PVT-SSD: Single-Stage 3D Object Detector with Point-Voxel Transformer. (arXiv:2305.06621v1 [cs.CV])

Recent Transformer-based 3D object detectors learn point cloud features
either from point- or voxel-based representations. However, the former requires
time-consuming sampling while the latter introduces quantization errors. In
this paper, we present a novel Point-Voxel Transformer for single-stage 3D
detection (PVT-SSD) that takes advantage of these two representations.
Specifically, we first use voxel-based sparse convolutions for efficient
feature encoding. Then, we propose a Point-Voxel Transformer (PVT) module that
obtains long-range contexts in a cheap manner from voxels while attaining
accurate …

arxiv cloud detection errors features learn novel paper quantization sampling ssd stage transformer voxel