Computer Vision
 
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Person Re-Identification

510 papers with code • 34 benchmarks • 57 datasets

Person Re-Identification is a computer vision task in which the goal is to match a person's identity across different cameras or locations in a video or image sequence. It involves detecting and tracking a person and then using features such as appearance, body shape, and clothing to match their identity in different frames. The goal is to associate the same person across multiple non-overlapping camera views in a robust and efficient manner.

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Use these libraries to find Person Re-Identification models and implementations

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Bag of Tricks and A Strong Baseline for Deep Person Re-identification

michuanhaohao/reid-strong-baseline • • 17 Mar 2019

In the literature, some effective training tricks are briefly appeared in several papers or source codes.

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Unlabeled Samples Generated by GAN Improve the Person Re-identification Baseline in vitro

layumi/Person-reID_GAN • • ICCV 2017

We verify the proposed method on a practical problem: person re-identification (re-ID).

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Deep Mutual Learning

huanghoujing/AlignedReID-Re-Production-Pytorch • • CVPR 2018

Model distillation is an effective and widely used technique to transfer knowledge from a teacher to a student network.

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Learning Generalisable Omni-Scale Representations for Person Re-Identification

KaiyangZhou/deep-person-reid • • 15 Oct 2019

An effective person re-identification (re-ID) model should learn feature representations that are both discriminative, for distinguishing similar-looking people, and generalisable, for deployment across datasets without any adaptation.

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Torchreid: A Library for Deep Learning Person Re-Identification in Pytorch

KaiyangZhou/deep-person-reid • • 22 Oct 2019

Person re-identification (re-ID), which aims to re-identify people across different camera views, has been significantly advanced by deep learning in recent years, particularly with convolutional neural networks (CNNs).

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PAMTRI: Pose-Aware Multi-Task Learning for Vehicle Re-Identification Using Highly Randomized Synthetic Data

NVlabs/PAMTRI • • ICCV 2019

In comparison with person re-identification (ReID), which has been widely studied in the research community, vehicle ReID has received less attention.

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AlignedReID++: Dynamically matching local information for person re-identification

mindspore-ai/models • • Pattern Recognition 2019

Then, we propose a deep model name AlignedReID++ which is jointly learned with global features and local feature based on DMLI.

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Batch DropBlock Network for Person Re-identification and Beyond

daizuozhuo/batch-feature-erasing-network • • ICCV 2019

In this paper, we propose the Batch DropBlock (BDB) Network which is a two branch network composed of a conventional ResNet-50 as the global branch and a feature dropping branch.

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Deep Cosine Metric Learning for Person Re-Identification

nwojke/cosine_metric_learning • • 2 Dec 2018

Metric learning aims to construct an embedding where two extracted features corresponding to the same identity are likely to be closer than features from different identities.

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ABD-Net: Attentive but Diverse Person Re-Identification

TAMU-VITA/ABD-Net • • ICCV 2019

Attention mechanism has been shown to be effective for person re-identification (Re-ID).

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