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 951–1000 of 1648 papers

TitleStatusHype
Towards A Unified Policy Abstraction Theory and Representation Learning Approach in Markov Decision Processes—0
Towards Comprehensive Representation Enhancement in Semantics-guided Self-supervised Monocular Depth Estimation—0
Towards Context-Aware Neural Performance-Score Synchronisation—0
Towards ECDSA key derivation from deep embeddings for novel Blockchain applications—0
Towards Fine-Grained Webpage Fingerprinting at Scale—0
Towards Making High Dimensional Distance Metric Learning Practical—0
Towards Scalable and Channel-Robust Radio Frequency Fingerprint Identification for LoRa—0
Towards Self-Adaptive Metric Learning On the Fly—0
Towards structure-preserving quantum encodings—0
Towards understanding how attention mechanism works in deep learning—0
Towards Visually Explaining Similarity Models—0
Tracklet Association by Online Target-Specific Metric Learning and Coherent Dynamics Estimation—0
Tracklet Association with Online Target-Specific Metric Learning—0
Trade When Opportunity Comes: Price Movement Forecasting via Locality-Aware Attention and Iterative Refinement Labeling—0
Trainable Class Prototypes for Few-Shot Learning—0
TransA: An Adaptive Approach for Knowledge Graph Embedding—0
Transductive Episodic-Wise Adaptive Metric for Few-Shot Learning—0
Transferable Deep Metric Learning for Clustering—0
Transfer Metric Learning: Algorithms, Applications and Outlooks—0
Transfer of View-manifold Learning to Similarity Perception of Novel Objects—0
Transferring Knowledge Fragments for Learning Distance Metric from A Heterogeneous Domain—0
Treating Pseudo-labels Generation as Image Matting for Weakly Supervised Semantic Segmentation—0
Tree Edit Distance Learning via Adaptive Symbol Embeddings: Supplementary Materials and Results—0
Tree Edit Distance Learning via Adaptive Symbol Embeddings—0
Tree Structure-Aware Graph Representation Learning via Integrated Hierarchical Aggregation and Relational Metric Learning—0
Triple-stream Deep Metric Learning of Great Ape Behavioural Actions—0
TripletGAN: Training Generative Model with Triplet Loss—0
Triplet Loss-less Center Loss Sampling Strategies in Facial Expression Recognition Scenarios—0
Triplet Network with Attention for Speaker Diarization—0
MetricUNet: Synergistic Image- and Voxel-Level Learning for Precise CT Prostate Segmentation via Online Sampling—0
TrueBranch: Metric Learning-based Verification of Forest Conservation Projects—0
Two Regimes of Generalization for Non-Linear Metric Learning—0
Two-Stage Metric Learning—0
Two-stream joint matching method based on contrastive learning for few-shot action recognition—0
Ugly Ducklings or Swans: A Tiered Quadruplet Network with Patient-Specific Mining for Improved Skin Lesion Classification—0
Uncertainty-Aware Deep Attention Recurrent Neural Network for Heterogeneous Time Series Imputation—0
Uncertainty-Aware Few-Shot Image Classification—0
Self-Supervised 3D Traversability Estimation with Proxy Bank Guidance—0
Understanding and Exploiting Dependent Variables with Deep Metric Learning—0
Understanding Metric Learning on Unit Hypersphere and Generating Better Examples for Adversarial Training—0
Understanding Open-Set Recognition by Jacobian Norm and Inter-Class Separation—0
Unified Embedding and Metric Learning for Zero-Exemplar Event Detection—0
Unifying Few- and Zero-Shot Egocentric Action Recognition—0
Unique Faces Recognition in Videos—0
Unit Region Encoding: A Unified and Compact Geometry-aware Representation for Floorplan Applications—0
Universal Correspondence Network—0
Learning Unified Distance Metric Across Diverse Data Distributions with Parameter-Efficient Transfer Learning—0
Unsupervised Deep Metric Learning via Auxiliary Rotation Loss—0
Unsupervised Deep Metric Learning via Orthogonality based Probabilistic Loss—0
Unsupervised Deep Metric Learning with Transformed Attention Consistency and Contrastive Clustering Loss—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