Precision Vehicle Pose Estimation with Uncertainty-aware Neural Network
[ 1 ] Wydział Automatyki, Robotyki i Elektrotechniki, Politechnika Poznańska | [ 2 ] Instytut Robotyki i Inteligencji Maszynowej, Wydział Automatyki, Robotyki i Elektrotechniki, Politechnika Poznańska | [ SzD ] doctoral school student | [ P ] employee
[2.2] Automation, electronics, electrical engineering and space technologies
2024
chapter in monograph / paper
english
- monocular pose estimation
- neural network architecture
- uncertainty-aware pipeline
EN This study presents a neural network designed for precise vehicle pose estimation from single images in complex settings. Utilising neural network backbones known for accurate human pose keypoint detection, our architecture effectively localises vehicle characteristic points. Task-specific modules estimate point coordinates and quality for pose computation. Training on ApolloCar3D with auto-generated 3D labels, our approach achieves the high pose estimation accuracy. We highlight the crucial role of accurate keypoint detection in addressing single-view geometry ambiguities, enhancing pose estimation precision.
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