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
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
Robust Text Detection in Natural Scene Images—0
Rogue Emitter Detection Using Hybrid Network of Denoising Autoencoder and Deep Metric Learning—0
Rotation Invariant Aerial Image Retrieval with Group Convolutional Metric Learning—0
Routine Modeling with Time Series Metric Learning—0
RS-MetaNet: Deep meta metric learning for few-shot remote sensing scene classification—0
Sample complexity of learning Mahalanobis distance metrics—0
SAR Image Change Detection via Spatial Metric Learning with an Improved Mahalanobis Distance—0
Satellite Image Search in AgoraEO—0
Scalable Angular Discriminative Deep Metric Learning for Face Recognition—0
Scalable Deep Metric Learning on Attributed Graphs—0
Scalable Fine-grained Generated Image Classification Based on Deep Metric Learning—0
Scalable Metric Learning via Weighted Approximate Rank Component Analysis—0
Scalable Nonlinear Embeddings for Semantic Category-based Image Retrieval—0
Scalable Similarity Learning using Large Margin Neighborhood Embedding—0
Scaling-up Empirical Risk Minimization: Optimization of Incomplete U-statistics—0
Scene Parsing with Integration of Parametric and Non-parametric Models—0
School-based malaria chemoprevention as a cost-effective approach to improve cognitive and educational outcomes: a meta-analysis—0
SC-ML: Self-supervised Counterfactual Metric Learning for Debiased Visual Question Answering—0
SCNet: Enhancing Few-Shot Semantic Segmentation by Self-Contrastive Background Prototypes—0
SCoRe: Submodular Combinatorial Representation Learning—0
A Self-Penalizing Objective Function for Scalable Interaction Detection—0
Secure Metric Learning via Differential Pairwise Privacy—0
See the Forest for the Trees: Joint Spatial and Temporal Recurrent Neural Networks for Video-Based Person Re-Identification—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