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 1–50 of 1648 papers

TitleStatusHype
Unsupervised Ground Metric Learning—0
Are encoders able to learn landmarkers for warm-starting of Hyperparameter Optimization?—0
Droid: A Resource Suite for AI-Generated Code Detection—0
Grid-Reg: Grid-Based SAR and Optical Image Registration Across Platforms—0
Dare to Plagiarize? Plagiarized Painting Recognition and Retrieval—0
Multimodal Information Retrieval for Open World with Edit Distance Weak Supervision—0
Offline Goal-Conditioned Reinforcement Learning with Projective Quasimetric Planning—0
AbRank: A Benchmark Dataset and Metric-Learning Framework for Antibody-Antigen Affinity RankingCode1
Global Ground Metric Learning with Applications to scRNA dataCode0
Few-Shot Learning for Industrial Time Series: A Comparative Analysis Using the Example of Screw-Fastening Process Monitoring—0
Discrete Scale-invariant Metric Learning for Efficient Collaborative FilteringCode0
Synthetic Speech Source Tracing using Metric Learning—0
Self-supervised Latent Space Optimization with Nebula Variational Coding—0
Unveiling Audio Deepfake Origins: A Deep Metric learning And Conformer Network Approach With Ensemble Fusion—0
DA-VPT: Semantic-Guided Visual Prompt Tuning for Vision TransformersCode1
Emotion-aware Dual Cross-Attentive Neural Network with Label Fusion for Stance Detection in Misinformative Social Media ContentCode0
Learning to Select In-Context Demonstration Preferred by Large Language Model—0
Adversarial Deep Metric Learning for Cross-Modal Audio-Text Alignment in Open-Vocabulary Keyword Spotting—0
LLM-based Evaluation Policy Extraction for Ecological Modeling—0
Negative Metric Learning for Graphs—0
Physics-informed Temporal Difference Metric Learning for Robot Motion PlanningCode1
Let Humanoids Hike! Integrative Skill Development on Complex Trails—0
GRAML: Goal Recognition As Metric Learning—0
ProFi-Net: Prototype-based Feature Attention with Curriculum Augmentation for WiFi-based Gesture Recognition—0
A Few-Shot Metric Learning Method with Dual-Channel Attention for Cross-Modal Same-Neuron Identification—0
Proxy-Anchor and EVT-Driven Continual Learning Method for Generalized Category DiscoveryCode0
Optimistic Online Learning in Symmetric Cone Games—0
Randomized Pairwise Learning with Adaptive Sampling: A PAC-Bayes Analysis—0
Reasoning and Learning a Perceptual Metric for Self-Training of Reflective Objects in Bin-Picking with a Low-cost CameraCode0
Unlocking the Hidden Potential of CLIP in Generalizable Deepfake DetectionCode2
Enhancing Martian Terrain Recognition with Deep Constrained Clustering—0
Reconstructing Cell Lineage Trees from Phenotypic Features with Metric Learning—0
Riemannian Metric Learning: Closer to You than You Imagine—0
Radar Pulse Deinterleaving with Transformer Based Deep Metric Learning—0
Stability-based Generalization Analysis of Randomized Coordinate Descent for Pairwise Learning—0
Solving Instance Detection from an Open-World Perspective—0
GPU-accelerated Multi-relational Parallel Graph Retrieval for Web-scale Recommendations—0
A novel approach to data generation in generative model—0
Automatic Identification of Samples in Hip-Hop Music via Multi-Loss Training and an Artificial Dataset—0
Learning Fused State Representations for Control from Multi-View Observations—0
Supervised Similarity for High-Yield Corporate Bonds with Quantum Cognition Machine Learning—0
Exploring Few-Shot Defect Segmentation in General Industrial Scenarios with Metric Learning and Vision Foundation ModelsCode0
Supervised Quadratic Feature Analysis: Information Geometry Approach for Dimensionality ReductionCode0
Personalized Layer Selection for Graph Neural Networks—0
Geometric Mean Improves Loss For Few-Shot Learning—0
ARM-IRL: Adaptive Resilience Metric Quantification Using Inverse Reinforcement Learning—0
CroMe: Multimodal Fake News Detection using Cross-Modal Tri-Transformer and Metric Learning—0
Enhancing Sample Utilization in Noise-Robust Deep Metric Learning With Subgroup-Based Positive-Pair SelectionCode0
Unit Region Encoding: A Unified and Compact Geometry-aware Representation for Floorplan Applications—0
Mutual Regression Distance—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