Learning to Refocus with Video Diffusion Models
Focus is a cornerstone of photography, yet autofocus systems often fail to capture the intended subject, and users frequently wish to adjust focus after capture. We introduce a novel method for realistic post-capture refocusing using video diffusion models. From a single defocused image, our approach generates a perceptually accurate focal stack, represented as a video sequence, enabling interactive refocusing and unlocking a range of downstream applications. We release a large-scale focal stack dataset acquired under diverse real-world smartphone conditions to support this work and future research. Our method consistently outperforms existing approaches in both perceptual quality and robustness across challenging scenarios, paving the way for more advanced focus-editing capabilities in everyday photography. Code and data are available at www.learn2refocus.github.io
694c3517746a34b55dd53fb8
SaiKiran Tedla
claimed_verified
2025-12-25T20:43:58.837Z
64fb54957021123688c08959
/avatars/e0fe41e3701bc6eeba7429dbd05a686f.svg
SaiKiran Tedla
tedlasai
user
tedlasai
694c3517746a34b55dd53fb9
Zhoutong Zhang
694c3517746a34b55dd53fba
Xuaner Zhang
694c3517746a34b55dd53fbb
Shumian Xin
Learning to Refocus with Video Diffusion Models
Focus is a cornerstone of photography, yet autofocus systems often fail to capture the intended subject, and users frequently wish to adjust focus after capture. We introduce a novel method for realistic post-capture refocusing using video diffusion models. From a single defocused image, our approach generates a perceptually accurate focal stack, represented as a video sequence, enabling interactive refocusing and unlocking a range of downstream applications. We release a large-scale focal stack dataset acquired under diverse real-world smartphone conditions to support this work and future research. Our method consistently outperforms existing approaches in both perceptual quality and robustness across challenging scenarios, paving the way for more advanced focus-editing capabilities in everyday photography. Code and data are available at www.learn2refocus.github.io