NTIRE 2021 Multi-Modal Aerial View Object Classification Challenge

Jerrick Liu, Nathan Inkawhich, Oliver Nina, Radu Timofte; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2021, pp. 588-595

Abstract

In this paper, we introduce the first Challenge on Multimodal Aerial View Object Classification (MAVOC) in conjunction with the NTIRE 2021 workshop at CVPR. This challenge is composed of two different tracks using EO and SAR 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.

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[bibtex]
@InProceedings{Liu_2021_CVPR, author = {Liu, Jerrick and Inkawhich, Nathan and Nina, Oliver and Timofte, Radu}, title = {NTIRE 2021 Multi-Modal Aerial View Object Classification Challenge}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2021}, pages = {588-595} }