-
[pdf]
[supp]
[bibtex]@InProceedings{Yang_2024_CVPR, author = {Yang, Yixin and Liang, Jinxiu and Yu, Bohan and Chen, Yan and Ren, Jimmy S. and Shi, Boxin}, title = {Latency Correction for Event-guided Deblurring and Frame Interpolation}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, month = {June}, year = {2024}, pages = {24977-24986} }
Latency Correction for Event-guided Deblurring and Frame Interpolation
Abstract
Event cameras with their high temporal resolution dynamic range and low power consumption are particularly good at time-sensitive applications like deblurring and frame interpolation. However their performance is hindered by latency variability especially under low-light conditions and with fast-moving objects. This paper addresses the challenge of latency in event cameras -- the temporal discrepancy between the actual occurrence of changes in the corresponding timestamp assigned by the sensor. Focusing on event-guided deblurring and frame interpolation tasks we propose a latency correction method based on a parameterized latency model. To enable data-driven learning we develop an event-based temporal fidelity to describe the sharpness of latent images reconstructed from events and the corresponding blurry images and reformulate the event-based double integral model differentiable to latency. The proposed method is validated using synthetic and real-world datasets demonstrating the benefits of latency correction for deblurring and interpolation across different lighting conditions.
Related Material