Spatio-Temporal Difference Guided Motion Deblurring with the Complementary Vision Sensor
Motion blur arises when rapid scene changes occur during the exposure period, collapsing rich intra-exposure motion into a single RGB frame. Without explicit structural or temporal cues, RGB-only deblurring is highly ill-posed and often fails under extreme motion. Inspired by the human visual system, brain-inspired vision sensors introduce temporally dense information to alleviate this problem. However, event cameras still suffer from event rate saturation under rapid motion, while the event modality entangles edge features and motion cues, which limits their effectiveness. As a recent breakthrough, the complementary vision sensor (CVS), Tianmouc, captures synchronized RGB frames together...
| Authors | Yapeng Meng, Lin Yang, Yuguo Chen et al. |
|---|---|
| Primary category | cs.CV |
| Published | 12 April 2026 |
| Last updated at source | 12 April 2026 |
Models and datasets referencing this paper
- mypThu/SportsSlomo-CVSDataset
- mypThu/CVSRealDeblurDataDataset
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