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Authors: Ankit Sonthalia 1 ; 2 ; Ramy Battrawy 1 ; René Schuster 1 and Didier Stricker 1

Affiliations: 1 German Research Center for Artificial Intelligence (DFKI GmbH), Kaiserslautern, Germany ; 2 Tübingen AI Center, Eberhard Karls Universität Tübingen, Germany

Keyword(s): LiDAR, Point Cloud, Event Camera, Bi-Directional Fusion, Attention, Scene Flow.

Abstract: In this paper, we propose the fusion of event streams and point clouds for scene flow estimation. Bio-inspired event cameras offer significantly lower latency and higher dynamic ranges than regular RGB cameras, and are therefore appropriate for recording high-speed motions. However, events do not provide depth information, which makes them unsuitable for scene flow (3D) estimation. On the other hand, LiDAR-based approaches are well suited to scene flow estimation due to the high precision of LiDAR measurements for outdoor scenes (e.g. autonomous vehicle applications) but they fail in the presence of unstructured regions (e.g. ground surface, grass, walls, etc.). We propose our EvLiDAR-Flow, a neural network architecture equipped with an attention module for bi-directional feature fusion between an event (2D) branch and a point cloud (3D) branch. This kind of fusion helps to overcome the lack of depth information in events while enabling the LiDAR-based scene flow branch to benefit fr om the rich motion information encoded by events. We validate the proposed EvLiDAR-Flow by showing that it performs significantly better and is robust to the presence of ground points, in comparison to a state-of-the-art LiDAR-only scene flow estimation method. (More)

CC BY-NC-ND 4.0

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Paper citation in several formats:
Sonthalia, A.; Battrawy, R.; Schuster, R. and Stricker, D. (2023). EvLiDAR-Flow: Attention-Guided Fusion Between Point Clouds and Events for Scene Flow Estimation. In Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-626-2; ISSN 2184-4313, SciTePress, pages 733-742. DOI: 10.5220/0011615900003411

@conference{icpram23,
author={Ankit Sonthalia. and Ramy Battrawy. and René Schuster. and Didier Stricker.},
title={EvLiDAR-Flow: Attention-Guided Fusion Between Point Clouds and Events for Scene Flow Estimation},
booktitle={Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2023},
pages={733-742},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011615900003411},
isbn={978-989-758-626-2},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - EvLiDAR-Flow: Attention-Guided Fusion Between Point Clouds and Events for Scene Flow Estimation
SN - 978-989-758-626-2
IS - 2184-4313
AU - Sonthalia, A.
AU - Battrawy, R.
AU - Schuster, R.
AU - Stricker, D.
PY - 2023
SP - 733
EP - 742
DO - 10.5220/0011615900003411
PB - SciTePress