[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
Implementation of TabTransformer, attention network for tabular data, in Pytorch

Tab Transformer Implementation of Tab Transformer, attention network for tabular data, in Pytorch. This simple architecture came within a hair's bread

Phil Wang 420 Jan 05, 2023
Restricted Boltzmann Machines in Python.

How to Use First, initialize an RBM with the desired number of visible and hidden units. rbm = RBM(num_visible = 6, num_hidden = 2) Next, train the m

Edwin Chen 928 Dec 30, 2022
List some popular DeepFake models e.g. DeepFake, FaceSwap-MarekKowal, IPGAN, FaceShifter, FaceSwap-Nirkin, FSGAN, SimSwap, CihaNet, etc.

deepfake-models List some popular DeepFake models e.g. DeepFake, CihaNet, SimSwap, FaceSwap-MarekKowal, IPGAN, FaceShifter, FaceSwap-Nirkin, FSGAN, Si

Mingcan Xiang 100 Dec 17, 2022
Official Chainer implementation of GP-GAN: Towards Realistic High-Resolution Image Blending (ACMMM 2019, oral)

GP-GAN: Towards Realistic High-Resolution Image Blending (ACMMM 2019, oral) [Project] [Paper] [Demo] [Related Work: A2RL (for Auto Image Cropping)] [C

Wu Huikai 402 Dec 27, 2022
Pytorch implementation for "Adversarial Robustness under Long-Tailed Distribution" (CVPR 2021 Oral)

Adversarial Long-Tail This repository contains the PyTorch implementation of the paper: Adversarial Robustness under Long-Tailed Distribution, CVPR 20

Tong WU 89 Dec 15, 2022
JAX code for the paper "Control-Oriented Model-Based Reinforcement Learning with Implicit Differentiation"

Optimal Model Design for Reinforcement Learning This repository contains JAX code for the paper Control-Oriented Model-Based Reinforcement Learning wi

Evgenii Nikishin 43 Sep 28, 2022
An official implementation of the paper Exploring Sequence Feature Alignment for Domain Adaptive Detection Transformers

Sequence Feature Alignment (SFA) By Wen Wang, Yang Cao, Jing Zhang, Fengxiang He, Zheng-jun Zha, Yonggang Wen, and Dacheng Tao This repository is an o

WangWen 79 Dec 24, 2022
GLaRA: Graph-based Labeling Rule Augmentation for Weakly Supervised Named Entity Recognition

GLaRA: Graph-based Labeling Rule Augmentation for Weakly Supervised Named Entity Recognition

Xinyan Zhao 29 Dec 26, 2022
PyTorch implementation of the paper Ultra Fast Structure-aware Deep Lane Detection

PyTorch implementation of the paper Ultra Fast Structure-aware Deep Lane Detection

1.4k Jan 06, 2023
PyTorch implementation of Neural View Synthesis and Matching for Semi-Supervised Few-Shot Learning of 3D Pose

Neural View Synthesis and Matching for Semi-Supervised Few-Shot Learning of 3D Pose Release Notes The official PyTorch implementation of Neural View S

Angtian Wang 20 Oct 09, 2022
An open-source online reverse dictionary.

An open-source online reverse dictionary.

THUNLP 6.3k Jan 09, 2023
As-ViT: Auto-scaling Vision Transformers without Training

As-ViT: Auto-scaling Vision Transformers without Training [PDF] Wuyang Chen, Wei Huang, Xianzhi Du, Xiaodan Song, Zhangyang Wang, Denny Zhou In ICLR 2

VITA 68 Sep 05, 2022
NeuTex: Neural Texture Mapping for Volumetric Neural Rendering

NeuTex: Neural Texture Mapping for Volumetric Neural Rendering Paper: https://arxiv.org/abs/2103.00762 Running Run on the provided DTU scene cd run ba

Fanbo Xiang 67 Dec 28, 2022
The code for 'Deep Residual Fourier Transformation for Single Image Deblurring'

Deep Residual Fourier Transformation for Single Image Deblurring Xintian Mao, Yiming Liu, Wei Shen, Qingli Li and Yan Wang News 2021.12.5 Release Deep

145 Jan 05, 2023
Weakly Supervised Posture Mining with Reverse Cross-entropy for Fine-grained Classification

Fine-grainedImageClassification Weakly Supervised Posture Mining with Reverse Cross-entropy for Fine-grained Classification We trained model here: lin

ZhenchaoTang 14 Oct 21, 2022
Official implementation of "Towards Good Practices for Efficiently Annotating Large-Scale Image Classification Datasets" (CVPR2021)

Towards Good Practices for Efficiently Annotating Large-Scale Image Classification Datasets This is the official implementation of "Towards Good Pract

Sanja Fidler's Lab 52 Nov 22, 2022
这是一个yolox-keras的源码，可以用于训练自己的模型。

YOLOX：You Only Look Once目标检测模型在Keras当中的实现 目录 性能情况 Performance 实现的内容 Achievement 所需环境 Environment 小技巧的设置 TricksSet 文件下载 Download 训练步骤 How2train 预测步骤 Ho

Bubbliiiing 64 Nov 10, 2022
Pytorch implementation of the paper "Class-Balanced Loss Based on Effective Number of Samples"

Class-balanced-loss-pytorch Pytorch implementation of the paper Class-Balanced Loss Based on Effective Number of Samples presented at CVPR'19. Yin Cui

Vandit Jain 697 Dec 29, 2022
PPO Lagrangian in JAX

PPO Lagrangian in JAX This repository implements PPO in JAX. Implementation is tested on the safety-gym benchmark. Usage Install dependencies using th

Karush Suri 2 Sep 14, 2022
A Simplied Framework of GAN Inversion

Framework of GAN Inversion Introcuction You can implement your own inversion idea using our repo. We offer a full range of tuning settings (in hparams

Kangneng Zhou 13 Sep 27, 2022