Abstract:3D computer vision models are commonly used in security-critical applications such as autonomous driving and surgical robotics. Emerging concerns over the robustness of these models against real-world deformations must be addressed practically and reliably. In this work, we propose 3DeformRS, a method to certify the robustness of point cloud Deep Neural Networks (DNNs) against realworld deformations. We developed 3DeformRS by building upon recent work that generalized Randomized Smoothing (RS) from pixel-inten… Show more
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