[ACM MM2021] MGH: Metadata Guided Hypergraph Modeling for Unsupervised Person Re-identification

Related tags

Deep LearningMGH.pytorch
Overview

Introduction

This project is developed based on FastReID, which is an ongoing ReID project.

Projects

BUC

In projects/BUC, we implement AAAI 2019 paper A Bottom-Up Clustering Approach to Unsupervised Person Re-Identification. The original implementation is in BUC.

SpCL

In projects/SpCL, we implement NeurIPS 2020 paper Self-paced Contrastive Learning with Hybrid Memory for Domain Adaptive Object Re-ID. The original implementation is in SpCL.

HCT

In projects/HCT, we implement CVPR 2020 paper Hierarchical Clustering with Hard-batch Triplet Loss for Person Re-identification. The original implementation is in HCT

MGH

In projects/MGH, we implement ACM MM 2021 paper MGH: Metadata Guided Hypergraph Modeling for Unsupervised Person Re-identification. Please refer it's README for more details. Paper

Citation

Please cite our work:

@inproceedings{wu2021mgh,
  author    = {Yiming Wu and
               Xintian Wu and 
               Jian Tian and 
               Xi Li},
  title     = {MGH: Metadata Guided Hypergraph Modeling for Unsupervised Person Re-identification},
  booktitle = ACMMM,
  year      = 2021,
  publisher = {{ACM}}}
You might also like...
[TIP2020] Adaptive Graph Representation Learning for Video Person Re-identification

Introduction This is the PyTorch implementation for Adaptive Graph Representation Learning for Video Person Re-identification. Get started git clone h

WuYiming 41 Dec 12, 2022
[CVPR-2021] UnrealPerson: An adaptive pipeline for costless person re-identification
[CVPR-2021] UnrealPerson: An adaptive pipeline for costless person re-identification

UnrealPerson: An Adaptive Pipeline for Costless Person Re-identification In our paper (arxiv), we propose a novel pipeline, UnrealPerson, that decreas

ZhangTianyu 70 Oct 10, 2022
IAUnet: Global Context-Aware Feature Learning for Person Re-Identification

IAUnet This repository contains the code for the paper: IAUnet: Global Context-Aware Feature Learning for Person Re-Identification Ruibing Hou, Bingpe

null 30 Jul 14, 2022
Implementation of "Learning Multi-Granular Hypergraphs for Video-Based Person Re-Identification"

hypergraph_reid Implementation of "Learning Multi-Granular Hypergraphs for Video-Based Person Re-Identification" If you find this help your research,

null 62 Dec 21, 2022
Person Re-identification
Person Re-identification

Person Re-identification Final project of Computer Vision Table of content Person Re-identification Table of content Students: Proposed method Dataset

Nguyễn Hoàng Quân 4 Jun 17, 2021
Experiment about Deep Person Re-identification with EfficientNet-v2
Experiment about Deep Person Re-identification with EfficientNet-v2

We evaluated the baseline with Resnet50 and Efficienet-v2 without using pretrained models. Also Resnet50-IBN-A and Efficientnet-v2 using pretrained on ImageNet. We used two datasets: Market-1501 and CUHK03.

lan.nguyen2k 77 Jan 3, 2023
Torchreid: Deep learning person re-identification in PyTorch.

Torchreid Torchreid is a library for deep-learning person re-identification, written in PyTorch. It features: multi-GPU training support both image- a

Kaiyang 3.7k Jan 5, 2023
Joint Discriminative and Generative Learning for Person Re-identification. CVPR'19 (Oral)
Joint Discriminative and Generative Learning for Person Re-identification. CVPR'19 (Oral)

Joint Discriminative and Generative Learning for Person Re-identification [Project] [Paper] [YouTube] [Bilibili] [Poster] [Supp] Joint Discriminative

NVIDIA Research Projects 1.2k Dec 30, 2022
CM-NAS: Cross-Modality Neural Architecture Search for Visible-Infrared Person Re-Identification (ICCV2021)

CM-NAS Official Pytorch code of paper CM-NAS: Cross-Modality Neural Architecture Search for Visible-Infrared Person Re-Identification in ICCV2021. Vis

JDAI-CV 40 Nov 25, 2022
Releases(v0.1-alpha)

  • v0.1-alpha(Aug 23, 2021)

    For projects MGH, these models are trained on Market1501, DukeMTMC, and MSMT17. The model files should be organized as follow

    models
├── duke
│   └── model_duke.pth
├── market
│   └── model_market.pth
└── msmt17
    └── model_msmt17.pth

    if you want to test these models, please check projects/MGH/test.sh, and follow projects/MGH/README.md to run testing.

    Source code(tar.gz)
    Source code(zip)
    models.zip(965.39 MB)
Owner
WuYiming
WuYiming
GitHub Repository
One-Shot Neural Ensemble Architecture Search by Diversity-Guided Search Space Shrinking

One-Shot Neural Ensemble Architecture Search by Diversity-Guided Search Space Shrinking This is an official implementation for NEAS presented in CVPR

Multimedia Research 19 Sep 08, 2022
PyTorch implementation of some learning rate schedulers for deep learning researcher.

pytorch-lr-scheduler PyTorch implementation of some learning rate schedulers for deep learning researcher. Usage WarmupReduceLROnPlateauScheduler Visu

Soohwan Kim 59 Dec 08, 2022
Supplementary materials for ISMIR 2021 LBD paper "Evaluation of Latent Space Disentanglement in the Presence of Interdependent Attributes"

Evaluation of Latent Space Disentanglement in the Presence of Interdependent Attributes Supplementary materials for ISMIR 2021 LBD submission: K. N. W

Karn Watcharasupat 2 Oct 25, 2021
Advances in Neural Information Processing Systems (NeurIPS), 2020.

What is being transferred in transfer learning? This repo contains the code for the following paper: Behnam Neyshabur*, Hanie Sedghi*, Chiyuan Zhang*.

Google Research 36 Aug 26, 2022
This is a pytorch implementation for the BST model from Alibaba https://arxiv.org/pdf/1905.06874.pdf

Behavior-Sequence-Transformer-Pytorch This is a pytorch implementation for the BST model from Alibaba https://arxiv.org/pdf/1905.06874.pdf This model

Jaime Ferrando Huertas 83 Jan 05, 2023
Evidential Softmax for Sparse Multimodal Distributions in Deep Generative Models

Evidential Softmax for Sparse Multimodal Distributions in Deep Generative Models Abstract Many applications of generative models rely on the marginali

Stanford Intelligent Systems Laboratory 9 Jun 06, 2022
Official repository of the paper "GPR1200: A Benchmark for General-PurposeContent-Based Image Retrieval"

GPR1200 Dataset GPR1200: A Benchmark for General-Purpose Content-Based Image Retrieval (ArXiv) Konstantin Schall, Kai Uwe Barthel, Nico Hezel, Klaus J

Visual Computing Group 16 Nov 21, 2022
Adversarial Autoencoders

Adversarial Autoencoders (with Pytorch) Dependencies argparse time torch torchvision numpy itertools matplotlib Create Datasets python create_datasets

Felipe Ducau 188 Jan 01, 2023
《Single Image Reflection Removal Beyond Linearity》(CVPR 2019)

Single-Image-Reflection-Removal-Beyond-Linearity Paper Single Image Reflection Removal Beyond Linearity. Qiang Wen, Yinjie Tan, Jing Qin, Wenxi Liu, G

Qiang Wen 51 Jun 24, 2022
Implementation of ProteinBERT in Pytorch

ProteinBERT - Pytorch (wip) Implementation of ProteinBERT in Pytorch. Original Repository Install $ pip install protein-bert-pytorch Usage import torc

Phil Wang 92 Dec 25, 2022
Brain tumor detection using Convolution-Neural Network (CNN)

Detect and Classify Brain Tumor using CNN. A system performing detection and classification by using Deep Learning Algorithms using Convolution-Neural Network (CNN).

assia 1 Feb 07, 2022
Lexical Substitution Framework

LexSubGen Lexical Substitution Framework This repository contains the code to reproduce the results from the paper: Arefyev Nikolay, Sheludko Boris, P

Samsung 37 Sep 15, 2022
The official pytorch implementation of our paper "Is Space-Time Attention All You Need for Video Understanding?"

TimeSformer This is an official pytorch implementation of Is Space-Time Attention All You Need for Video Understanding?. In this repository, we provid

Facebook Research 1k Dec 31, 2022
Code and data of the ACL 2021 paper: Few-Shot Text Ranking with Meta Adapted Synthetic Weak Supervision

MetaAdaptRank This repository provides the implementation of meta-learning to reweight synthetic weak supervision data described in the paper Few-Shot

THUNLP 5 Jun 16, 2022
Baseline powergrid model for NY

Baseline-powergrid-model-for-NY Table of Contents About The Project Built With Usage License Contact Acknowledgements About The Project As the urgency

Anderson Energy Lab at Cornell 6 Nov 24, 2022
Minimal deep learning library written from scratch in Python, using NumPy/CuPy.

SmallPebble Project status: experimental, unstable. SmallPebble is a minimal/toy automatic differentiation/deep learning library written from scratch

Sidney Radcliffe 92 Dec 30, 2022
Chinese license plate recognition

AgentCLPR 简介 一个基于 ONNXRuntime、AgentOCR 和 License-Plate-Detector 项目开发的中国车牌检测识别系统。 车牌识别效果 支持多种车牌的检测和识别（其中单层车牌识别效果较好）： 单层车牌： [[[[373, 282], [69, 284],

AgentMaker 26 Dec 25, 2022
An API-first distributed deployment system of deep learning models using timeseries data to analyze and predict systems behaviour

Gordo Building thousands of models with timeseries data to monitor systems. Table of content About Examples Install Uninstall Developer manual How to

Equinor 26 Dec 27, 2022
Fibonacci Method Gradient Descent

An implementation of the Fibonacci method for gradient descent, featuring a TKinter GUI for inputting the function / parameters to be examined and a matplotlib plot of the function and results.

Emma 1 Jan 28, 2022
[Link]deep_portfolo - Use Reforcemet earg ad Supervsed learg to Optmze portfolo allocato []

rl_portfolio This Repository uses Reinforcement Learning and Supervised learning to Optimize portfolio allocation. The goal is to make profitable agen

Deepender Singla 165 Dec 02, 2022