consistency based Self-supervised Learning for Robust Automatic Speech Recognition	Dec 23, 2021	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified	0
Towards Universal GAN Image Detection	Dec 23, 2021	Contrastive Learning	—Unverified	0
Multi-Centroid Representation Network for Domain Adaptive Person Re-ID	Dec 22, 2021	Contrastive LearningDomain Adaptive Person Re-Identification	—Unverified	0
Looking Beyond Corners: Contrastive Learning of Visual Representations for Keypoint Detection and Description Extraction	Dec 22, 2021	Contrastive LearningKeypoint Detection	CodeCode Available	0
Augmented Contrastive Self-Supervised Learning for Audio Invariant Representations	Dec 21, 2021	Audio ClassificationClassification	—Unverified	0
Contrast and Generation Make BART a Good Dialogue Emotion Recognizer	Dec 21, 2021	Contrastive LearningDecoder	CodeCode Available	1
Max-Margin Contrastive Learning	Dec 21, 2021	Contrastive LearningRepresentation Learning	CodeCode Available	1
Supervised Graph Contrastive Pretraining for Text Classification	Dec 21, 2021	ClassificationContrastive Learning	—Unverified	0
AGPNet -- Autonomous Grading Policy Network	Dec 20, 2021	Contrastive Learningreinforcement-learning	—Unverified	0
Camera-aware Style Separation and Contrastive Learning for Unsupervised Person Re-identification	Dec 19, 2021	Contrastive LearningPerson Re-Identification	—Unverified	0
Cross-modal Contrastive Learning for Speech Translation	Dec 17, 2021	Contrastive LearningRetrieval	—Unverified	0
HiURE: Hierarchical Exemplar Contrastive Learning for Unsupervised Relation Extraction	Dec 17, 2021	ClusteringContrastive Learning	—Unverified	0
Contrastive Learning for Fair Representations	Dec 17, 2021	AttributeClassification	—Unverified	0
Contrastive Vision-Language Pre-training with Limited Resources	Dec 17, 2021	Contrastive Learning	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