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 2951–3000 of 6661 papers

TitleStatusHype
Generating Counterfactual Hard Negative Samples for Graph Contrastive Learning—0
Higher-order Cross-structural Embedding Model for Time Series Analysis—0
High-Frequency-aware Hierarchical Contrastive Selective Coding for Representation Learning on Text-attributed Graphs—0
Fusion Self-supervised Learning for Recommendation—0
Generating Compositional Color Representations from Text—0
Contrastive Learning of Emoji-based Representations for Resource-Poor Languages—0
Boundary-aware Information Maximization for Self-supervised Medical Image Segmentation—0
Joint enhancement of automatic chest X-ray diagnosis and radiological gaze prediction with multi-stage cooperative learning—0
General-Purpose Multi-Modal OOD Detection Framework—0
Generalizing Supervised Contrastive learning: A Projection Perspective—0
Contrastive Learning of Coarse-Grained Force Fields—0
Generalizing Graph ODE for Learning Complex System Dynamics across Environments—0
HNCSE: Advancing Sentence Embeddings via Hybrid Contrastive Learning with Hard Negatives—0
Hodge-Aware Contrastive Learning—0
Animate Your Thoughts: Decoupled Reconstruction of Dynamic Natural Vision from Slow Brain Activity—0
Homography augumented momentum constrastive learning for SAR image retrieval—0
BotSSCL: Social Bot Detection with Self-Supervised Contrastive Learning—0
Adults as Augmentations for Children in Facial Emotion Recognition with Contrastive Learning—0
jina-clip-v2: Multilingual Multimodal Embeddings for Text and Images—0
How do Cross-View and Cross-Modal Alignment Affect Representations in Contrastive Learning?—0
Contrastive Learning of 3D Shape Descriptor with Dynamic Adversarial Views—0
How does self-supervised pretraining improve robustness against noisy labels across various medical image classification datasets?—0
Contrastive learning, multi-view redundancy, and linear models—0
How Does SimSiam Avoid Collapse Without Negative Samples? A Unified Understanding with Self-supervised Contrastive Learning—0
Bootstrapping Your Own Positive Sample: Contrastive Learning With Electronic Health Record Data—0
Generalized Class Discovery in Instance Segmentation—0
Contrastive Learning Method for Sequential Recommendation based on Multi-Intention Disentanglement—0
How to Enhance Downstream Adversarial Robustness (almost) without Touching the Pre-Trained Foundation Model?—0
How to Make Cross Encoder a Good Teacher for Efficient Image-Text Retrieval?—0
How to Train Your DRAGON: Diverse Augmentation Towards Generalizable Dense Retrieval—0
Generalization Bounds for Adversarial Contrastive Learning—0
Generalization Beyond Feature Alignment: Concept Activation-Guided Contrastive Learning—0
Bootstrapping Vision-language Models for Self-supervised Remote Physiological Measurement—0
Human-aligned Deep Learning: Explainability, Causality, and Biological Inspiration—0
Human-Centered Prior-Guided and Task-Dependent Multi-Task Representation Learning for Action Recognition Pre-Training—0
An Image-based Approach of Task-driven Driving Scene Categorization—0
Jitter Does Matter: Adapting Gaze Estimation to New Domains—0
Jointly Learning Representations for Map Entities via Heterogeneous Graph Contrastive Learning—0
KaLM: Knowledge-aligned Autoregressive Language Modeling via Dual-view Knowledge Graph Contrastive Learning—0
Hybrid Augmented Automated Graph Contrastive Learning—0
Generalization Analysis for Deep Contrastive Representation Learning—0
Hybrid Contrastive Learning of Tri-Modal Representation for Multimodal Sentiment Analysis—0
Hybrid Contrastive Learning with Cluster Ensemble for Unsupervised Person Re-identification—0
Generalization Analysis for Contrastive Representation Learning under Non-IID Settings—0
Contrastive Learning Meets Transfer Learning: A Case Study In Medical Image Analysis—0
Generalization Analysis for Contrastive Representation Learning—0
Hybrid Dynamic Contrast and Probability Distillation for Unsupervised Person Re-Id—0
Achieving Domain Generalization in Underwater Object Detection by Domain Mixup and Contrastive Learning—0
Contrastive Learning Is Not Optimal for Quasiperiodic Time Series—0
Generalizable Low-Resource Activity Recognition with Diverse and Discriminative Representation Learning—0
Show:102550
← PrevPage 60 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