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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2751–2800 of 6661 papers

TitleStatusHype
FISHing in Uncertainty: Synthetic Contrastive Learning for Genetic Aberration DetectionCode0
How to Bridge Spatial and Temporal Heterogeneity in Link Prediction? A Contrastive Method—0
Metric Learning for 3D Point Clouds Using Optimal Transport—0
Towards Cross-Modal Text-Molecule Retrieval with Better Modality AlignmentCode0
JEMA: A Joint Embedding Framework for Scalable Co-Learning with Multimodal Alignment—0
Topology-Aware Graph Augmentation for Predicting Clinical Trajectories in Neurocognitive Disorders—0
Multi-modal Spatial Clustering for Spatial Transcriptomics Utilizing High-resolution Histology Images—0
BioNCERE: Non-Contrastive Enhancement For Relation Extraction In Biomedical Texts—0
Dual Contrastive Transformer for Hierarchical Preference Modeling in Sequential Recommendation—0
DOA-Aware Audio-Visual Self-Supervised Learning for Sound Event Localization and Detection—0
PARDON: Privacy-Aware and Robust Federated Domain GeneralizationCode0
Contrastive Learning and Adversarial Disentanglement for Task-Oriented Semantic CommunicationsCode0
Dataset Awareness is not Enough: Implementing Sample-level Tail Encouragement in Long-tailed Self-supervised Learning—0
Higher-order Cross-structural Embedding Model for Time Series Analysis—0
Revisiting Multi-Granularity Representation via Group Contrastive Learning for Unsupervised Vehicle Re-identification—0
A Fresh Look at Generalized Category Discovery through Non-negative Matrix Factorization—0
Unsupervised Multimodal Fusion of In-process Sensor Data for Advanced Manufacturing Process Monitoring—0
Emotion-Guided Image to Music Generation—0
Relation-based Counterfactual Data Augmentation and Contrastive Learning for Robustifying Natural Language Inference Models—0
Breccia and basalt classification of thin sections of Apollo rocks with deep learningCode0
Fidelity-Imposed Displacement Editing for the Learn2Reg 2024 SHG-BF Challenge—0
PepDoRA: A Unified Peptide Language Model via Weight-Decomposed Low-Rank Adaptation—0
Beyond Positive History: Re-ranking with List-level Hybrid Feedback—0
Enhancing CTR Prediction in Recommendation Domain with Search Query Representation—0
Prototypical Extreme Multi-label Classification with a Dynamic Margin Loss—0
ANOMIX: A Simple yet Effective Hard Negative Generation via Mixing for Graph Anomaly DetectionCode0
Uncovering Capabilities of Model Pruning in Graph Contrastive Learning—0
Idempotent Unsupervised Representation Learning for Skeleton-Based Action RecognitionCode0
Few-shot Open Relation Extraction with Gaussian Prototype and Adaptive Margin—0
Accelerating Augmentation Invariance Pretraining—0
CLOUDSPAM: Contrastive Learning On Unlabeled Data for Segmentation and Pre-Training Using Aggregated Point Clouds and MoCoCode0
MatExpert: Decomposing Materials Discovery by Mimicking Human Experts—0
Pseudo-Label Enhanced Prototypical Contrastive Learning for Uniformed Intent DiscoveryCode0
Human-Object Interaction Detection Collaborated with Large Relation-driven Diffusion Models—0
CLAP. I. Resolving miscalibration for deep learning-based galaxy photometric redshift estimationCode0
ShifCon: Enhancing Non-Dominant Language Capabilities with a Shift-based Contrastive FrameworkCode0
A contrastive-learning approach for auditory attention detection—0
Enhancing pretraining efficiency for medical image segmentation via transferability metricsCode0
Double Banking on Knowledge: Customized Modulation and Prototypes for Multi-Modality Semi-supervised Medical Image Segmentation—0
SRA: A Novel Method to Improve Feature Embedding in Self-supervised Learning for Histopathological Images—0
FairDgcl: Fairness-aware Recommendation with Dynamic Graph Contrastive LearningCode0
Rethinking Positive Pairs in Contrastive Learning—0
EntityCLIP: Entity-Centric Image-Text Matching via Multimodal Attentive Contrastive Learning—0
Enhancing Multimodal Medical Image Classification using Cross-Graph Modal Contrastive LearningCode0
Time and Frequency Synergy for Source-Free Time-Series Domain Adaptations—0
Bridging the Modality Gap: Dimension Information Alignment and Sparse Spatial Constraint for Image-Text Matching—0
Unsupervised Time Series Anomaly Prediction with Importance-based Generative Contrastive Learning—0
Prototype and Instance Contrastive Learning for Unsupervised Domain Adaptation in Speaker Verification—0
EPContrast: Effective Point-level Contrastive Learning for Large-scale Point Cloud Understanding—0
SigCLR: Sigmoid Contrastive Learning of Visual Representations—0
Show:102550
← PrevPage 56 of 134Next →
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