Telescope: Learnable Hyperbolic Foveation for Ultra-Long-Range Object Detection
Autonomous highway driving, especially for long-haul heavy trucks, requires detecting objects at long ranges beyond 500 meters to satisfy braking distance requirements at high speeds. At long distances, vehicles and other critical objects occupy only a few pixels in high-resolution images, causing state-of-the-art object detectors to fail. This challenge is compounded by the limited effective range of commercially available LiDAR sensors, which fall short of ultra-long range thresholds because of quadratic loss of resolution with distance, making image-based detection the most practically scalable solution given commercially available sensor constraints. We introduce Telescope, a two-stag...
| Authors | Parker Ewen, Dmitriy Rivkin, Mario Bijelic et al. |
|---|---|
| Primary category | cs.CV |
| Published | 7 April 2026 |
| Last updated at source | 7 April 2026 |
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