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Open Source Science

https://github.com/cvi-szu/uniface

https://github.com/cvi-szu/uniface

Science Score: 13.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ○
    .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
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    Academic email domains
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (7.0%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

Repository

Basic Info
  • Host: GitHub
  • Owner: CVI-SZU
  • Language: Python
  • Default Branch: main
  • Size: 2.77 MB
Statistics
  • Stars: 39
  • Watchers: 2
  • Forks: 2
  • Open Issues: 7
  • Releases: 0
Created almost 3 years ago · Last pushed over 2 years ago
Metadata Files
Readme

README.md

Introduction

This is the official PyTorch implementation of the ICCV 2023 paper.

UniFace: Unified Cross-Entropy Loss for Deep Face Recognition.pdf

Supplementary.pdf

Get started

Requirement: PyTorch >= 1.8.1

  1. Prepare dataset

    Download CASIA-Webface preprocessed by insightface. console unzip faces_webface_112x112.zip

  2. Train model

    Modify the 'data_path' in train.py (Line 57)

    Select and uncomment the 'loss' in backbone.py (Line 67) console python train.py

  3. Test model console python pytorch2onnx.py zip model.zip model.onnx Upload model.zip to MFR Ongoing and then wait for the results.

    We provide a pre-trained model (ResNet-50) on Google Drive for easy and direct development. This model is trained on CASIA-WebFace and achieved 48.42% on MR-All and 99.56% on LFW.

Citation

If you find UniFace useful in your research, please consider to cite:

bibtex @InProceedings{Zhou_2023_ICCV, author = {Zhou, Jiancan and Jia, Xi and Li, Qiufu and Shen, Linlin and Duan, Jinming}, title = {UniFace: Unified Cross-Entropy Loss for Deep Face Recognition}, booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)}, month = {October}, year = {2023}, pages = {20730-20739} }

Owner

  • Name: Computer Vision Institute, SZU
  • Login: CVI-SZU
  • Kind: organization
  • Location: Shenzhen Univeristy, Shenzhen, China

Computer Vision Institute, Shenzhen University

GitHub Events

Total
  • Watch event: 10
  • Issue comment event: 1
Last Year
  • Watch event: 10
  • Issue comment event: 1

Issues and Pull Requests

Last synced: over 1 year ago

All Time
  • Total issues: 9
  • Total pull requests: 0
  • Average time to close issues: about 23 hours
  • Average time to close pull requests: N/A
  • Total issue authors: 7
  • Total pull request authors: 0
  • Average comments per issue: 1.89
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 6
  • Pull requests: 0
  • Average time to close issues: about 23 hours
  • Average time to close pull requests: N/A
  • Issue authors: 4
  • Pull request authors: 0
  • Average comments per issue: 2.0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
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Top Authors
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  • WisonZ (3)
  • zws98 (1)
  • zhishao (1)
  • Phil-Lin (1)
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