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 4501–4550 of 6661 papers

TitleStatusHype
Deep Contrastive Graph Representation via Adaptive Homotopy Learning—0
Deep Contrastive Learning for Feature Alignment: Insights from Housing-Household Relationship Inference—0
Deep Contrastive Multiview Network Embedding—0
Understanding Deep Contrastive Learning via Coordinate-wise Optimization—0
Deep Contrastive Multi-view Clustering under Semantic Feature Guidance—0
DeepfakeUCL: Deepfake Detection via Unsupervised Contrastive Learning—0
Deep Fraud Detection on Non-attributed Graph—0
DeepGATGO: A Hierarchical Pretraining-Based Graph-Attention Model for Automatic Protein Function Prediction—0
Deep Graph Clustering via Mutual Information Maximization and Mixture Model—0
Deep Incomplete Multi-view Clustering with Cross-view Partial Sample and Prototype Alignment—0
Statistically-informed deep learning for gravitational wave parameter estimation—0
Deep-learning-based clustering of OCT images for biomarker discovery in age-related macular degeneration (Pinnacle study report 4)—0
Deep Learning-Based Identification of Inconsistent Method Names: How Far Are We?—0
Deep learning-based UAV detection in the low altitude clutter background—0
Deep Learning for Cross-Border Transaction Anomaly Detection in Anti-Money Laundering Systems—0
Deep Learning to Predict Glaucoma Progression using Structural Changes in the Eye—0
Deep Pneumonia: Attention-Based Contrastive Learning for Class-Imbalanced Pneumonia Lesion Recognition in Chest X-rays—0
DeepQR: Neural-based Quality Ratings for Learnersourced Multiple-Choice Questions—0
DeepRGVP: A Novel Microstructure-Informed Supervised Contrastive Learning Framework for Automated Identification Of The Retinogeniculate Pathway Using dMRI Tractography—0
DeepRicci: Self-supervised Graph Structure-Feature Co-Refinement for Alleviating Over-squashing—0
Deep Submodular Peripteral Networks—0
DEEPTalk: Dynamic Emotion Embedding for Probabilistic Speech-Driven 3D Face Animation—0
Deep Temporal Contrastive Clustering—0
Deep Variational Multivariate Information Bottleneck -- A Framework for Variational Losses—0
Defending Multimodal Backdoored Models by Repulsive Visual Prompt Tuning—0
DEHRFormer: Real-time Transformer for Depth Estimation and Haze Removal from Varicolored Haze Scenes—0
Delving into E-Commerce Product Retrieval with Vision-Language Pre-training—0
Del Visual al Auditivo: Sonorización de Escenas Guiada por Imagen—0
Denoising Long- and Short-term Interests for Sequential Recommendation—0
Denoising Multi-modal Sequential Recommenders with Contrastive Learning—0
Dense Contrastive Visual-Linguistic Pretraining—0
Dense Semantic Contrast for Self-Supervised Visual Representation Learning—0
Density-Guided Semi-Supervised 3D Semantic Segmentation with Dual-Space Hardness Sampling—0
Depth-CUPRL: Depth-Imaged Contrastive Unsupervised Prioritized Representations in Reinforcement Learning for Mapless Navigation of Unmanned Aerial Vehicles—0
DER-GCN: Dialogue and Event Relation-Aware Graph Convolutional Neural Network for Multimodal Dialogue Emotion Recognition—0
Detecting Anomalies Through Contrast in Heterogeneous Data—0
Detecting Emotional Incongruity of Sarcasm by Commonsense Reasoning—0
Detection and Recovery Against Deep Neural Network Fault Injection Attacks Based on Contrastive Learning—0
Detect Low-Resource Rumors in Microblog Posts via Adversarial Contrastive Learning—0
Developing Healthcare Language Model Embedding Spaces—0
DFA-CON: A Contrastive Learning Approach for Detecting Copyright Infringement in DeepFake Art—0
DFCon: Attention-Driven Supervised Contrastive Learning for Robust Deepfake Detection—0
Dial2vec: Self-Guided Contrastive Learning of Unsupervised Dialogue Embeddings—0
DialAug: Mixing up Dialogue Contexts in Contrastive Learning for Robust Conversational Modeling—0
DIAL: Dense Image-text ALignment for Weakly Supervised Semantic Segmentation—0
Dialogue Response Generation via Contrastive Latent Representation Learning—0
Dialogue State Distillation Network with Inter-slot Contrastive Learning for Dialogue State Tracking—0
DICE: Data-Efficient Clinical Event Extraction with Generative Models—0
DictBERT: Dictionary Description Knowledge Enhanced Language Model Pre-training via Contrastive Learning—0
Dictionary-based Framework for Interpretable and Consistent Object Parsing—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