Weakly Supervised Multi-Modal 3D Human Body Pose Estimation for Autonomous Driving
Bauer P, Bouazizi A, Kressel U, Flohr FB (2023)
Publication Type: Conference contribution
Publication year: 2023
Publisher: Institute of Electrical and Electronics Engineers Inc.
Book Volume: 2023-June
Conference Proceedings Title: IEEE Intelligent Vehicles Symposium, Proceedings
Event location: Anchorage, AK, USA
ISBN: 9798350346916
DOI: 10.1109/IV55152.2023.10186575
Abstract
Accurate 3D human pose estimation (3D HPE) is crucial for enabling autonomous vehicles (AVs) to make informed decisions and respond proactively in critical road scenarios. Promising results of 3D HPE have been gained in several domains such as human-computer interaction, robotics, sports and medical analytics, often based on data collected in well-controlled laboratory environments. Nevertheless, the transfer of 3D HPE methods to AVs has received limited research attention, due to the challenges posed by obtaining accurate 3D pose annotations and the limited suitability of data from other domains.We present a simple yet efficient weakly supervised approach for 3D HPE in the AV context by employing a high-level sensor fusion between camera and LiDAR data. The weakly supervised setting enables training on the target datasets without any 2D / 3D keypoint labels by using an off-the-shelf 2D joint extractor and pseudo labels generated from LiDAR to image projections. Our approach outperforms state-of-the-art results by up to ~ 13% on the Waymo Open Dataset in the weakly supervised setting and achieves state-of-the-art results in the supervised setting.
Authors with CRIS profile
Involved external institutions
Universität Stuttgart
Germany (DE)
Universität Ulm
Germany (DE)
Hochschule für angewandte Wissenschaften München
Germany (DE)
Germany (DE)
Universität Ulm
Germany (DE)
Hochschule für angewandte Wissenschaften München
Germany (DE)
How to cite
APA:
Bauer, P., Bouazizi, A., Kressel, U., & Flohr, F.B. (2023). Weakly Supervised Multi-Modal 3D Human Body Pose Estimation for Autonomous Driving. In IEEE Intelligent Vehicles Symposium, Proceedings. Anchorage, AK, USA: Institute of Electrical and Electronics Engineers Inc..
MLA:
Bauer, Peter, et al. "Weakly Supervised Multi-Modal 3D Human Body Pose Estimation for Autonomous Driving." Proceedings of the 34th IEEE Intelligent Vehicles Symposium, IV 2023, Anchorage, AK, USA Institute of Electrical and Electronics Engineers Inc., 2023.
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