PiLoT: Neural Pixel-to-3D Registration for UAV-based Ego and Target Geo-localization
We present PiLoT, a unified framework that tackles UAV-based ego and target geo-localization. Conventional approaches rely on decoupled pipelines that fuse GNSS and Visual-Inertial Odometry (VIO) for ego-pose estimation, and active sensors like laser rangefinders for target localization. However, these methods are susceptible to failure in GNSS-denied environments and incur substantial hardware costs and complexity. PiLoT breaks this paradigm by directly registering live video stream against a geo-referenced 3D map. To achieve robust, accurate, and real-time performance, we introduce three key contributions: 1) a Dual-Thread Engine that decouples map rendering from core localization threa...
| Authors | Xiaoya Cheng, Long Wang, Yan Liu et al. |
|---|---|
| Primary category | cs.CV |
| Published | 21 March 2026 |
| Last updated at source | 27 March 2026 |
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