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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

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Showing 1051–1100 of 6661 papers

TitleStatusHype
Position-Aware Subgraph Neural Networks with Data-Efficient LearningCode1
A picture of the space of typical learnable tasksCode1
A simple, efficient and scalable contrastive masked autoencoder for learning visual representationsCode1
Speaker Representation Learning via Contrastive Loss with Maximal Speaker SeparabilityCode1
Differentiable Data Augmentation for Contrastive Sentence Representation LearningCode1
DisenPOI: Disentangling Sequential and Geographical Influence for Point-of-Interest RecommendationCode1
cRedAnno+: Annotation Exploitation in Self-Explanatory Lung Nodule DiagnosisCode1
Robust Data2vec: Noise-robust Speech Representation Learning for ASR by Combining Regression and Improved Contrastive LearningCode1
Pretraining Respiratory Sound Representations using Metadata and Contrastive LearningCode1
Broken Neural Scaling LawsCode1
Boosting Semi-Supervised Semantic Segmentation with Probabilistic RepresentationsCode1
IMU2CLIP: Multimodal Contrastive Learning for IMU Motion Sensors from Egocentric Videos and TextCode1
MABEL: Attenuating Gender Bias using Textual Entailment DataCode1
Unsupervised Anomaly Detection for Auditing Data and Impact of Categorical EncodingsCode1
Contrastive Representation Learning for Gaze EstimationCode1
Rethinking Rotation in Self-Supervised Contrastive Learning: Adaptive Positive or Negative Data AugmentationCode1
Neural Eigenfunctions Are Structured Representation LearnersCode1
Bootstrapping meaning through listening: Unsupervised learning of spoken sentence embeddingsCode1
Contrastive Prototypical Network with Wasserstein Confidence PenaltyCode1
Exploring Representation-Level Augmentation for Code SearchCode1
Twin Contrastive Learning for Online ClusteringCode1
Does Learning from Decentralized Non-IID Unlabeled Data Benefit from Self Supervision?Code1
SSiT: Saliency-guided Self-supervised Image Transformer for Diabetic Retinopathy GradingCode1
Learning from the Dictionary: Heterogeneous Knowledge Guided Fine-tuning for Chinese Spell CheckingCode1
DyTed: Disentangled Representation Learning for Discrete-time Dynamic GraphCode1
Sentiment-Aware Word and Sentence Level Pre-training for Sentiment AnalysisCode1
Unsupervised visualization of image datasets using contrastive learningCode1
Multiple Instance Learning via Iterative Self-Paced Supervised Contrastive LearningCode1
Unifying Graph Contrastive Learning with Flexible Contextual ScopesCode1
Supervised Prototypical Contrastive Learning for Emotion Recognition in ConversationCode1
Towards Effective Image Manipulation Detection with Proposal Contrastive LearningCode1
How Mask Matters: Towards Theoretical Understandings of Masked AutoencodersCode1
Augmented Dual-Contrastive Aggregation Learning for Unsupervised Visible-Infrared Person Re-IdentificationCode1
Fine-grained Category Discovery under Coarse-grained supervision with Hierarchical Weighted Self-contrastive LearningCode1
MICO: A Multi-alternative Contrastive Learning Framework for Commonsense Knowledge RepresentationCode1
Low-resource Neural Machine Translation with Cross-modal AlignmentCode1
Contrastive Retrospection: honing in on critical steps for rapid learning and generalization in RLCode1
Self-Attention Message Passing for Contrastive Few-Shot LearningCode1
Multi-Granularity Cross-modal Alignment for Generalized Medical Visual Representation LearningCode1
MAP: Multimodal Uncertainty-Aware Vision-Language Pre-training ModelCode1
Contrastive Trajectory Similarity Learning with Dual-Feature AttentionCode1
Adversarial Contrastive Learning for Evidence-aware Fake News Detection with Graph Neural NetworksCode1
HiCo: Hierarchical Contrastive Learning for Ultrasound Video Model PretrainingCode1
SMiLE: Schema-augmented Multi-level Contrastive Learning for Knowledge Graph Link PredictionCode1
Towards Robust Visual Question Answering: Making the Most of Biased Samples via Contrastive LearningCode1
Contrastive Bayesian Analysis for Deep Metric LearningCode1
Revisiting Self-Supervised Contrastive Learning for Facial Expression RecognitionCode1
Hierarchical Few-Shot Object Detection: Problem, Benchmark and MethodCode1
InfoCSE: Information-aggregated Contrastive Learning of Sentence EmbeddingsCode1
Augmentations in Hypergraph Contrastive Learning: Fabricated and GenerativeCode1
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All datasetsimagenet-1k10,000 People - Human Pose Recognition DataCIFAR-10STL-10

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ResNet50ImageNet Top-1 Accuracy73.6—Unverified
2ResNet50ImageNet Top-1 Accuracy73—Unverified
3ResNet50ImageNet Top-1 Accuracy71.1—Unverified
4ResNet50ImageNet Top-1 Accuracy69.3—Unverified
5ResNet50 (v2)ImageNet Top-1 Accuracy67.6—Unverified
6ResNet50 (v2)ImageNet Top-1 Accuracy63.8—Unverified
7ResNet50ImageNet Top-1 Accuracy63.6—Unverified
8ResNet50ImageNet Top-1 Accuracy61.5—Unverified
9ResNet50ImageNet Top-1 Accuracy61.5—Unverified
10ResNet50 (4×)ImageNet Top-1 Accuracy61.3—Unverified
#ModelMetricClaimedVerifiedStatus
110..5sec1—Unverified
#ModelMetricClaimedVerifiedStatus
1IPCL (ResNet18)Accuracy (Top-1)84.77—Unverified
#ModelMetricClaimedVerifiedStatus
1IPCL (ResNet18)Accuracy (Top-1)85.55—Unverified