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 1501–1550 of 1648 papers

TitleStatusHype
Improving safety in physical human-robot collaboration via deep metric learning—0
Improving Semantic Embedding Consistency by Metric Learning for Zero-Shot Classification—0
Improving the Gap in Visual Speech Recognition Between Normal and Silent Speech Based on Metric Learning—0
Improving the Robustness of Deep Neural Networks via Adversarial Training with Triplet Loss—0
Improving Voice Trigger Detection with Metric Learning—0
Incorporating Intra-Class Variance to Fine-Grained Visual Recognition—0
Incremental Class Learning using Variational Autoencoders with Similarity Learning—0
Inductive Regularized Learning of Kernel Functions—0
Information Theoretic Learning with Infinitely Divisible Kernels—0
Informative Sample-Aware Proxy for Deep Metric Learning—0
Instance Cross Entropy for Deep Metric Learning—0
Integrating Parametric and Non-Parametric Models For Scene Labeling—0
Intelligent Known and Novel Aircraft Recognition -- A Shift from Classification to Similarity Learning for Combat Identification—0
Interpolated Discretized Embedding of Single Vectors and Vector Pairs for Classification, Metric Learning and Distance Approximation—0
Interpretable and Generalizable Person Re-Identification with Query-Adaptive Convolution and Temporal Lifting—0
Interpretable Distance Metric Learning for Handwritten Chinese Character Recognition—0
Interpretable embeddings to understand computing careers—0
Is Fairness Only Metric Deep? Evaluating and Addressing Subgroup Gaps in Deep Metric Learning—0
Iterated Support Vector Machines for Distance Metric Learning—0
Iterative Deep Graph Learning for Graph Neural Networks—0
Joint Adaptive Neighbours and Metric Learning for Multi-view Subspace Clustering—0
Joint Dimensionality Reduction and Metric Learning: A Geometric Take—0
Joint Discriminative and Metric Embedding Learning for Person Re-Identification—0
Joint Intensity and Spatial Metric Learning for Robust Gait Recognition—0
Jointly Learning Multiple Measures of Similarities from Triplet Comparisons—0
Kernel-based Distance Metric Learning in the Output Space—0
Mixed-type Distance Shrinkage and Selection for Clustering via Kernel Metric Learning—0
Kernel Regression with Sparse Metric Learning—0
Knowledge Elicitation using Deep Metric Learning and Psychometric Testing—0
Categorical Knowledge Fused Recognition: Fusing Hierarchical Knowledge with Image Classification through Aligning and Deep Metric Learning—0
Knowledge Guided Metric Learning for Few-Shot Text Classification—0
Label Efficient Learning of Transferable Representations acrosss Domains and Tasks—0
Label Efficient Learning of Transferable Representations across Domains and Tasks—0
LabellessFace: Fair Metric Learning for Face Recognition without Attribute Labels—0
Label-Removed Generative Adversarial Networks Incorporating with K-Means—0
Language and Obfuscation Oblivious Source Code Authorship Attribution—0
Large Margin Multi-Task Metric Learning—0
Large Margin Prototypical Network for Few-shot Relation Classification with Fine-grained Features—0
Large-Margin Representation Learning for Texture Classification—0
Large-scale Distance Metric Learning with Uncertainty—0
Large Scale Distributed Distance Metric Learning—0
Large Scale Landmark Recognition via Deep Metric Learning—0
Large Scale Local Online Similarity/Distance Learning Framework based on Passive/Aggressive—0
Large Scale Question Paraphrase Retrieval with Smoothed Deep Metric Learning—0
Large Scale Strongly Supervised Ensemble Metric Learning, with Applications to Face Verification and Retrieval—0
Large-Scale Visual Font Recognition—0
Latent Coincidence Analysis: A Hidden Variable Model for Distance Metric Learning—0
Latent Topic Refinement based on Distance Metric Learning and Semantics-assisted Non-negative Matrix Factorization—0
Latent Variable Modeling with Diversity-Inducing Mutual Angular Regularization—0
LDDMM-Face: Large Deformation Diffeomorphic Metric Learning for Flexible and Consistent Face Alignment—0
Show:102550
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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