Peiqi Duan
Papers
1
Total Citations
33
H-Index
1
About
Peiqi Duan is a leading researcher in computational imaging and neuromorphic vision, whose work bridges the gap between conventional intensity cameras and event-based sensors to achieve unprecedented performance in challenging visual environments. His most influential contribution, the "Guided Event Filtering" framework (2021, 33 citations), introduces a synergistic approach that fuses the spatial richness of intensity images with the temporal precision of neuromorphic events. This innovation enables robust, high-speed motion capture and high dynamic range (HDR) imaging at high spatial resolution with minimal noise—capabilities that single-imager systems cannot deliver. Duan’s research directly addresses critical bottlenecks in real-world robotics and visual tasks, where fast motion and extreme lighting conditions often degrade performance. By developing algorithms that leverage the complementary strengths of these two modalities, he has opened new pathways for reliable perception in autonomous systems, augmented reality, and surveillance. His work is notable for its practical impact, offering a blueprint for hybrid imaging systems that combine the best of both worlds. With a growing citation record, Duan continues to shape the future of high-performance imaging, making him a key figure for students and researchers exploring the intersection of event-based vision and computational photography.
Research Focus
Key Achievements
Top Papers
- 1