In this paper, we introduce the first Challenge on Multi-modal Aerial View Object Classification (MAVOC) in conjunction with the NTIRE 2021 workshop at CVPR. This challenge is composed of two different tracks using EO andSAR imagery. Both EO and SAR sensors possess different advantages and drawbacks. The purpose of this competition is to analyze how to use both sets of sensory information in complementary ways. We discuss the top methods submitted for this competition and evaluate their results on our blind test set. Our challenge results show significant improvement of more than 15% accuracy from our current baselines for each track of the competition
@article{arxiv.2107.01189,
title = {NTIRE 2021 Multi-modal Aerial View Object Classification Challenge},
author = {Jerrick Liu and Nathan Inkawhich and Oliver Nina and Radu Timofte and Sahil Jain and Bob Lee and Yuru Duan and Wei Wei and Lei Zhang and Songzheng Xu and Yuxuan Sun and Jiaqi Tang and Xueli Geng and Mengru Ma and Gongzhe Li and Xueli Geng and Huanqia Cai and Chengxue Cai and Sol Cummings and Casian Miron and Alexandru Pasarica and Cheng-Yen Yang and Hung-Min Hsu and Jiarui Cai and Jie Mei and Chia-Ying Yeh and Jenq-Neng Hwang and Michael Xin and Zhongkai Shangguan and Zihe Zheng and Xu Yifei and Lehan Yang and Kele Xu and Min Feng},
journal= {arXiv preprint arXiv:2107.01189},
year = {2022}
}
Comments
The paper needs to be withdrawn since it did not properly go through the public release process. We will soon release a new version to replace this one