Deblurring Low-Light Images with Events
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition,Software
Link
https://link.springer.com/content/pdf/10.1007/s11263-023-01754-5.pdf
Reference91 articles.
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2. Barrios-Avilés, J., Rosado-Muñoz, A., Medus, L. D., Bataller-Mompeán, M., & Guerrero-Martínez, J. F. (2018). Less data same information for event-based sensors: A bioinspired filtering and data reduction algorithm. Sensors, 18(12), 4122.
3. Boracchi, G., & Foi, A. (2012). Modeling the performance of image restoration from motion blur. IEEE Transactions on Image Processing, 21(8), 3502–3517.
4. Brandli, C., Berner, R., Yang, M., Liu, S. C., & Delbruck, T. (2014). A 240 $$\times $$ 180 130 dB 3 $$\mu $$s latency global shutter spatiotemporal vision sensor. IEEE Journal of Solid-State Circuits, 49(10), 2333–2341.
5. Chakrabarti, A. (2016). A neural approach to blind motion deblurring. In: Proceedings of European conference on computer vision, pp. 221–235.
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