@inproceedings{
maurel2023rototranslation,
title={Roto-translation Equivariant {YOLO} for Aerial Images},
author={Benjamin Maurel and Samy Blusseau and Santiago Velasco-Forero and Teodora Petrisor},
booktitle={NeurIPS 2023 Workshop on Symmetry and Geometry in Neural Representations},
year={2023},
url={https://openreview.net/forum?id=EoyeHdfJ6l}
}
This work introduces Eq-YOLO, an Equivariant One-Stage Object Detector based on YOLO-v8 incorporating group convolutions to handle rotational transformations. We show the interest of using equivariant-transforms to improve the detection performance on rotated data over the regular YOLO-v8 model while dividing the number of parameters to train by a factor greater than three.
Roto-translation Equivariant YOLO for Aerial Images
Benjamin Maurel Samy Blusseau Santiago Velasco-Forero Teodora Petrisor