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 851–900 of 1648 papers

TitleStatusHype
Interpretable Distance Metric Learning for Handwritten Chinese Character Recognition—0
Distance Metric-Based Learning with Interpolated Latent Features for Location Classification in Endoscopy Image and Video—0
Pretraining Neural Architecture Search Controllers with Locality-based Self-Supervised LearningCode0
Metric Learning for Anti-Compression Facial Forgery Detection—0
Cross-Domain Similarity Learning for Face Recognition in Unseen Domains—0
Cross-modal Image Retrieval with Deep Mutual Information Maximization—0
Fully Convolutional Geometric Features for Category-level Object Alignment—0
Meta-learning representations for clustering with infinite Gaussian mixture models—0
A Primer on Contrastive Pretraining in Language Processing: Methods, Lessons Learned and Perspectives—0
Decoupled and Memory-Reinforced Networks: Towards Effective Feature Learning for One-Step Person SearchCode0
Fuzzy clustering algorithms with distance metric learning and entropy regularization—0
Semi Supervised Learning For Few-shot Audio Classification By Episodic Triplet Mining—0
A Unified Batch Selection Policy for Active Metric Learning—0
Exploring Adversarial Robustness of Deep Metric LearningCode0
Dimension Free Generalization Bounds for Non Linear Metric Learning—0
MOTS R-CNN: Cosine-margin-triplet loss for multi-object tracking—0
Hyperspherical embedding for novel class classification—0
Feature Representation in Deep Metric Embeddings—0
Multimodal-Aware Weakly Supervised Metric Learning with Self-weighting Triplet Loss—0
Semantic Borrowing for Generalized Zero-Shot Learning—0
Melon Playlist Dataset: a public dataset for audio-based playlist generation and music taggingCode0
Few-Shot Learning for Road Object Detection—0
Supervised Tree-Wasserstein Distance—0
Hashing and metric learning for charged particle tracking—0
How Shift Equivariance Impacts Metric Learning for Instance SegmentationCode0
Probabilistic Metric Learning with Adaptive Margin for Top-K Recommendation—0
Rethinking Interactive Image Segmentation: Feature Space AnnotationCode0
Adversarial-Metric Learning for Audio-Visual Cross-Modal MatchingCode0
Lesion2Vec: Deep Metric Learning for Few-Shot Multiple Lesions Recognition in Wireless Capsule Endoscopy Video—0
Metric Learning for Session-based RecommendationsCode0
Recommending Accurate and Diverse Items Using Bilateral Branch Network—0
Sequence Metric Learning as Synchronization of Recurrent Neural Networks—0
Embedding Transfer via Smooth Contrastive Loss—0
Normalized Human Pose Features for Human Action Video Alignment—0
Adversarial Deep Metric Learning—0
Learning Deep Local Features With Multiple Dynamic Attentions for Large-Scale Image RetrievalCode0
Bayesian Metric Learning for Robust Training of Deep Models under Noisy Labels—0
Channel Augmented Joint Learning for Visible-Infrared RecognitionCode0
Learning Semantic Similarities for Prototypical Classifiers—0
Contextual Image Parsing via Panoptic Segment Sorting—0
Learning Better Visual Data Similarities via New Grouplet Non-Euclidean Embedding—0
MM-FSOD: Meta and metric integrated few-shot object detection—0
Person Re-identification with Adversarial Triplet Embedding—0
Person Re-Identification using Deep Learning Networks: A Systematic Review—0
Predicting Generalization in Deep Learning via Metric Learning -- PGDL Shared task—0
Odd-One-Out Representation LearningCode0
Deep Depression Prediction on Longitudinal Data via Joint Anomaly Ranking and Classification—0
Generalization Bound of Gradient Descent for Non-Convex Metric LearningCode0
Sharper Generalization Bounds for Pairwise Learning—0
A Deep Metric Learning Method for Biomedical Passage Retrieval—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