Voxel Transformer for 3D Object Detection

Understand

We present Voxel Transformer (VoTr), a novel and effective voxel-based Transformer backbone for 3D object detection from point clouds.

• Conventional 3D convolutional backbones in voxel-based 3D detectors cannot efficiently capture large context information, which is crucial for object recognition and localization, owing to the limited receptive fields.
• In this paper, we resolve the problem by introducing a Transformer-based architecture that enables long-range relationships between voxels by self-attention.
• Given the fact that non-empty voxels are naturally sparse but numerous, directly applying standard Transformer on voxels is non-trivial.