Web: http://arxiv.org/abs/2201.12733

June 16, 2022, 1:13 a.m. | Wenda Chu, Linyi Li, Bo Li

cs.CV updates on arXiv.org arxiv.org

Point cloud models with neural network architectures have achieved great
success and have been widely used in safety-critical applications, such as
Lidar-based recognition systems in autonomous vehicles. However, such models
are shown vulnerable to adversarial attacks which aim to apply stealthy
semantic transformations such as rotation and tapering to mislead model
predictions. In this paper, we propose a transformation-specific smoothing
framework TPC, which provides tight and scalable robustness guarantees for
point cloud models against semantic transformation attacks. We first categorize …

arxiv cloud cv models transformation

More from arxiv.org / cs.CV updates on arXiv.org

Machine Learning Researcher - Saalfeld Lab

@ Howard Hughes Medical Institute - Chevy Chase, MD | Ashburn, Virginia

Project Director, Machine Learning in US Health

@ ideas42.org | Remote, US

Data Science Intern

@ NannyML | Remote

Machine Learning Engineer NLP/Speech

@ Play.ht | Remote

Research Scientist, 3D Reconstruction

@ Yembo | Remote, US

Clinical Assistant or Associate Professor of Management Science and Systems

@ University at Buffalo | Buffalo, NY