Metric Learning
Leaderboards
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Greatest papers with code
Time-Contrastive Networks: Self-Supervised Learning from Video
While representations are learned from an unlabeled collection of task-related videos, robot behaviors such as pouring are learned by watching a single 3rd-person demonstration by a human.
Classification is a Strong Baseline for Deep Metric Learning
• microsoft/computervision-recipes
• 
Deep metric learning aims to learn a function mapping image pixels to embedding feature vectors that model the similarity between images.
CONTENT-BASED IMAGE RETRIEVAL FACE VERIFICATION METRIC LEARNING
A Metric Learning Reality Check
• KevinMusgrave/pytorch-metric-learning
•
Deep metric learning papers from the past four years have consistently claimed great advances in accuracy, often more than doubling the performance of decade-old methods.
metric-learn: Metric Learning Algorithms in Python
metric-learn is an open source Python package implementing supervised and weakly-supervised distance metric learning algorithms.
In Defense of the Triplet Loss for Person Re-Identification
• VisualComputingInstitute/triplet-reid
• 
In the past few years, the field of computer vision has gone through a revolution fueled mainly by the advent of large datasets and the adoption of deep convolutional neural networks for end-to-end learning.
#24 best model for
Person Re-Identification
on DukeMTMC-reID
Building Computationally Efficient and Well-Generalizing Person Re-Identification Models with Metric Learning
Submitted to International Conference on Pattern Recognition (ICPR 2020) 2020
• opencv/openvino_training_extensions
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This work considers the problem of domain shift in person re-identification. Being trained on one dataset, a re-identification model usually performs much worse on unseen data.
#3 best model for
Person Re-Identification
on MSMT17
DOMAIN GENERALIZATION FACE RECOGNITION METRIC LEARNING PERSON RE-IDENTIFICATION
Matching Networks for One Shot Learning
NeurIPS 2016
• oscarknagg/few-shot
•
Our algorithm improves one-shot accuracy on ImageNet from 87. 6% to 93. 2% and from 88. 0% to 93. 8% on Omniglot compared to competing approaches.
#6 best model for
Few-Shot Image Classification
on OMNIGLOT - 1-Shot Learning
LANGUAGE MODELLING METRIC LEARNING OMNIGLOT ONE-SHOT LEARNING
Cross-Batch Memory for Embedding Learning
Mining informative negative instances are of central importance to deep metric learning (DML).
Multi-Similarity Loss with General Pair Weighting for Deep Metric Learning
CVPR 2019
• bnu-wangxun/Deep_Metric
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A family of loss functions built on pair-based computation have been proposed in the literature which provide a myriad of solutions for deep metric learning.
Person Re-identification by Local Maximal Occurrence Representation and Metric Learning
CVPR 2015
• zhunzhong07/person-re-ranking
•
In this paper, we propose an effective feature representation called Local Maximal Occurrence (LOMO), and a subspace and metric learning method called Cross-view Quadratic Discriminant Analysis (XQDA).
#33 best model for
Person Re-Identification
on DukeMTMC-reID