Coded Event Focal Stack for Continuous Refocusing in Dynamic Scene

Traditional cameras face limitations in maintaining focus across dynamic scenes, especially during rapid motion, due to the constraints of their lenses. Post-capture refocusing techniques, including deep learning-based methods and light field cameras, have been explored to mitigate these challenges. However, these approaches frequently struggle with temporal consistency or experience a trade-off in spatial resolution. In this paper, we introduce the coded event focal stack, a novel approach that captures both motion and depth information through event streams recorded during a modulated focal sweep. Our coded event focal stack enables the generation of full-time intermediate frames refocused at arbitrary focal distances. Extensive experiments on both synthetic and real-world datasets demonstrate the superior refocusing capability of our method over state-of-the-art techniques, particularly in dynamic scenes with complex motion and depth variations.