SparseVoxelDet: Fully Sparse Voxel Networks for Efficient Event-Based Drone Detection
Event cameras excel at detecting small, fast drones, but today's detectors give away their key advantage: they convert the sparse event stream into dense grids and pay dense-processing cost on inputs that are almost entirely empty. We present SparseVoxelDet, to our knowledge the first coordinate-sparse 3D event voxel bounding-box detector: backbone, feature pyramid, temporal reduction, and detection head all operate directly on coordinate-indexed features, with no dense spatial grid at any stage. Building it exposed a hidden failure mode we name support inflation: an input filling a median 0.0652% of the voxel lattice inflates stage by stage until standard pyramid fusion leaves the detect...
| Authors | Mohamad Yazan Sadoun, Sarah Sharif, Yaser Mike Banad |
|---|---|
| Primary category | cs.CV |
| Published | 23 March 2026 |
| Last updated at source | 7 August 2026 |
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