Person Re-Identification

268 papers with code • 15 benchmarks • 33 datasets

Person re-identification is the task of associating images of the same person taken from different cameras or from the same camera in different occasions.

( Image credit: PRID2011 dataset )

Greatest papers with code

MobileNetV2: Inverted Residuals and Linear Bottlenecks

tensorflow/models CVPR 2018

In this paper we describe a new mobile architecture, MobileNetV2, that improves the state of the art performance of mobile models on multiple tasks and benchmarks as well as across a spectrum of different model sizes.

Image Classification Object Detection +3

Deep Residual Learning for Image Recognition

tensorflow/models CVPR 2016

Deep residual nets are foundations of our submissions to ILSVRC & COCO 2015 competitions, where we also won the 1st places on the tasks of ImageNet detection, ImageNet localization, COCO detection, and COCO segmentation.

Breast Tumour Classification Domain Generalization +8

Random Erasing Data Augmentation

rwightman/pytorch-image-models 16 Aug 2017

In this paper, we introduce Random Erasing, a new data augmentation method for training the convolutional neural network (CNN).

General Classification Image Augmentation +3

Densely Connected Convolutional Networks

pytorch/vision CVPR 2017

Recent work has shown that convolutional networks can be substantially deeper, more accurate, and efficient to train if they contain shorter connections between layers close to the input and those close to the output.

Breast Tumour Classification Crowd Counting +4

ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices

tensorpack/tensorpack CVPR 2018

We introduce an extremely computation-efficient CNN architecture named ShuffleNet, which is designed specially for mobile devices with very limited computing power (e. g., 10-150 MFLOPs).

General Classification Image Classification +2

Simple Online and Realtime Tracking with a Deep Association Metric

nwojke/deep_sort 21 Mar 2017

Simple Online and Realtime Tracking (SORT) is a pragmatic approach to multiple object tracking with a focus on simple, effective algorithms.

Large-Scale Person Re-Identification Multiple Object Tracking +1

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).

Person Re-Identification

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.

Unsupervised Domain Adaptation Unsupervised Person Re-Identification

Omni-Scale Feature Learning for Person Re-Identification

KaiyangZhou/deep-person-reid ICCV 2019

As an instance-level recognition problem, person re-identification (ReID) relies on discriminative features, which not only capture different spatial scales but also encapsulate an arbitrary combination of multiple scales.

Person Re-Identification

Deep Transfer Learning for Person Re-identification

KaiyangZhou/deep-person-reid 16 Nov 2016

Second, a two-stepped fine-tuning strategy is developed to transfer knowledge from auxiliary datasets.

General Classification Image Classification +2