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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 6351–6400 of 6661 papers

TitleStatusHype
Spatial Contrastive Learning for Few-Shot ClassificationCode1
Evolution Is All You Need: Phylogenetic Augmentation for Contrastive Learning—0
Self-Supervised Multimodal Domino: in Search of Biomarkers for Alzheimer's DiseaseCode0
Self-Supervised Representation Learning for Astronomical ImagesCode1
Adversarial Momentum-Contrastive Pre-TrainingCode0
P4Contrast: Contrastive Learning with Pairs of Point-Pixel Pairs for RGB-D Scene Understanding—0
Motif-Driven Contrastive Learning of Graph Representations—0
PTN: A Poisson Transfer Network for Semi-supervised Few-shot Learning—0
Sequence-to-Sequence Contrastive Learning for Text RecognitionCode1
Camera-aware Proxies for Unsupervised Person Re-IdentificationCode1
Addressing Feature Suppression in Unsupervised Visual Representations—0
ISD: Self-Supervised Learning by Iterative Similarity DistillationCode1
Joint Generative and Contrastive Learning for Unsupervised Person Re-identificationCode1
Wasserstein Contrastive Representation Distillation—0
Understanding the Behaviour of Contrastive Loss—0
CODE: Contrastive Pre-training with Adversarial Fine-tuning for Zero-shot Expert LinkingCode1
Contrastive Learning with Adversarial Perturbations for Conditional Text GenerationCode1
Rethinking the Promotion Brought by Contrastive Learning to Semi-Supervised Node Classification—0
LRC-BERT: Latent-representation Contrastive Knowledge Distillation for Natural Language Understanding—0
Contrastive Learning for Label-Efficient Semantic Segmentation—0
Contrastive Learning of Relative Position Regression for One-Shot Object Localization in 3D Medical ImagesCode1
Self-supervised Text-independent Speaker Verification using Prototypical Momentum Contrastive LearningCode1
Tactile Object Pose Estimation from the First Touch with Geometric Contact Rendering—0
Multi-Objective Interpolation Training for Robustness to Label NoiseCode1
Fine-grained Angular Contrastive Learning with Coarse LabelsCode1
Proactive Pseudo-Intervention: Causally Informed Contrastive Learning For Interpretable Vision Models—0
Cross-Domain Sentiment Classification with In-Domain Contrastive LearningCode1
SAM: Self-supervised Learning of Pixel-wise Anatomical Embeddings in Radiological ImagesCode1
Seed the Views: Hierarchical Semantic Alignment for Contrastive Representation Learning—0
Multi-Label Contrastive Learning for Abstract Visual ReasoningCode0
Learning View-Disentangled Human Pose Representation by Contrastive Cross-View Mutual Information Maximization—0
About contrastive unsupervised representation learning for classification and its convergence—0
A Risk Communication Event Detection Model via Contrastive Learning—0
Text Classification by Contrastive Learning and Cross-lingual Data Augmentation for Alzheimer's Disease Detection—0
Multi-level Knowledge Distillation via Knowledge Alignment and CorrelationCode1
Pre-Trained Image Processing TransformerCode1
Counterfactual Contrastive Learning for Weakly-Supervised Vision-Language Grounding—0
Self-Supervised Relationship Probing—0
Unsupervised Representation Learning by Invariance Propagation—0
Soft Contrastive Learning for Visual LocalizationCode1
Annotation-Efficient Untrimmed Video Action Recognition—0
PCPs: Patient Cardiac Prototypes—0
CROCS: Clustering and Retrieval of Cardiac Signals Based on Patient Disease Class, Sex, and Age—0
Time Series Change Point Detection with Self-Supervised Contrastive Predictive CodingCode1
Self supervised contrastive learning for digital histopathologyCode1
Automatic coding of students' writing via Contrastive Representation Learning in the Wasserstein space—0
USCL: Pretraining Deep Ultrasound Image Diagnosis Model through Video Contrastive Representation LearningCode1
StackMix: A complementary Mix algorithm—0
Contrastive Representation Learning for Whole Brain Cytoarchitectonic Mapping in Histological Human Brain Sections—0
Boosting Contrastive Self-Supervised Learning with False Negative CancellationCode1
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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