Published January 17, 2020 | Version 12.0.0
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Aerial Single-View Depth Completion with Image-Guided Uncertainty Estimation - Aerial Dataset

Description

This is the Aerial Dataset described in the letter "This work is described in the letter "Aerial Single-View Depth Completion with Image-Guided Uncertainty Estimation", by Lucas Teixeira, Martin R. Oswald, Marc Pollefeys, Margarita Chli, published in the IEEE Robotics and Automation Letters and presented at ICRA 2020.

The dataset was split into 6 tar-files for training and 1 for evaluation. Inside there are multiple sequences of RGB-D images compressed using HDF5. On the GitHub repository below you can find a python reader for the dataset.

The visual-inertial simulator and models that were used to create the dataset and more information are available in https://github.com/VIS4ROB-lab/aerial-depth-completion

The authors thank the creator of the 3D models. The models were downloaded from Sketchfab and all the authors are identified together with the 3D models.

 

Files

Files (149.0 GB)

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md5:42cc0c83c7fe402e2b0c69d3bf65dcdf
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md5:bd6cc60ab7c733b07efb1b71852bb8a6
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20.6 GB Download
md5:3c5fbaf212933d120fa36b0e80c0bad6
21.7 GB Download
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md5:8efd76d7041a3ffa2ca8336aec7dc0ca
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md5:844f8441b6abcf5b7ee88a6ea0b78fd1
28.1 GB Download

Additional details

Funding

Swiss National Science Foundation
NCCR Robotics: Intelligent Robots for Improving the Quality of Life (phase III) 51NF40-185543