/async-ev-cnn

Code for the paper "Asynchronous Convolutional Networks for Object Detection in Neuromorphic Cameras"

Primary LanguagePythonMIT LicenseMIT

Asynchronous Convolutional Networks for Object Detection in Neuromorphic Cameras

Code for the CVPR2019 Event-based Vision Workshop paper "A Differentiable Recurrent Surface for Asynchronous Event-Based Data"
Authors: Marco Cannici, Marco Ciccone, Andrea Romanoni, Matteo Matteucci

Citing:

If you use this work for research, please cite our accompanying CVPR2019 Event-based Vision Workshop paper:

@inproceedings{cannici2019asynchronous,
  title={Asynchronous Convolutional Networks for Object Detection in Neuromorphic Cameras},
  author={Cannici, Marco and Ciccone, Marco and Romanoni, Andrea and Matteucci, Matteo},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year={2019}
}

Requirements

  • TensorFlow 1.4.0
  • Cython extensions: build_setup.sh

You can create a conda environment to run the code as it follows:

conda create -n aync-ev-cnn python=3.6`
conda activate aync-ev-cnn
conda env update -f=requirements.yml
python cython_setup.py build_ext --inplace

Run scripts

  • To check event layers equivalence (no dataset or checkpoint required):
    python src/scripts/test_correctness.py

  • To run network predictions on a dataset (select the proper .yml file):