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 5176–5200 of 6661 papers

Title	Date	Tasks	Status	Hype
Temporal Abstractions-Augmented Temporally Contrastive Learning: An Alternative to the Laplacian in RL	Mar 21, 2022	continuous-controlContinuous Control	—Unverified	0
Language modeling via stochastic processes	Mar 21, 2022	Contrastive LearningLanguage Modeling	CodeCode Available	1
Revisiting Domain Generalized Stereo Matching Networks from a Feature Consistency Perspective	Mar 21, 2022	Contrastive LearningStereo Matching	CodeCode Available	1
Partitioning Image Representation in Contrastive Learning	Mar 20, 2022	Contrastive LearningData Augmentation	—Unverified	0
SimAN: Exploring Self-Supervised Representation Learning of Scene Text via Similarity-Aware Normalization	Mar 20, 2022	Common Sense ReasoningContrastive Learning	CodeCode Available	1
Multi-view Multi-behavior Contrastive Learning in Recommendation	Mar 20, 2022	Contrastive Learning	CodeCode Available	1
Prototypical Verbalizer for Prompt-based Few-shot Tuning	Mar 18, 2022	Contrastive LearningEntity Typing	CodeCode Available	4
Contrastive Learning with Positive-Negative Frame Mask for Music Representation	Mar 17, 2022	Contrastive LearningCover song identification	—Unverified	0
Mixing Up Contrastive Learning: Self-Supervised Representation Learning for Time Series	Mar 17, 2022	Contrastive LearningData Augmentation	CodeCode Available	1
CYBORGS: Contrastively Bootstrapping Object Representations by Grounding in Segmentation	Mar 17, 2022	Contrastive LearningObject	CodeCode Available	0
Modulated Contrast for Versatile Image Synthesis	Mar 17, 2022	Contrastive LearningImage Generation	CodeCode Available	1
PLANET: Dynamic Content Planning in Autoregressive Transformers for Long-form Text Generation	Mar 17, 2022	Contrastive LearningDecoder	—Unverified	0
Contrastive Learning for Cross-Domain Open World Recognition	Mar 17, 2022	Contrastive Learning	CodeCode Available	1
Robustness through Cognitive Dissociation Mitigation in Contrastive Adversarial Training	Mar 16, 2022	Adversarial RobustnessClassification	CodeCode Available	0
Weak Augmentation Guided Relational Self-Supervised Learning	Mar 16, 2022	Contrastive LearningRelation	CodeCode Available	1
QS-Attn: Query-Selected Attention for Contrastive Learning in I2I Translation	Mar 16, 2022	Contrastive LearningTranslation	CodeCode Available	1
Is it all a cluster game? -- Exploring Out-of-Distribution Detection based on Clustering in the Embedding Space	Mar 16, 2022	AllContrastive Learning	—Unverified	0
Multi-View Dreaming: Multi-View World Model with Contrastive Learning	Mar 15, 2022	Contrastive Learningreinforcement-learning	—Unverified	0
Better Quality Estimation for Low Resource Corpus Mining	Mar 15, 2022	Contrastive LearningData Augmentation	—Unverified	0
Improving Word Translation via Two-Stage Contrastive Learning	Mar 15, 2022	Bilingual Lexicon InductionContrastive Learning	CodeCode Available	1
InsCon:Instance Consistency Feature Representation via Self-Supervised Learning	Mar 15, 2022	Contrastive Learningimage-classification	—Unverified	0
Unpaired Deep Image Dehazing Using Contrastive Disentanglement Learning	Mar 15, 2022	Contrastive LearningDisentanglement	—Unverified	0
Contrastive Learning of Sociopragmatic Meaning in Social Media	Mar 15, 2022	Contrastive Learning	CodeCode Available	0
Supervised Contrastive Learning with Structure Inference for Graph Classification	Mar 15, 2022	ClassificationContrastive Learning	—Unverified	0
Imputing Out-of-Vocabulary Embeddings with LOVE Makes Language Models Robust with Little Cost	Mar 15, 2022	Contrastive LearningLanguage Modeling	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