This repository contains the model weights for the paper
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. This work introduces a novel method for realistic post-capture refocusing using video diffusion models. From a single defocused image, the approach generates a perceptually accurate focal stack, represented as a video sequence, enabling interactive refocusing and unlocking a range of downstream applications.
For detailed environment setup, training, and testing instructions, please refer to the official
GitHub repository. The model utilizes fine-tuned Stable Video Diffusion (SVD) weights.
If you use our dataset, code, or model in your research, please cite the following paper:
1@inproceedings{Tedla2025Refocus,
2 title={{Learning to Refocus with Video Diffusion Models}},
3 author={{Tedla, SaiKiran and Zhang, Zhoutong and Zhang, Xuaner and Xin, Shumian}},
4 booktitle={{Proceedings of the ACM SIGGRAPH Asia Conference}},
5 year={{2025}}
6}
