Record link: 
http://hdl.handle.net/20.500.12708/229459
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Title: 
Synthetic Skeletal Pose Pre-training to Mitigate Data Scarcity in In-Cabin 2D-to-3D Pose Lifting
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Citation: 
Kunanuntakij, T., Schörkhuber, D., & Gelautz, M. (2026). Synthetic Skeletal Pose Pre-training to Mitigate Data Scarcity in In-Cabin 2D-to-3D Pose Lifting. In Proceedings of the Austrian Symposium on AI, Robotics, and Vision 2026 (pp. 119–124).
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Publication Type: 
Inproceedings - Full-Paper Contribution
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Language: 
English
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Authors: 
Kunanuntakij, Thummanoon 
Schörkhuber, Dominik 
Gelautz, Margrit 
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Organisational Unit: 
E193-01 - Forschungsbereich Computer Vision 
E056-19 - Fachbereich Precision Livestock Farming 
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Published in: 
Proceedings of the Austrian Symposium on AI, Robotics, and Vision 2026 
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Date (published): 
10-Apr-2026
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Event name: 
AIRoV - Austrian Symposium on AI, Robotics, and Vision 2026 
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Event date: 
13-Apr-2026 - 15-Apr-2026
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Event place: 
Leoben, Austria
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Number of Pages: 
6
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Peer reviewed: 
Yes
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Keywords: 
Computer Vision; Driver Monitoring; Human Pose Estimation; Synthetic Data
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Project title: 
UNIversal Single Camera-based 3D Sensing for COmprehensive Human PErception: 911019 (FFG - Österr. Forschungsförderungs- gesellschaft mbH) 
Simulation von Fahrzeuginnenräumen für die effiziente Entwicklung von Driver/Occupant Monitoring Systemen: 884336 (FFG - Österr. Forschungsförderungs- gesellschaft mbH) 
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Research Areas: 
Visual Computing and Human-Centered Technology: 100%
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Science Branch: 
1020 - Informatik: 100%
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Appears in Collections:
Conference Paper

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