Fisheye Evaluation Suite
FES is an indoor data set that can be used for evaluation of deep learning approaches and is part of the publication THEODORE accepted by the WACV.
If you are interested please contact: roman.seidel@…
Dataset Details
- Resolution
- 1680 x 1680 Pixel
- Number of Images
- 301
- Classes
- 6 - Armchair, TV, Table, Chair, Person, Wheeled Walker
- Segmentation Masks
- Yes
- Bounding Boxes
- Yes
If you use the data set in your work, please do not forget the following reference:
@inproceedings{scheck2020theodore,
title={Learning from THEODORE: A Synthetic Omnidirectional Top-View Indoor Dataset for Deep Transfer Learning},
author={Tobias Scheck and Roman Seidel and Gangolf Hirtz},
booktitle={2020 IEEE Winter Conference on Applications of Computer Vision (WACV)},
year={2020}
}