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Metric Learning

133 papers with code · Methodology

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Time-Contrastive Networks: Self-Supervised Learning from Video

23 Apr 2017tensorflow/models

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.

METRIC LEARNING

Classification is a Strong Baseline for Deep Metric Learning

30 Nov 2018microsoft/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

18 Mar 2020KevinMusgrave/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 LEARNING

metric-learn: Metric Learning Algorithms in Python

13 Aug 2019scikit-learn-contrib/metric-learn

metric-learn is an open source Python package implementing supervised and weakly-supervised distance metric learning algorithms.

METRIC LEARNING MODEL SELECTION

In Defense of the Triplet Loss for Person Re-Identification

22 Mar 2017VisualComputingInstitute/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.

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.

LANGUAGE MODELLING METRIC LEARNING OMNIGLOT ONE-SHOT LEARNING

Cross-Batch Memory for Embedding Learning

14 Dec 2019bnu-wangxun/Deep_Metric

Mining informative negative instances are of central importance to deep metric learning (DML).

IMAGE RETRIEVAL METRIC LEARNING

Multi-Similarity Loss with General Pair Weighting for Deep Metric Learning

CVPR 2019 bnu-wangxun/Deep_Metric

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.

IMAGE RETRIEVAL 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).

METRIC LEARNING PERSON RE-IDENTIFICATION