SOTAVerified

Metric Learning

The goal of Metric Learning is to learn a representation function that maps objects into an embedded space. The distance in the embedded space should preserve the objects’ similarity — similar objects get close and dissimilar objects get far away. Various loss functions have been developed for Metric Learning. For example, the contrastive loss guides the objects from the same class to be mapped to the same point and those from different classes to be mapped to different points whose distances are larger than a margin. Triplet loss is also popular, which requires the distance between the anchor sample and the positive sample to be smaller than the distance between the anchor sample and the negative sample.

Source: Road Network Metric Learning for Estimated Time of Arrival

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 501–550 of 1648 papers

TitleStatusHype
ProtoVAE: Prototypical Networks for Unsupervised Disentanglement—0
SuSana Distancia is all you need: Enforcing class separability in metric learning via two novel distance-based loss functions for few-shot image classification—0
Category-Oriented Representation Learning for Image to Multi-Modal Retrieval—0
Semantic Frame Induction with Deep Metric Learning—0
STIR: Siamese Transformer for Image Retrieval PostprocessingCode0
FineEHR: Refine Clinical Note Representations to Improve Mortality Prediction—0
Deep Metric Learning Assisted by Intra-variance in A Semi-supervised View of Learning—0
Multilingual Query-by-Example Keyword Spotting with Metric Learning and Phoneme-to-Embedding Mapping—0
Collaborative Residual Metric LearningCode0
Learning Empirical Bregman Divergence for Uncertain Distance Representation—0
Self-supervised Auxiliary Loss for Metric Learning in Music Similarity-based Retrieval and Auto-tagging—0
Deep Metric Multi-View Hashing for Multimedia Retrieval—0
Representer Theorems for Metric and Preference Learning: A Geometric Perspective—0
BotTriNet: A Unified and Efficient Embedding for Social Bots Detection via Metric Learning—0
Robust Calibrate Proxy Loss for Deep Metric Learning—0
SC-ML: Self-supervised Counterfactual Metric Learning for Debiased Visual Question Answering—0
VGTS: Visually Guided Text Spotting for Novel Categories in Historical Manuscripts—0
Adaptive Cross Batch Normalization for Metric Learning—0
An embedding for EEG signals learned using a triplet loss—0
Creating Ensembles of Classifiers through UMDA for Aerial Scene Classification—0
School-based malaria chemoprevention as a cost-effective approach to improve cognitive and educational outcomes: a meta-analysis—0
MRIS: A Multi-modal Retrieval Approach for Image Synthesis on Diverse Modalities—0
Privacy-preserving Pedestrian Tracking using Distributed 3D LiDARs—0
Ultra-High-Resolution Detector Simulation with Intra-Event Aware GAN and Self-Supervised Relational ReasoningCode0
Learning Human-Compatible Representations for Case-Based Decision SupportCode0
DTW-SiameseNet: Dynamic Time Warped Siamese Network for Mispronunciation Detection and Correction—0
Domain-aware Triplet loss in Domain GeneralizationCode0
Metric Learning Improves the Ability of Combinatorial Coverage Metrics to Anticipate Classification Error—0
Improving safety in physical human-robot collaboration via deep metric learning—0
On the Stability and Generalization of Triplet Learning—0
Fashion Image Retrieval with Multi-Granular Alignment—0
Distinguishability Calibration to In-Context LearningCode0
Transferable Deep Metric Learning for Clustering—0
Triplet Loss-less Center Loss Sampling Strategies in Facial Expression Recognition Scenarios—0
Multi-Fidelity Covariance Estimation in the Log-Euclidean GeometryCode0
Learning Generalized Hybrid Proximity Representation for Image Recognition—0
Proxy-based Zero-Shot Entity Linking by Effective Candidate Retrieval—0
Inspecting class hierarchies in classification-based metric learning modelsCode0
An Automated Vulnerability Detection Framework for Smart Contracts—0
MN-Pair Contrastive Damage Representation and Clustering for Prognostic Explanation—0
NAPReg: Nouns As Proxies Regularization for Semantically Aware Cross-Modal EmbeddingsCode0
Triple-stream Deep Metric Learning of Great Ape Behavioural Actions—0
Learning Debiased Representations via Conditional Attribute InterpolationCode0
Similarity Metric Learning for RGB-Infrared Group Re-IdentificationCode0
Treating Pseudo-labels Generation as Image Matting for Weakly Supervised Semantic Segmentation—0
Learning with Diversity: Self-Expanded Equalization for Better Generalized Deep Metric Learning—0
Deep Semi-Supervised Metric Learning With Mixed Label Propagation—0
HSE: Hybrid Species Embedding for Deep Metric LearningCode0
Frequency Guidance Matters in Few-Shot Learning—0
Misalign, Contrast then Distill: Rethinking Misalignments in Language-Image Pre-training—0
Show:102550
← PrevPage 11 of 33Next →
All datasetsCARS196Stanford Online ProductsCUB-200-2011In-ShopDyML-AnimalDyML-ProductDyML-Vehicle

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Unicom+ViT-L@336pxR@198.2—Unverified
2Hyp-DINO 8x8R@192.8—Unverified
3ResNet-50 + AVSLR@191.5—Unverified
4NEDR@191.5—Unverified
5ResNet-50 + Intra-Batch (ensemble of 5)R@191.5—Unverified
6EfficientDML-VPTSP-G/512R@191.2—Unverified
7CCL (ResNet-50)R@191.02—Unverified
8ResNet50 + LanguageR@190.2—Unverified
9ResNet-50 + MetrixR@189.6—Unverified
10ResNet50 + S2SDR@189.5—Unverified
#ModelMetricClaimedVerifiedStatus
1Unicom+ViT-L@336pxR@191.2—Unverified
2STIRR@188.3—Unverified
3Recall@k Surrogate Loss (ViT-B/16)R@188—Unverified
4ViT-TripletR@186.5—Unverified
5ROADMAP (DeiT-S)R@186—Unverified
6Hyp-ViTR@185.9—Unverified
7Hyp-DINOR@185.1—Unverified
8Recall@k Surrogate Loss (ViT-B/32)R@185.1—Unverified
9CCL (ResNet-50)R@183.1—Unverified
10ROADMAP (ResNet-50)R@183.1—Unverified
#ModelMetricClaimedVerifiedStatus
1Unicom+ViT-L@336pxR@190.1—Unverified
2EfficientDML-VPTSP-G/512R@188.5—Unverified
3Hyp-ViTR@185.6—Unverified
4Hyp-DINOR@180.9—Unverified
5NEDR@174.9—Unverified
6CCL (ResNet-50)R@173.45—Unverified
7ResNet-50 + AVSLR@171.9—Unverified
8ResNet-50 + Intra-Batch ConnectionsR@171.8—Unverified
9ResNet50 + LanguageR@171.4—Unverified
10ResNet-50 + MetrixR@171.4—Unverified
#ModelMetricClaimedVerifiedStatus
1Unicom+ViT-L@336pxR@196.7—Unverified
2STIRR@195—Unverified
3MGAR@194.3—Unverified
4Hyp-ViTR@192.5—Unverified
5Hyp-DINOR@192.4—Unverified
6CCL (ResNet-50)R@192.31—Unverified
7Gradient SurgeryR@192.21—Unverified
8ResNet-50 + MetrixR@192.2—Unverified
9EfficientDML-VPTSP-G/512R@192.1—Unverified
10ViT-TripletR@192.1—Unverified
#ModelMetricClaimedVerifiedStatus
1HAPPIERAverage-mAP43.8—Unverified
2CSLAverage-mAP31—Unverified
#ModelMetricClaimedVerifiedStatus
1HAPPIERAverage-mAP38—Unverified
2CSLAverage-mAP28.7—Unverified
#ModelMetricClaimedVerifiedStatus
1HAPPIERAverage-mAP37—Unverified
2CSLAverage-mAP12.1—Unverified