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 801–850 of 1648 papers

TitleStatusHype
Deep Metric Learning Model for Imbalanced Fault Diagnosis—0
Quantifying Outlierness of Funds from their Categories using Supervised Similarity—0
Quantifying point cloud realism through adversarially learned latent representations—0
Quantum Polar Metric Learning: Efficient Classically Learned Quantum Embeddings—0
Query-augmented Active Metric Learning—0
Query-Guided Networks for Few-shot Fine-grained Classification and Person Search—0
Radar Pulse Deinterleaving with Transformer Based Deep Metric Learning—0
RaLF: Flow-based Global and Metric Radar Localization in LiDAR Maps—0
Randomized Pairwise Learning with Adaptive Sampling: A PAC-Bayes Analysis—0
Ranking labs-of-origin for genetically engineered DNA using Metric Learning—0
Realigned Softmax Warping for Deep Metric Learning—0
Recommending Accurate and Diverse Items Using Bilateral Branch Network—0
Reconstructing Big Semantic Similarity Networks—0
Reconstructing Cell Lineage Trees from Phenotypic Features with Metric Learning—0
Reconstruction-Based Disentanglement for Pose-invariant Face Recognition—0
Reconstruction Regularized Deep Metric Learning for Multi-label Image Classification—0
Reduced-Rank Local Distance Metric Learning for k-NN Classification—0
Rethinking preventing class-collapsing in metric learning with margin-based losses—0
Reducing Class Collapse in Metric Learning with Easy Positive Sampling—0
Regressing Relative Fine-Grained Change for Sub-Groups in Unreliable Heterogeneous Data Through Deep Multi-Task Metric Learning—0
Regressive Virtual Metric Learning—0
Regularized Distance Metric Learning:Theory and Algorithm—0
Relational Constraints for Metric Learning on Relational Data—0
Relational Proxy Loss for Audio-Text based Keyword Spotting—0
Relative Geometry-Aware Siamese Neural Network for 6DOF Camera Relocalization—0
Relative Order Analysis and Optimization for Unsupervised Deep Metric Learning—0
Reliable Probability Intervals For Classification Using Inductive Venn Predictors Based on Distance Learning—0
RelocNet: Continuous Metric Learning Relocalisation using Neural Nets—0
Representer Theorems for Metric and Preference Learning: A Geometric Perspective—0
RetailKLIP : Finetuning OpenCLIP backbone using metric learning on a single GPU for Zero-shot retail product image classification—0
Re-thinking and Re-labeling LIDC-IDRI for Robust Pulmonary Cancer Prediction—0
Rethinking Batch Sample Relationships for Data Representation: A Batch-Graph Transformer based Approach—0
Beyond Triplet Loss: Meta Prototypical N-tuple Loss for Person Re-identification—0
Rethinking Collaborative Metric Learning: Toward an Efficient Alternative without Negative Sampling—0
Rethinking Deep Contrastive Learning with Embedding Memory—0
Rethinking Few-Shot Class-Incremental Learning with Open-Set Hypothesis in Hyperbolic Geometry—0
Retrospective Encoders for Video Summarization—0
Revisiting Distance Metric Learning for Few-Shot Natural Language Classification—0
Revisiting Experience Replayable Conditions—0
Revisiting Metric Learning for Few-Shot Image Classification—0
Revisiting Metric Learning for SPD Matrix Based Visual Representation—0
Revisiting Relevance Feedback for CLIP-based Interactive Image Retrieval—0
Revisiting Street-to-Aerial View Image Geo-localization and Orientation Estimation—0
Riemannian Metric Learning: Closer to You than You Imagine—0
Riemannian Metric Learning for Symmetric Positive Definite Matrices—0
Riemannian Metric Learning via Optimal Transport—0
Road Network Metric Learning for Estimated Time of Arrival—0
Denoising Multi-Similarity Formulation: A Self-paced Curriculum-Driven Approach for Robust Metric Learning—0
Robust Calibrate Proxy Loss for Deep Metric Learning—0
Robustness and Generalization for 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
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