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 1551–1600 of 1648 papers

TitleStatusHype
LEAP: Learning Embeddings for Adaptive Pace—0
Learning 3D Keypoint Descriptors for Non-Rigid Shape Matching—0
Learning a Discriminative Null Space for Person Re-identification—0
Learning a Distance Metric from a Network—0
Learning a Local Feature Descriptor for 3D LiDAR Scans—0
Learning and Exploiting Interclass Visual Correlations for Medical Image Classification—0
Learning and Understanding a Disentangled Feature Representation for Hidden Parameters in Reinforcement Learning—0
Learning an Integrated Distance Metric for Comparing Structure of Complex Networks—0
Learning a Tree of Metrics with Disjoint Visual Features—0
Learning a Unified Embedding for Visual Search at Pinterest—0
Learning Better Visual Data Similarities via New Grouplet Non-Euclidean Embedding—0
Learning Deep Optimal Embeddings with Sinkhorn Divergences—0
Learning Deep Representations by Mutual Information for Person Re-identification—0
Learning Deep Structure-Preserving Image-Text Embeddings—0
Learning Discriminative ab-Divergences for Positive Definite Matrices—0
Learning Discriminative Aggregation Network for Video-Based Face Recognition—0
Learning Discriminative Alpha-Beta-divergence for Positive Definite Matrices (Extended Version)—0
Learning Discriminative features using Center Loss and Reconstruction as Regularizer for Speech Emotion Recognition—0
Learning Discriminative Representation via Metric Learning for Imbalanced Medical Image Classification—0
Learning Distances from Data with Normalizing Flows and Score Matching—0
Learning Empirical Bregman Divergence for Uncertain Distance Representation—0
Learning Euclidean-to-Riemannian Metric for Point-to-Set Classification—0
Learning for Transductive Threshold Calibration in Open-World Recognition—0
Learning from Extrinsic and Intrinsic Supervisions for Domain Generalization—0
Learning Fused State Representations for Control from Multi-View Observations—0
Learning Generalized Hybrid Proximity Representation for Image Recognition—0
Learning Graph Edit Distance by Graph Neural Networks—0
Learning Hierarchical Feature Space Using CLAss-specific Subspace Multiple Kernel -- Metric Learning for Classification—0
Learning Incremental Triplet Margin for Person Re-identification—0
Learning Invariant Representations Of Planar Curves—0
Learning Locally-Adaptive Decision Functions for Person Verification—0
Learning Local Metrics and Influential Regions for Classification—0
Learning Low-Dimensional Metrics—0
Robust Mahalanobis Metric Learning via Geometric Approximation Algorithms—0
Learning Mahalanobis Metric Spaces via Geometric Approximation Algorithms—0
Learning Metric Graphs for Neuron Segmentation In Electron Microscopy Images—0
Learning Optimal Parameters for Multi-target Tracking with Contextual Interactions—0
Learning Personalized Item-to-Item Recommendation Metric via Implicit Feedback—0
Learning Point Embeddings from Shape Repositories for Few-Shot Segmentation—0
Learning Rates for Nonconvex Pairwise Learning—0
Learning Semantic Relatedness From Human Feedback Using Metric Learning—0
Learning Semantic Similarities for Prototypical Classifiers—0
Learning Sequence Neighbourhood Metrics—0
Learning Similarity Metrics for Dynamic Scene Segmentation—0
Learning Speaker-specific Lip-to-Speech Generation—0
Learning Spectral Transform Network on 3D Surface for Non-rigid Shape Analysis—0
Learning suction graspability considering grasp quality and robot reachability for bin-picking—0
Learning to Align Multi-Camera Domains using Part-Aware Clustering for Unsupervised Video Person Re-Identification—0
Learning to Compare Relation: Semantic Alignment for Few-Shot Learning—0
Learning to embed semantic similarity for joint image-text retrieval—0
Show:102550
← PrevPage 32 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