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 501550 of 1648 papers

TitleStatusHype
Task-Embedded Control Networks for Few-Shot Imitation LearningCode0
InDiReCT: Language-Guided Zero-Shot Deep Metric Learning for ImagesCode0
A Framework to Enhance Generalization of Deep Metric Learning methods using General Discriminative Feature Learning and Class Adversarial Neural NetworksCode0
Cross-View Kernel Similarity Metric Learning Using Pairwise Constraints for Person Re-identificationCode0
Adversarial-Metric Learning for Audio-Visual Cross-Modal MatchingCode0
Incorporating the Rhetoric of Scientific Language into Sentence Embeddings using Phrase-guided Distant Supervision and Metric LearningCode0
Enhancing Sample Utilization in Noise-Robust Deep Metric Learning With Subgroup-Based Positive-Pair SelectionCode0
Time-Frequency Scattering Accurately Models Auditory Similarities Between Instrumental Playing TechniquesCode0
Ensemble of Loss Functions to Improve Generalizability of Deep Metric Learning methodsCode0
Context-Aware Visual Compatibility PredictionCode0
A Systematic Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and DatasetsCode0
Cross-view Asymmetric Metric Learning for Unsupervised Person Re-identificationCode0
In Defense of the Classification Loss for Person Re-IdentificationCode0
Adapted Deep Embeddings: A Synthesis of Methods for k-Shot Inductive Transfer LearningCode0
Improving Collaborative Metric Learning with Efficient Negative SamplingCode0
Improving Generalization of Metric Learning via Listwise Self-distillationCode0
In Defense of the Triplet Loss for Person Re-IdentificationCode0
Interval Bound Interpolation for Few-shot Learning with Few TasksCode0
Hyperparameter-Free Out-of-Distribution Detection Using Softmax of Scaled Cosine SimilarityCode0
Affective Manifolds: Modeling Machine's Mind to Like, Dislike, Enjoy, Suffer, Worry, Fear, and Feel Like A HumanCode0
IDEAL: Improved DEnse locAL Contrastive Learning for Semi-Supervised Medical Image SegmentationCode0
How Shift Equivariance Impacts Metric Learning for Instance SegmentationCode0
Affect-DML: Context-Aware One-Shot Recognition of Human Affect using Deep Metric LearningCode0
HSE: Hybrid Species Embedding for Deep Metric LearningCode0
Holistic and Comprehensive Annotation of Clinically Significant Findings on Diverse CT Images: Learning from Radiology Reports and Label OntologyCode0
Associative Alignment for Few-shot Image ClassificationCode0
Human Motion Analysis with Deep Metric LearningCode0
IDEAL: Independent Domain Embedding Augmentation LearningCode0
A few-shot learning approach with domain adaptation for personalized real-life stress detection in close relationshipsCode0
Criterion-based Heterogeneous Collaborative Filtering for Multi-behavior Implicit RecommendationCode0
Heated-Up Softmax EmbeddingCode0
Hierarchical Latent Relation Modeling for Collaborative Metric LearningCode0
Hard Example Generation by Texture Synthesis for Cross-domain Shape Similarity LearningCode0
Hard-Aware Deeply Cascaded EmbeddingCode0
Hard-Aware Point-to-Set Deep Metric for Person Re-identificationCode0
MGNN: Graph Neural Networks Inspired by Distance Geometry ProblemCode0
Facing the Void: Overcoming Missing Data in Multi-View ImageryCode0
Cosine meets Softmax: A tough-to-beat baseline for visual groundingCode0
GSSF: Generalized Structural Sparse Function for Deep Cross-modal Metric LearningCode0
Hardness-Aware Deep Metric LearningCode0
High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric LearningCode0
Correlation Congruence for Knowledge DistillationCode0
Correcting the Triplet Selection Bias for Triplet LossCode0
A Simple and Effective Framework for Pairwise Deep Metric LearningCode0
Counterpart Fairness -- Addressing Systematic between-group Differences in Fairness EvaluationCode0
Ground Metric Learning on GraphsCode0
Graphite: GRAPH-Induced feaTure Extraction for Point Cloud RegistrationCode0
Global Ground Metric Learning with Applications to scRNA dataCode0
Fast(er) Reconstruction of Shredded Text Documents via Self-Supervised Deep Asymmetric Metric LearningCode0
Exploring Temporal Concurrency for Video-Language Representation LearningCode0
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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