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 651–700 of 1648 papers

TitleStatusHype
Fully Convolutional Geometric Features for Category-level Object Alignment—0
Dare to Plagiarize? Plagiarized Painting Recognition and Retrieval—0
From Graph Local Embedding to Deep Metric Learning—0
A Unified Representation Learning Strategy for Open Relation Extraction with Ranked List Loss—0
Deep Credible Metric Learning for Unsupervised Domain Adaptation Person Re-identification—0
Attention Control with Metric Learning Alignment for Image Set-based Recognition—0
Hard Negative Mining for Metric Learning Based Zero-Shot Classification—0
Deep Cross-modality Adaptation via Semantics Preserving Adversarial Learning for Sketch-based 3D Shape Retrieval—0
Hashing and metric learning for charged particle tracking—0
Deep Distributional Sequence Embeddings Based on a Wasserstein Loss—0
Heterogeneous Metric Learning with Content-based Regularization for Software Artifact Retrieval—0
Heterogeneous Multi-task Metric Learning across Multiple Domains—0
From Forks to Forceps: A New Framework for Instance Segmentation of Surgical Instruments—0
Hierarchical Annotation of Images with Two-Alternative-Forced-Choice Metric Learning—0
From Age Estimation to Age-Invariant Face Recognition: Generalized Age Feature Extraction Using Order-Enhanced Contrastive Learning—0
Hierarchical Invariant Feature Learning with Marginalization for Person Re-Identification—0
Interpolated Discretized Embedding of Single Vectors and Vector Pairs for Classification, Metric Learning and Distance Approximation—0
Hierarchical Metric Learning and Matching for 2D and 3D Geometric Correspondences—0
Hierarchical Metric Learning for Optical Remote Sensing Scene Categorization—0
Hierarchical Multimodal Metric Learning for Multimodal Classification—0
Frequency Guidance Matters in Few-Shot Learning—0
Frequency Domain Modality-invariant Feature Learning for Visible-infrared Person Re-Identification—0
Attention-based Ensemble for Deep Metric Learning—0
HIER: Metric Learning Beyond Class Labels via Hierarchical Regularization—0
Integrating Parametric and Non-Parametric Models For Scene Labeling—0
Hi-Gen: Generative Retrieval For Large-Scale Personalized E-commerce Search—0
Deep learning-based person re-identification methods: A survey and outlook of recent works—0
Hotel Recognition via Latent Image Embedding—0
FlameFinder: Illuminating Obscured Fire through Smoke with Attentive Deep Metric Learning—0
A Geometric take on Metric Learning—0
A Metric Learning Approach to Misogyny Categorization—0
HSADML: Hyper-Sphere Angular Deep Metric based Learning for Brain Tumor Classification—0
Deep Metric Learning and Image Classification with Nearest Neighbour Gaussian Kernels—0
A metric learning approach for endoscopic kidney stone identification—0
Hybrid-Attention based Decoupled Metric Learning for Zero-Shot Image Retrieval—0
Hybrid Consistency Training with Prototype Adaptation for Few-Shot Learning—0
Compressive Mahalanobis Metric Learning Adapts to Intrinsic Dimension—0
Hybrid Multi-stage Decoding for Few-shot NER with Entity-aware Contrastive Learning—0
Fine-tune your Classifier: Finding Correlations With Temperature—0
Hyperbolic Metric Learning for Visual Outlier Detection—0
FinePseudo: Improving Pseudo-Labelling through Temporal-Alignablity for Semi-Supervised Fine-Grained Action Recognition—0
Instance Cross Entropy for Deep Metric Learning—0
Intelligent Known and Novel Aircraft Recognition -- A Shift from Classification to Similarity Learning for Combat Identification—0
Deep Metric Learning-Based Semi-Supervised Regression With Alternate Learning—0
Interpretable and Generalizable Person Re-Identification with Query-Adaptive Convolution and Temporal Lifting—0
Hyperspherical embedding for novel class classification—0
CLAREL: Classification via retrieval loss for zero-shot learning—0
Hyp-UML: Hyperbolic Image Retrieval with Uncertainty-aware Metric Learning—0
Deep Metric Learning for Computer Vision: A Brief Overview—0
Fine-Grained Visual Categorization via Multi-stage 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