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 2401–2450 of 6661 papers

TitleStatusHype
Low-confidence Samples Matter for Domain AdaptationCode0
Looking Beyond Corners: Contrastive Learning of Visual Representations for Keypoint Detection and Description ExtractionCode0
Advancing Brainwave-Based Biometrics: A Large-Scale, Multi-Session EvaluationCode0
Contrastive Learning of Semantic and Visual Representations for Text TrackingCode0
Low-Contrast-Enhanced Contrastive Learning for Semi-Supervised Endoscopic Image SegmentationCode0
Statement-Level Vulnerability Detection: Learning Vulnerability Patterns Through Information Theory and Contrastive LearningCode0
LogiCoL: Logically-Informed Contrastive Learning for Set-based Dense RetrievalCode0
Brain-Aware Replacements for Supervised Contrastive Learning in Detection of Alzheimer's DiseaseCode0
Local Aggregation for Unsupervised Learning of Visual EmbeddingsCode0
An Information Minimization Based Contrastive Learning Model for Unsupervised Sentence Embeddings LearningCode0
M3: A Multi-Task Mixed-Objective Learning Framework for Open-Domain Multi-Hop Dense Sentence RetrievalCode0
Contrastive Learning of General-Purpose Audio RepresentationsCode0
Line Graph Contrastive Learning for Link PredictionCode0
Link Prediction with Non-Contrastive LearningCode0
Lexical Knowledge Internalization for Neural Dialog GenerationCode0
CL-MRI: Self-Supervised Contrastive Learning to Improve the Accuracy of Undersampled MRI ReconstructionCode0
Leveraging Group Classification with Descending Soft Labeling for Deep Imbalanced RegressionCode0
Leveraging Unlabeled Data for 3D Medical Image Segmentation through Self-Supervised Contrastive LearningCode0
Lightweight Cross-Lingual Sentence Representation LearningCode0
M3ANet: Multi-scale and Multi-Modal Alignment Network for Brain-Assisted Target Speaker ExtractionCode0
Contrastive Learning Meets Pseudo-label-assisted Mixup Augmentation: A Comprehensive Graph Representation Framework from Local to GlobalCode0
Less is More: Multimodal Region Representation via Pairwise Inter-view LearningCode0
An Eye for an Ear: Zero-shot Audio Description Leveraging an Image Captioner using Audiovisual Distribution AlignmentCode0
Less is More: Selective Reduction of CT Data for Self-Supervised Pre-Training of Deep Learning Models with Contrastive Learning Improves Downstream Classification PerformanceCode0
Contrastive Learning in Distilled ModelsCode0
A Dual-Contrastive Framework for Low-Resource Cross-Lingual Named Entity RecognitionCode0
Less Attention is More: Prompt Transformer for Generalized Category DiscoveryCode0
Bootstrapping Informative Graph Augmentation via A Meta Learning ApproachCode0
An Experimental Comparison Of Multi-view Self-supervised Methods For Music TaggingCode0
Leave No One Behind: Online Self-Supervised Self-Distillation for Sequential RecommendationCode0
Length is a Curse and a Blessing for Document-level SemanticsCode0
Learning What You Need from What You Did: Product Taxonomy Expansion with User Behaviors SupervisionCode0
Learning with Open-world Noisy Data via Class-independent Margin in Dual Representation SpaceCode0
Lesion-Aware Contrastive Representation Learning for Histopathology Whole Slide Images AnalysisCode0
Leveraging Contrastive Learning and Self-Training for Multimodal Emotion Recognition with Limited Labeled SamplesCode0
Learning to Plan via Supervised Contrastive Learning and Strategic Interpolation: A Chess Case StudyCode0
Bootstrap Latents of Nodes and Neighbors for Graph Self-Supervised LearningCode0
Learning Transferable Pedestrian Representation from Multimodal Information SupervisionCode0
Boost-RS: Boosted Embeddings for Recommender Systems and its Application to Enzyme-Substrate Interaction PredictionCode0
Learning to Locate Visual Answer in Video Corpus Using QuestionCode0
Learning Tree-Structured Composition of Data AugmentationCode0
Contrastive Learning for Task-Independent SpeechLLM-PretrainingCode0
An Empirical Study of Accuracy-Robustness Tradeoff and Training Efficiency in Self-Supervised LearningCode0
Boosting Short Text Classification with Multi-Source Information Exploration and Dual-Level Contrastive LearningCode0
Contrastive Learning for Sleep Staging based on Inter Subject CorrelationCode0
ACE: Zero-Shot Image to Image Translation via Pretrained Auto-Contrastive-EncoderCode0
Learning the Simplicity of Scattering AmplitudesCode0
Learning Semi-Supervised Medical Image Segmentation from Spatial RegistrationCode0
Boosting Semi-Supervised Scene Text Recognition via Viewing and SummarizingCode0
An efficient framework based on large foundation model for cervical cytopathology whole slide image screeningCode0
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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