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

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Showing 1151–1200 of 1648 papers

TitleStatusHype
Automatic MILP Solver Configuration By Learning Problem Similarities—0
A weakly supervised adaptive triplet loss for deep metric learning—0
A Weakly Supervised Approach to Emotion-change Prediction and Improved Mood Inference—0
Bayesian Evidential Learning for Few-Shot Classification—0
Bayesian Metric Learning for Robust Training of Deep Models under Noisy Labels—0
Bayesian Neighbourhood Component Analysis—0
Bayesian representation learning with oracle constraints—0
Better Knowledge Retention through Metric Learning—0
Beyond Accuracy: Statistical Measures and Benchmark for Evaluation of Representation from Self-Supervised Learning—0
Beyond Classification: Latent User Interests Profiling from Visual Contents Analysis—0
Beyond Context: Exploring Semantic Similarity for Tiny Face Detection—0
Beyond Mahalanobis Metric: Cayley-Klein Metric Learning—0
Beyond the Deep Metric Learning: Enhance the Cross-Modal Matching with Adversarial Discriminative Domain Regularization—0
Bidirectional Feature Globalization for Few-shot Semantic Segmentation of 3D Point Cloud Scenes—0
BIER - Boosting Independent Embeddings Robustly—0
Bilevel Distance Metric Learning for Robust Image Recognition—0
Bilinear pooling and metric learning network for early Alzheimer's disease identification with FDG-PET images—0
Blazingly Fast Video Object Segmentation with Pixel-Wise Metric Learning—0
Boosted Sparse Non-linear Distance Metric Learning—0
BotTriNet: A Unified and Efficient Embedding for Social Bots Detection via Metric Learning—0
Bounded-Distortion Metric Learning—0
BP-Triplet Net for Unsupervised Domain Adaptation: A Bayesian Perspective—0
Bridging Gap between Image Pixels and Semantics via Supervision: A Survey—0
Bringing Multimodality to Amazon Visual Search System—0
BWSNet: Automatic Perceptual Assessment of Audio Signals—0
Bypassing Logits Bias in Online Class-Incremental Learning with a Generative Framework—0
CAFENet: Class-Agnostic Few-Shot Edge Detection Network—0
Calibrated neighborhood aware confidence measure for deep metric learning—0
Threshold-Consistent Margin Loss for Open-World Deep Metric Learning—0
Can an unsupervised clustering algorithm reproduce a categorization system?—0
EnvId: A Metric Learning Approach for Forensic Few-Shot Identification of Unseen Environments—0
Case-based Similar Image Retrieval for Weakly Annotated Large Histopathological Images of Malignant Lymphoma Using Deep Metric Learning—0
Catching Image Retrieval Generalization—0
Causal Fair Metric: Bridging Causality, Individual Fairness, and Adversarial Robustness—0
CDAD-Net: Bridging Domain Gaps in Generalized Category Discovery—0
Center Contrastive Loss for Metric Learning—0
Centroid-based deep metric learning for speaker recognition—0
Challenge report: Recognizing Families In the Wild Data Challenge—0
Channel Interaction Networks for Fine-Grained Image Categorization—0
Chemical Identification and Indexing in PubMed Articles via BERT and Text-to-Text Approaches—0
Class2Simi: A Noise Reduction Perspective on Learning with Noisy Labels—0
Class Anchor Margin Loss for Content-Based Image Retrieval—0
Classifying All Interacting Pairs in a Single Shot—0
Class-Specific Channel Attention for Few-Shot Learning—0
CLLMFS: A Contrastive Learning enhanced Large Language Model Framework for Few-Shot Named Entity Recognition—0
Closed-Form Training of Mahalanobis Distance for Supervised Clustering—0
A Broad Dataset is All You Need for One-Shot Object Detection—0
Cluster Head Detection for Hierarchical UAV Swarm With Graph Self-supervised Learning—0
CNN Retrieval based Unsupervised Metric Learning for Near-Duplicated Video Retrieval—0
Coded Residual Transform for Generalizable Deep Metric Learning—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