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

Showing 401450 of 1648 papers

TitleStatusHype
On Background Bias in Deep Metric LearningCode0
And what if two musical versions don't share melody, harmony, rhythm, or lyrics ?0
Lexical semantics enhanced neural word embeddings0
Self-Supervised Monocular Depth Estimation: Solving the Edge-Fattening ProblemCode1
Incorporating the Rhetoric of Scientific Language into Sentence Embeddings using Phrase-guided Distant Supervision and Metric LearningCode0
COPNER: Contrastive Learning with Prompt Guiding for Few-shot Named Entity RecognitionCode1
The Minority Matters: A Diversity-Promoting Collaborative Metric Learning AlgorithmCode0
Uncertainty Estimation for 3D Dense Prediction via Cross-Point EmbeddingsCode0
A Simple Way to Learn Metrics Between Attributed Graphs0
Understanding Open-Set Recognition by Jacobian Norm and Inter-Class Separation0
Query-Guided Networks for Few-shot Fine-grained Classification and Person Search0
DDGHM: Dual Dynamic Graph with Hybrid Metric Training for Cross-Domain Sequential Recommendation0
Deep Metric Learning with Chance ConstraintsCode0
Magnetic Resonance Fingerprinting with compressed sensing and distance metric learning0
Towards A Unified Policy Abstraction Theory and Representation Learning Approach in Markov Decision Processes0
A Continual Development Methodology for Large-scale Multitask Dynamic ML SystemsCode0
Combining Metric Learning and Attention Heads For Accurate and Efficient Multilabel Image ClassificationCode1
Learning Deep Optimal Embeddings with Sinkhorn Divergences0
Vec2Face-v2: Unveil Human Faces from their Blackbox Features via Attention-based Network in Face Recognition0
ScaleFace: Uncertainty-aware Deep Metric LearningCode0
Class-Specific Channel Attention for Few-Shot Learning0
Latent Similarity Identifies Important Functional Connections for Phenotype PredictionCode0
Optimizing Bi-Encoder for Named Entity Recognition via Contrastive LearningCode1
Affective Manifolds: Modeling Machine's Mind to Like, Dislike, Enjoy, Suffer, Worry, Fear, and Feel Like A HumanCode0
Few-Shot Learning Meets Transformer: Unified Query-Support Transformers for Few-Shot Classification0
Satellite Image Search in AgoraEO0
Learning Branched Fusion and Orthogonal Projection for Face-Voice AssociationCode1
Representation Learning for the Automatic Indexing of Sound Effects LibrariesCode1
HyP^2 Loss: Beyond Hypersphere Metric Space for Multi-label Image RetrievalCode1
Bidirectional Feature Globalization for Few-shot Semantic Segmentation of 3D Point Cloud Scenes0
Regressing Relative Fine-Grained Change for Sub-Groups in Unreliable Heterogeneous Data Through Deep Multi-Task Metric Learning0
Pairwise Learning via Stagewise Training in Proximal Setting0
Unsupervised Graph Spectral Feature Denoising for Crop Yield Prediction0
Content-Based Landmark Retrieval Combining Global and Local Features using Siamese Neural NetworksCode0
Semantic Data Augmentation based Distance Metric Learning for Domain Generalization0
DAS: Densely-Anchored Sampling for Deep Metric LearningCode1
Re-thinking and Re-labeling LIDC-IDRI for Robust Pulmonary Cancer Prediction0
V^2L: Leveraging Vision and Vision-language Models into Large-scale Product RetrievalCode1
Active Learning of Ordinal Embeddings: A User Study on Football Data0
ConceptBeam: Concept Driven Target Speech Extraction0
Rethinking Few-Shot Class-Incremental Learning with Open-Set Hypothesis in Hyperbolic Geometry0
Bayesian Evidential Learning for Few-Shot Classification0
WideResNet with Joint Representation Learning and Data Augmentation for Cover Song Identification0
Cross Vision-RF Gait Re-identification with Low-cost RGB-D Cameras and mmWave Radars0
Segment-level Metric Learning for Few-shot Bioacoustic Event DetectionCode1
Adversarial Reweighting for Speaker Verification Fairness0
Learning Discriminative Representation via Metric Learning for Imbalanced Medical Image Classification0
Few-Shot Specific Emitter Identification via Deep Metric Ensemble LearningCode1
Dam reservoir extraction from remote sensing imagery using tailored metric learning strategiesCode0
Supervised similarity learning for corporate bonds using Random Forest proximities0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Unicom+ViT-L@336pxR@198.2Unverified
2Hyp-DINO 8x8R@192.8Unverified
3ResNet-50 + AVSLR@191.5Unverified
4NEDR@191.5Unverified
5ResNet-50 + Intra-Batch (ensemble of 5)R@191.5Unverified
6EfficientDML-VPTSP-G/512R@191.2Unverified
7CCL (ResNet-50)R@191.02Unverified
8ResNet50 + LanguageR@190.2Unverified
9ResNet-50 + MetrixR@189.6Unverified
10ResNet50 + S2SDR@189.5Unverified
#ModelMetricClaimedVerifiedStatus
1Unicom+ViT-L@336pxR@191.2Unverified
2STIRR@188.3Unverified
3Recall@k Surrogate Loss (ViT-B/16)R@188Unverified
4ViT-TripletR@186.5Unverified
5ROADMAP (DeiT-S)R@186Unverified
6Hyp-ViTR@185.9Unverified
7Hyp-DINOR@185.1Unverified
8Recall@k Surrogate Loss (ViT-B/32)R@185.1Unverified
9CCL (ResNet-50)R@183.1Unverified
10ROADMAP (ResNet-50)R@183.1Unverified
#ModelMetricClaimedVerifiedStatus
1Unicom+ViT-L@336pxR@190.1Unverified
2EfficientDML-VPTSP-G/512R@188.5Unverified
3Hyp-ViTR@185.6Unverified
4Hyp-DINOR@180.9Unverified
5NEDR@174.9Unverified
6CCL (ResNet-50)R@173.45Unverified
7ResNet-50 + AVSLR@171.9Unverified
8ResNet-50 + Intra-Batch ConnectionsR@171.8Unverified
9ResNet50 + LanguageR@171.4Unverified
10ResNet-50 + MetrixR@171.4Unverified
#ModelMetricClaimedVerifiedStatus
1Unicom+ViT-L@336pxR@196.7Unverified
2STIRR@195Unverified
3MGAR@194.3Unverified
4Hyp-ViTR@192.5Unverified
5Hyp-DINOR@192.4Unverified
6CCL (ResNet-50)R@192.31Unverified
7Gradient SurgeryR@192.21Unverified
8ResNet-50 + MetrixR@192.2Unverified
9EfficientDML-VPTSP-G/512R@192.1Unverified
10ViT-TripletR@192.1Unverified
#ModelMetricClaimedVerifiedStatus
1HAPPIERAverage-mAP43.8Unverified
2CSLAverage-mAP31Unverified
#ModelMetricClaimedVerifiedStatus
1HAPPIERAverage-mAP38Unverified
2CSLAverage-mAP28.7Unverified
#ModelMetricClaimedVerifiedStatus
1HAPPIERAverage-mAP37Unverified
2CSLAverage-mAP12.1Unverified