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3D-VField: Adversarial Augmentation of Point Clouds for Domain Generalization in 3D Object Detection. (arXiv:2112.04764v2 [cs.CV] UPDATED)
Web: http://arxiv.org/abs/2112.04764
May 4, 2022, 1:12 a.m. | Alexander Lehner, Stefano Gasperini, Alvaro Marcos-Ramiro, Michael Schmidt, Mohammad-Ali Nikouei Mahani, Nassir Navab, Benjamin Busam, Federico Tombar
cs.LG updates on arXiv.org arxiv.org
As 3D object detection on point clouds relies on the geometrical
relationships between the points, non-standard object shapes can hinder a
method's detection capability. However, in safety-critical settings, robustness
to out-of-domain and long-tail samples is fundamental to circumvent dangerous
issues, such as the misdetection of damaged or rare cars. In this work, we
substantially improve the generalization of 3D object detectors to
out-of-domain data by deforming point clouds during training. We achieve this
with 3D-VField: a novel data augmentation method …
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