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

Showing 16011648 of 1648 papers

TitleStatusHype
Similarity Component Analysis0
Multiple Closed-Form Local Metric Learning for K-Nearest Neighbor Classifier0
Reconstructing Big Semantic Similarity Networks0
A Kernel Classification Framework for Metric Learning0
A Metric-learning based framework for Support Vector Machines and Multiple Kernel Learning0
The Classification Accuracy of Multiple-Metric Learning Algorithm on Multi-Sensor Fusion0
Manopt, a Matlab toolbox for optimization on manifolds0
Supervised Metric Learning with Generalization Guarantees0
Neighborhood Repulsed Metric Learning for Kinship Verification0
Learning an Integrated Distance Metric for Comparing Structure of Complex Networks0
A Survey on Metric Learning for Feature Vectors and Structured Data0
Guaranteed Classification via Regularized Similarity Learning0
Fusing Robust Face Region Descriptors via Multiple Metric Learning for Face Recognition in the Wild0
Learning Locally-Adaptive Decision Functions for Person Verification0
Locally Aligned Feature Transforms across Views0
Local Fisher Discriminant Analysis for Pedestrian Re-identification0
On the Generalization Ability of Online Learning Algorithms for Pairwise Loss Functions0
Efficient Distance Metric Learning by Adaptive Sampling and Mini-Batch Stochastic Gradient Descent (SGD)0
Information Theoretic Learning with Infinitely Divisible Kernels0
Robust Text Detection in Natural Scene Images0
Large Scale Strongly Supervised Ensemble Metric Learning, with Applications to Face Verification and Retrieval0
Metric Learning for Graph-Based Domain Adaptation0
Modeling ESL Word Choice Similarities By Representing Word Intensions and Extensions0
Parametric Local Metric Learning for Nearest Neighbor Classification0
A Geometric take on Metric Learning0
Non-linear Metric Learning0
Semi-Crowdsourced Clustering: Generalizing Crowd Labeling by Robust Distance Metric Learning0
Latent Coincidence Analysis: A Hidden Variable Model for Distance Metric Learning0
Communication/Computation Tradeoffs in Consensus-Based Distributed Optimization0
Hamming Distance Metric Learning0
Robustness and Generalization for Metric Learning0
Detection of Peculiar Word Sense by Distance Metric Learning with Labeled Examples0
Robust Metric Learning by Smooth Optimization0
Metric Learning with Multiple Kernels0
Learning a Distance Metric from a Network0
Maximum Covariance Unfolding : Manifold Learning for Bimodal Data0
Target Neighbor Consistent Feature Weighting for Nearest Neighbor Classification0
Learning a Tree of Metrics with Disjoint Visual Features0
Learning Sequence Neighbourhood Metrics0
Generative Local Metric Learning for Nearest Neighbor Classification0
Inductive Regularized Learning of Kernel Functions0
Large Margin Multi-Task Metric Learning0
Worst-Case Linear Discriminant Analysis0
Sparse Metric Learning via Smooth Optimization0
Regularized Distance Metric Learning:Theory and Algorithm0
Positive Semidefinite Metric Learning with Boosting0
Supervised Bipartite Graph Inference0
Online Metric Learning and Fast Similarity Search0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Unicom+ViT-L@336pxR@198.2Unverified
2Hyp-DINO 8x8R@192.8Unverified
3NEDR@191.5Unverified
4ResNet-50 + Intra-Batch (ensemble of 5)R@191.5Unverified
5ResNet-50 + AVSLR@191.5Unverified
6EfficientDML-VPTSP-G/512R@191.2Unverified
7CCL (ResNet-50)R@191.02Unverified
8ResNet50 + LanguageR@190.2Unverified
9ResNet-50 + MetrixR@189.6Unverified
10ResNet50 + S2SDR@189.5Unverified
#ModelMetricClaimedVerifiedStatus
1Unicom+ViT-L@336pxR@191.2Unverified
2STIRR@188.3Unverified
3Recall@k Surrogate Loss (ViT-B/16)R@188Unverified
4ViT-TripletR@186.5Unverified
5ROADMAP (DeiT-S)R@186Unverified
6Hyp-ViTR@185.9Unverified
7Hyp-DINOR@185.1Unverified
8Recall@k Surrogate Loss (ViT-B/32)R@185.1Unverified
9CCL (ResNet-50)R@183.1Unverified
10ROADMAP (ResNet-50)R@183.1Unverified
#ModelMetricClaimedVerifiedStatus
1Unicom+ViT-L@336pxR@190.1Unverified
2EfficientDML-VPTSP-G/512R@188.5Unverified
3Hyp-ViTR@185.6Unverified
4Hyp-DINOR@180.9Unverified
5NEDR@174.9Unverified
6CCL (ResNet-50)R@173.45Unverified
7ResNet-50 + AVSLR@171.9Unverified
8ResNet-50 + Intra-Batch ConnectionsR@171.8Unverified
9ResNet50 + LanguageR@171.4Unverified
10ResNet-50 + MetrixR@171.4Unverified
#ModelMetricClaimedVerifiedStatus
1Unicom+ViT-L@336pxR@196.7Unverified
2STIRR@195Unverified
3MGAR@194.3Unverified
4Hyp-ViTR@192.5Unverified
5Hyp-DINOR@192.4Unverified
6CCL (ResNet-50)R@192.31Unverified
7Gradient SurgeryR@192.21Unverified
8ResNet-50 + MetrixR@192.2Unverified
9EfficientDML-VPTSP-G/512R@192.1Unverified
10ViT-TripletR@192.1Unverified
#ModelMetricClaimedVerifiedStatus
1HAPPIERAverage-mAP43.8Unverified
2CSLAverage-mAP31Unverified
#ModelMetricClaimedVerifiedStatus
1HAPPIERAverage-mAP38Unverified
2CSLAverage-mAP28.7Unverified
#ModelMetricClaimedVerifiedStatus
1HAPPIERAverage-mAP37Unverified
2CSLAverage-mAP12.1Unverified