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 851–900 of 1648 papers

TitleStatusHype
SEINE: SEgment-based Indexing for NEural information retrieval—0
Self-supervised Auxiliary Loss for Metric Learning in Music Similarity-based Retrieval and Auto-tagging—0
Self-supervised Latent Space Optimization with Nebula Variational Coding—0
Self-Supervised Metric Learning in Multi-View Data: A Downstream Task Perspective—0
Self-Supervised Visual Place Recognition Learning in Mobile Robots—0
Self-Taught Metric Learning without Labels—0
Self-training via Metric Learning for Source-Free Domain Adaptation of Semantic Segmentation—0
Self-Weighted Multiview Metric Learning by Maximizing the Cross Correlations—0
Semantic Borrowing for Generalized Zero-Shot Learning—0
Semantic-Enhanced Relational Metric Learning for Recommender Systems—0
Semantic Frame Induction with Deep Metric Learning—0
Semantic Granularity Metric Learning for Visual Search—0
Semantic Segmentation from Limited Training Data—0
Semantic Video Entity Linking Based on Visual Content and Metadata—0
Semi-Crowdsourced Clustering: Generalizing Crowd Labeling by Robust Distance Metric Learning—0
Semi-Supervised Clustering for Short Answer Scoring—0
Semi-supervised Kernel Metric Learning Using Relative Comparisons—0
Semi Supervised Learning For Few-shot Audio Classification By Episodic Triplet Mining—0
Semi-Supervised Metric Learning: A Deep Resurrection—0
Semi-Supervised Nonlinear Distance Metric Learning via Forests of Max-Margin Cluster Hierarchies—0
Sensitive Image Classification by Vision Transformers—0
SentPWNet: A Unified Sentence Pair Weighting Network for Task-specific Sentence Embedding—0
Sequence Metric Learning as Synchronization of Recurrent Neural Networks—0
Set Augmented Triplet Loss for Video Person Re-Identification—0
SetMargin Loss applied to Deep Keystroke Biometrics with Circle Packing Interpretation—0
SGD Algorithms based on Incomplete U-statistics: Large-Scale Minimization of Empirical Risk—0
Shadow: A Novel Loss Function for Efficient Training in Siamese Networks—0
Sharing Matters for Generalization in Deep Metric Learning—0
Sharper Generalization Bounds for Pairwise Learning—0
Shoestring: Graph-Based Semi-Supervised Classification With Severely Limited Labeled Data—0
ShufaNet: Classification method for calligraphers who have reached the professional level—0
Distance Metric-Based Learning with Interpolated Latent Features for Location Classification in Endoscopy Image and Video—0
Signal Processing in the Retina: Interpretable Graph Classifier to Predict Ganglion Cell Responses—0
Signal-to-Noise Ratio: A Robust Distance Metric for Deep Metric Learning—0
Significance of Softmax-based Features in Comparison to Distance Metric Learning-based Features—0
Pairwise Supervision Can Provably Elicit a Decision Boundary—0
Similarity Component Analysis—0
Similarity Function Tracking using Pairwise Comparisons—0
SIMILARITY LEARNING FOR COVER SONG IDENTIFICATION USING CROSS-SIMILARITY MATRICES OF MULTI-LEVEL DEEP SEQUENCES—0
Similarity Learning via Adaptive Regression and Its Application to Image Retrieval—0
Simple But Effective: Rethinking the Ability of Deep Learning in fNIRS to Exclude Abnormal Input—0
Simple Stochastic and Online Gradient Descent Algorithms for Pairwise Learning—0
Simultaneous Preference and Metric Learning from Paired Comparisons—0
Single-image driven 3d viewpoint training data augmentation for effective wine label recognition—0
SLADE: A Self-Training Framework For Distance Metric Learning—0
Smart Mining for Deep Metric Learning—0
Smooth Proxy-Anchor Loss for Noisy Metric Learning—0
Solving Instance Detection from an Open-World Perspective—0
SpaDen : Sparse and Dense Keypoint Estimation for Real-World Chart Understanding—0
Sparse Compositional Metric Learning—0
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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
3NEDR@191.5—Unverified
4ResNet-50 + Intra-Batch (ensemble of 5)R@191.5—Unverified
5ResNet-50 + AVSLR@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