SOTAVerified

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 4601–4650 of 6661 papers

TitleStatusHype
Bidirectional Contrastive Split Learning for Visual Question Answering—0
Scenario-Adaptive and Self-Supervised Model for Multi-Scenario Personalized Recommendation—0
Bitext Mining for Low-Resource Languages via Contrastive LearningCode0
Efficient Self-Supervision using Patch-based Contrastive Learning for Histopathology Image SegmentationCode0
Faint Features Tell: Automatic Vertebrae Fracture Screening Assisted by Contrastive Learning—0
IMPaSh: A Novel Domain-shift Resistant Representation for Colorectal Cancer Tissue ClassificationCode0
Spiral Contrastive Learning: An Efficient 3D Representation Learning Method for Unannotated CT Lesions—0
CLOWER: A Pre-trained Language Model with Contrastive Learning over Word and Character Representations—0
Improving Knowledge-aware Recommendation with Multi-level Interactive Contrastive LearningCode1
Anatomy-Aware Contrastive Representation Learning for Fetal UltrasoundCode0
FairDisCo: Fairer AI in Dermatology via Disentanglement Contrastive LearningCode1
TaCo: Textual Attribute Recognition via Contrastive Learning—0
Patient-level Microsatellite Stability Assessment from Whole Slide Images By Combining Momentum Contrast Learning and Group Patch EmbeddingsCode0
CMSBERT-CLR: Context-driven Modality Shifting BERT with Contrastive Learning for linguistic, visual, acoustic Representations—0
GRETEL: Graph Contrastive Topic Enhanced Language Model for Long Document Extractive Summarization—0
CODER: Coupled Diversity-Sensitive Momentum Contrastive Learning for Image-Text Retrieval—0
Masked Video Modeling with Correlation-aware Contrastive Learning for Breast Cancer Diagnosis in Ultrasound—0
Fuse and Attend: Generalized Embedding Learning for Art and Sketches—0
GraphTTA: Test Time Adaptation on Graph Neural Networks—0
MvDeCor: Multi-view Dense Correspondence Learning for Fine-grained 3D SegmentationCode1
Reproducibility Report: Contrastive Learning of Socially-aware Motion RepresentationsCode1
Contrastive Semi-supervised Learning for Domain Adaptive Segmentation Across Similar Anatomical StructuresCode1
Mere Contrastive Learning for Cross-Domain Sentiment AnalysisCode1
Modeling Two-Way Selection Preference for Person-Job FitCode1
Disentangled Contrastive Learning for Social RecommendationCode0
Siamese Prototypical Contrastive Learning—0
Re4: Learning to Re-contrast, Re-attend, Re-construct for Multi-interest RecommendationCode1
SelF-Eval: Self-supervised Fine-grained Dialogue EvaluationCode0
CommitBART: A Large Pre-trained Model for GitHub Commits—0
Multi-View Correlation Consistency for Semi-Supervised Semantic Segmentation—0
CCL4Rec: Contrast over Contrastive Learning for Micro-video Recommendation—0
KRACL: Contrastive Learning with Graph Context Modeling for Sparse Knowledge Graph CompletionCode1
DICE: Data-Efficient Clinical Event Extraction with Generative Models—0
Object Discovery via Contrastive Learning for Weakly Supervised Object DetectionCode1
C3-DINO: Joint Contrastive and Non-contrastive Self-Supervised Learning for Speaker Verification—0
ARIEL: Adversarial Graph Contrastive LearningCode0
Hierarchical Attention Network for Few-Shot Object Detection via Meta-Contrastive LearningCode1
Multi-modal Siamese Network for Entity AlignmentCode1
Contrastive Learning for Joint Normal Estimation and Point Cloud FilteringCode0
Self-supervised Contrastive Representation Learning for Semi-supervised Time-Series ClassificationCode2
Enhancing Graph Contrastive Learning with Node Similarity—0
A Unified Two-Stage Group Semantics Propagation and Contrastive Learning Network for Co-Saliency Detection—0
Exploring High-quality Target Domain Information for Unsupervised Domain Adaptive Semantic SegmentationCode1
Contrastive Learning for OOD in Object detectionCode0
Contrastive Learning for Object DetectionCode0
Motion Sensitive Contrastive Learning for Self-supervised Video Representation—0
RenyiCL: Contrastive Representation Learning with Skew Renyi DivergenceCode1
Path-aware Siamese Graph Neural Network for Link PredictionCode0
Self-supervised Multi-modal Training from Uncurated Image and Reports Enables Zero-shot Oversight Artificial Intelligence in RadiologyCode0
Multi-View Pre-Trained Model for Code Vulnerability Identification—0
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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