UAV Video Deblurring via Motion-Aware Diffusion: A Path to Robust Target Detection
Unmanned Aerial Vehicles (UAVs) play a crucial role in various scenarios ranging from disaster response to traffic surveillance. However, aerial video footage often suffers from severe motion blur due to rapid flight maneuvers, vibrations, and camera panning, which can significantly degrade downstream tasks such as target detection. Our goal is to explore a computationally-efficient and effective video deblurring approach to enhance UAV target detection performance. To reduce computational cost, we first propose an Adaptive Latent Scale Selector that dynamically adjusts the latent space resolution according to the intensity of UAV motion, thus balancing detail preservation with inference ...
| Authors | Zhiqiang Hu, Shouren Huang, Masatoshi Ishikawa |
|---|---|
| Primary category | cs.CV |
| Published | 15 August 2026 |
| Last updated at source | 15 August 2026 |
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