Methods › Computer Vision › 3D Object Detection Models › VoTr
Voxel Transformer
VoTr
Introduced by Jiageng Mao et al. in Voxel Transformer for 3D Object Detection
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
VoTr is a Transformer-based 3D backbone for 3D object detection from point clouds. It contains a series of sparse and submanifold voxel modules. Submanifold voxel modules perform multi-head self-attention strictly on the non-empty voxels, while sparse voxel modules can extract voxel features at empty locations. Long-range relationships between voxels are captured via self-attention.
Given the fact that non-empty voxels are naturally sparse but numerous, directly applying standard Transformer on voxels is non-trivial. To this end, VoTr uses a sparse voxel module and a submanifold voxel module, which can operate on the empty and non-empty voxel positions effectively. To further enlarge the attention range while maintaining comparable computational overhead to the convolutional counterparts, two attention mechanisms are used for multi-head attention in those two modules: Local Attention and Dilated Attention. Furthermore Fast Voxel Query is used to accelerate the querying process in multi-head attention.
Papers archive 2025-07-28
1 shown of 1, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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Voxel Transformer for 3D Object Detection 6 Sep 2021 · 1 repository · arXiv:2109.02497Syntology ran 0 of 7 samples · 7 unverified · 7 pointer-only (licence)
Tasks archive 2025-07-28
6 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| 3D Object Detection | 1 |
| Computational Efficiency | 1 |
| Object | 1 |
| Object Detection | 1 |
| Object Recognition | 1 |
| object-detection | 1 |
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections