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 1251–1300 of 1648 papers

TitleStatusHype
Modeling Uncertainty with Hedged Instance Embeddings—0
Momentum Contrast Speaker Representation Learning—0
Motion2Vec: Semi-Supervised Representation Learning from Surgical Videos—0
MOTS R-CNN: Cosine-margin-triplet loss for multi-object tracking—0
COMPILED: Deep Metric Learning for Defect Classification of Threaded Pipe Connections using Multichannel Partially Observed Functional Data—0
MRIS: A Multi-modal Retrieval Approach for Image Synthesis on Diverse Modalities—0
MSE Loss with Outlying Label for Imbalanced Classification—0
Multi-Evidence Filtering and Fusion for Multi-Label Classification, Object Detection and Semantic Segmentation Based on Weakly Supervised Learning—0
Multi-feature Distance Metric Learning for Non-rigid 3D Shape Retrieval—0
Multifidelity Covariance Estimation via Regression on the Manifold of Symmetric Positive Definite Matrices—0
Multi-Head Deep Metric Learning Using Global and Local Representations—0
MULTI-LABEL METRIC LEARNING WITH BIDIRECTIONAL REPRESENTATION DEEP NEURAL NETWORKS—0
Multilingual Query-by-Example Keyword Spotting with Metric Learning and Phoneme-to-Embedding Mapping—0
Multi-Manifold Deep Metric Learning for Image Set Classification—0
Multimodal-Aware Weakly Supervised Metric Learning with Self-weighting Triplet Loss—0
Multimodal Information Retrieval for Open World with Edit Distance Weak Supervision—0
Multimodal Learning in Loosely-organized Web Images—0
Multimodal Prototype-Enhanced Network for Few-Shot Action Recognition—0
Multimorbidity Content-Based Medical Image Retrieval Using Proxies—0
Multiple Closed-Form Local Metric Learning for K-Nearest Neighbor Classifier—0
Multiple Kernel Fisher Discriminant Metric Learning for Person Re-identification—0
Multiple Manifolds Metric Learning with Application to Image Set Classification—0
Multiple Metric Learning for Structured Data—0
Multiple Riemannian Manifold-valued Descriptors based Image Set Classification with Multi-Kernel Metric Learning—0
Multi Proxy Anchor Family Loss for Several Types of Gradients—0
Multi-scale Adaptive Task Attention Network for Few-Shot Learning—0
Multiscale CNN based Deep Metric Learning for Bioacoustic Classification: Overcoming Training Data Scarcity Using Dynamic Triplet Loss—0
Multi-Scale Convolutions for Learning Context Aware Feature Representations—0
Multi-Scale Feature and Metric Learning for Relation Extraction—0
Multi-task Metric Learning for Text-independent Speaker Verification—0
Multi-Task Metric Learning on Network Data—0
Multi-threshold Deep Metric Learning for Facial Expression Recognition—0
Multi-view adaptive graph convolutions for graph classification—0
Multi-view Deep Features for Robust Facial Kinship Verification—0
Multi-view metric learning for multi-instance image classification—0
Multi-view Metric Learning for Multi-view Video Summarization—0
Multi-view Metric Learning in Vector-valued Kernel Spaces—0
Mutual Regression Distance—0
NDPNet: A novel non-linear data projection network for few-shot fine-grained image classification—0
Nearest Neighbour Radial Basis Function Solvers for Deep Neural Networks—0
Negative Metric Learning for Graphs—0
Neighborhood Repulsed Metric Learning for Kinship Verification—0
Neural Bregman Divergences for Distance Learning—0
Neural Metric Learning for Fast End-to-End Relation Extraction—0
Neural Snowflakes: Universal Latent Graph Inference via Trainable Latent Geometries—0
Next Item Recommendation with Self-Attention—0
Noise-Resistant Deep Metric Learning with Probabilistic Instance Filtering—0
Nonlinear Local Metric Learning for Person Re-identification—0
Non-linear Metric Learning—0
Nonlinear Metric Learning for kNN and SVMs through Geometric Transformations—0
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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