Large-Scale Pre-training for Person Re-identification with Noisy Labels (LUPerson-NL)

Overview

LUPerson-NL

Large-Scale Pre-training for Person Re-identification with Noisy Labels (LUPerson-NL)

The repository is for our CVPR2022 paper Large-Scale Pre-training for Person Re-identification with Noisy Labels.

LUPerson-NL Dataset

LUPerson-NL is currently the largest noisy annotated Person Re-identification dataset without humuan labelling efforts, which is used for Pre-training. LUPerson-NL consists of 10M images of over 430K identities extracted from 21K street-view videos and covers a much diverse range of capturing environments.

Details can be found at ./LUP-NL.

Pre-trained Models

Model link
ResNet50 R50 code:pr50
ResNet101 R101 code:r101
ResNet152 R152 code:r152

Finetuned Results

For MGN with ResNet50:

Dataset mAP cmc1 link
MSMT17 68.0 86.0 -
DukeMTMC 84.3 92.0 -
Market1501 91.9 96.6 -
CUHK03-L 80.4 80.9 -

For MGN with ResNet101:

Dataset mAP cmc1 path
MSMT17 70.8 87.1 -
DukeMTMC 85.5 92.8 -
Market1501 92.5 96.9 -
CUHK03-L 80.5 81.2 -

For MGN with ResNet152:

Dataset mAP cmc1 path
MSMT17 71.6 87.5 -
DukeMTMC 85.6 92.4 -
Market1501 92.7 96.8 -
CUHK03-L 80.6 81.2 -

Citation

If you find this code useful for your research, please cite our paper.

@article{fu2020unsupervised,
  title={Unsupervised Pre-training for Person Re-identification},
  author={Fu, Dengpan and Chen, Dongdong and Bao, Jianmin and Yang, Hao and Yuan, Lu and Zhang, Lei and Li, Houqiang and Chen, Dong},
  journal={Proceedings of the IEEE conference on computer vision and pattern recognition},
  year={2021}
}
@article{fu2022large,
  title={Large-Scale Pre-training for Person Re-identification with Noisy Labels},
  author={Fu, Dengpan and Chen, Dongdong and Yang, Hao and Bao, Jianmin and Yuan, Lu and Zhang, Lei and Li, Houqiang and Wen, Fang and Chen, Dong},
  journal={arXiv preprint arXiv:2203.16533},
  year={2022}
}
Image-to-Image Translation in PyTorch

CycleGAN and pix2pix in PyTorch New: Please check out contrastive-unpaired-translation (CUT), our new unpaired image-to-image translation model that e

Jun-Yan Zhu 19k Jan 07, 2023
Classification Modeling: Probability of Default

Credit Risk Modeling in Python Introduction: If you've ever applied for a credit card or loan, you know that financial firms process your information

Aktham Momani 2 Nov 07, 2022
Official PyTorch implementation of "Camera Distance-aware Top-down Approach for 3D Multi-person Pose Estimation from a Single RGB Image", ICCV 2019

PoseNet of "Camera Distance-aware Top-down Approach for 3D Multi-person Pose Estimation from a Single RGB Image" Introduction This repo is official Py

Gyeongsik Moon 677 Dec 25, 2022
The Deep Learning with Julia book, using Flux.jl.

Deep Learning with Julia DL with Julia is a book about how to do various deep learning tasks using the Julia programming language and specifically the

Logan Kilpatrick 67 Dec 25, 2022
NHL 94 AI contests

nhl94-ai The end goals of this project is to: Train Models that play NHL 94 Support AI vs AI contests in NHL 94 Provide an improved AI opponent for NH

Mathieu Poliquin 2 Dec 06, 2021
Official PyTorch implementation of "AASIST: Audio Anti-Spoofing using Integrated Spectro-Temporal Graph Attention Networks"

AASIST This repository provides the overall framework for training and evaluating audio anti-spoofing systems proposed in 'AASIST: Audio Anti-Spoofing

Clova AI Research 56 Jan 02, 2023
Notebooks for my "Deep Learning with TensorFlow 2 and Keras" course

Deep Learning with TensorFlow 2 and Keras – Notebooks This project accompanies my Deep Learning with TensorFlow 2 and Keras trainings. It contains the

Aurélien Geron 1.9k Dec 15, 2022
WarpDrive: Extremely Fast End-to-End Deep Multi-Agent Reinforcement Learning on a GPU

WarpDrive is a flexible, lightweight, and easy-to-use open-source reinforcement learning (RL) framework that implements end-to-end multi-agent RL on a single GPU (Graphics Processing Unit).

Salesforce 334 Jan 06, 2023
LiDAR R-CNN: An Efficient and Universal 3D Object Detector

LiDAR R-CNN: An Efficient and Universal 3D Object Detector Introduction This is the official code of LiDAR R-CNN: An Efficient and Universal 3D Object

TuSimple 295 Jan 05, 2023
An implementation of quantum convolutional neural network with MindQuantum. Huawei, classifying MNIST dataset

关于实现的一点说明 山东大学 2020级 苏博南 www.subonan.com 文件说明 tools.py 这里面主要有两个函数: resize(a, lenb) 这其实是我找同学写的一个小算法hhh。给出一个$28\times 28$的方阵a,返回一个$lenb\times lenb$的方阵。因

ぼっけなす 2 Aug 29, 2022
PESTO: Switching Point based Dynamic and Relative Positional Encoding for Code-Mixed Languages

PESTO: Switching Point based Dynamic and Relative Positional Encoding for Code-Mixed Languages Abstract NLP applications for code-mixed (CM) or mix-li

Mohsin Ali, Mohammed 1 Nov 12, 2021
Transformers provides thousands of pretrained models to perform tasks on different modalities such as text, vision, and audio.

English | 简体中文 | 繁體中文 | 한국어 State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow 🤗 Transformers provides thousands of pretrained models

Clara Meister 50 Nov 12, 2022
CLUES: Few-Shot Learning Evaluation in Natural Language Understanding

CLUES: Few-Shot Learning Evaluation in Natural Language Understanding This repo contains the data and source code for baseline models in the NeurIPS 2

Microsoft 29 Dec 29, 2022
The code for the CVPR 2021 paper Neural Deformation Graphs, a novel approach for globally-consistent deformation tracking and 3D reconstruction of non-rigid objects.

Neural Deformation Graphs Project Page | Paper | Video Neural Deformation Graphs for Globally-consistent Non-rigid Reconstruction Aljaž Božič, Pablo P

Aljaz Bozic 134 Dec 16, 2022
Code for the submitted paper Surrogate-based cross-correlation for particle image velocimetry

Surrogate-based cross-correlation (SBCC) This repository contains code for the submitted paper Surrogate-based cross-correlation for particle image ve

5 Jun 30, 2022
Developed an optimized algorithm which finds the most optimal path between 2 points in a 3D Maze using various AI search techniques like BFS, DFS, UCS, Greedy BFS and A*

Developed an optimized algorithm which finds the most optimal path between 2 points in a 3D Maze using various AI search techniques like BFS, DFS, UCS, Greedy BFS and A*. The algorithm was extremely

1 Mar 28, 2022
Official code for the paper "Why Do Self-Supervised Models Transfer? Investigating the Impact of Invariance on Downstream Tasks".

Why Do Self-Supervised Models Transfer? Investigating the Impact of Invariance on Downstream Tasks This repository contains the official code for the

Linus Ericsson 11 Dec 16, 2022
Crowd-Kit is a powerful Python library that implements commonly-used aggregation methods for crowdsourced annotation and offers the relevant metrics and datasets

Crowd-Kit: Computational Quality Control for Crowdsourcing Documentation Crowd-Kit is a powerful Python library that implements commonly-used aggregat

Toloka 125 Dec 30, 2022
nfelo: a power ranking, prediction, and betting model for the NFL

nfelo nfelo is a power ranking, prediction, and betting model for the NFL. Nfelo take's 538's Elo framework and further adapts it for the NFL, hence t

6 Nov 22, 2022
Learning Off-Policy with Online Planning, CoRL 2021

LOOP: Learning Off-Policy with Online Planning Accepted in Conference of Robot Learning (CoRL) 2021. Harshit Sikchi, Wenxuan Zhou, David Held Paper In

Harshit Sikchi 24 Nov 22, 2022