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Metric Learning

164 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 SELF-SUPERVISED 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

Disentangling by Subspace Diffusion

23 Jun 2020deepmind/deepmind-research

We show that fully unsupervised factorization of a data manifold is possible *if* the true metric of the manifold is known and each factor manifold has nontrivial holonomy -- for example, rotation in 3D.

METRIC LEARNING REPRESENTATION LEARNING

metric-learn: Metric Learning Algorithms in Python

13 Aug 2019all-umass/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.

FEW-SHOT IMAGE CLASSIFICATION LANGUAGE MODELLING METRIC LEARNING OMNIGLOT ONE-SHOT LEARNING

Point Cloud Oversegmentation with Graph-Structured Deep Metric Learning

CVPR 2019 loicland/superpoint_graph

We propose a new supervized learning framework for oversegmenting 3D point clouds into superpoints.

METRIC LEARNING SEMANTIC SEGMENTATION