NTIRE 2021 Multi-modal Aerial View Object Classification Challenge

07/02/2021

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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 our current baselines for each track of the competition

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NTIRE 2021 Multi-modal Aerial View Object Classification Challenge

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Code Repositories

ntire2021-sar

NTIRE 2021 Multi-modal Aerial View Object Classification Challenge

Related Research

The Multi-Modal Video Reasoning and Analyzing Competition

Multi-Modal Domain Fusion for Multi-modal Aerial View Object Classification

Roof material classification from aerial imagery

Scene Clustering Based Pseudo-labeling Strategy for Multi-modal Aerial View Object Classification

Truly Multi-modal YouTube-8M Video Classification with Video, Audio, and Text

AIM 2019 Challenge on Image Demoireing: Dataset and Study

Evaluating the Apperception Engine

Code Repositories

ntire2021-sar