/human-machine-fusion

Repo for the Paper: Tackling Face Verification Edge Cases: In-Depth Analysis and Human-Machine Fusion Approach

Primary LanguageJupyter Notebook

This is the official repository for the paper:

TACKLING FACE VERIFICATION EDGE CASES: IN-DEPTH ANALYSIS AND HUMAN-MACHINE FUSION APPROACH

accepted and published at the MVA Conference 2023, Japan.

Platform

We used the following platform to run the code:

  • Ubuntu 20.04
  • Python 3.8.10
  • NVIDIA GeForce GTX 1070
  • Cuda 11.2

Requirements

Create a virtual environment and install the requirements:

pip install -r requirements.txt

You then need to add the following lines of code to the init.py file in the vit_pytorch site-package folder in your virtual environment:

from vit_pytorch.vit_face import ViT_face
from vit_pytorch.vits_face import ViTs_face

Please also add the files from the vit_pytorch_files/ folder to the vit_pytorch site-package folder in your virtual environment.

Download Datasets & Models

python from utils.helper import * ;download_models(); download_datasets(); extract_datasets()

Issues

  • Memory of mxnet cannot be cleared so you might need to run model inference

Citation

If you find our work useful please consider a citation:

@article{knoche2023tackling,
  title={Tackling Face Verification Edge Cases: In-Depth Analysis and Human-Machine Fusion Approach},
  author={Knoche, Martin and Rigoll, Gerhard},
  journal={arXiv preprint arXiv:2304.08134},
  year={2023}
}