Zero-Shot Depth from Defocus

Yiming Zuo* · Hongyu Wen* · Venkat Subramanian* · Patrick Chen · Karhan Kayan · Mario Bijelic · Felix Heide · Jia Deng

(*Equal Contribution)

Princeton Vision & Learning Lab (PVL)

Paper · Project

Overview

We captured 100 focus stacks in 100 unique scenes, covering various indoor and outdoor locations, such as classrooms, hallways, robotics labs, offices, kitchens, and gardens, providing a diverse scene coverage.

For each focus stack, we capture images at 9 focus distances, ranging from 0.82 to 8.10m. We capture at 5 larger apertures (F1.4/2.0/2.8/4.0/5.6), and a small aperture (F16) for all-in-focus images, resulting in 6 x 9=54 images in total for each scene. This rich combination of focus distances and apertures allows us to study the sensitivity of the models' performance to each factor.

We provide a dense ground-truth depth map for each scene under the resolution of 1824 x 1216, captured with a high-accuracy Lidar.

— Paper (arXiv)

### Data Structure ZEDD contains 100 scenes divided into validation and test sets. For each scene, the data is organized as follows: ```text ZEDD/ ├── test/ │ ├── test_0001/ │ │ ├── focus_stack/ │ │ │ ├── img_run_1_motor_6D3E_aperture_F1.4.jpg │ │ │ ├── img_run_1_motor_6D3E_aperture_F2.0.jpg │ │ │ └── ... │ │ └── gt/ │ │ └── K.txt │ └── ... └── val/ ├── val_0001/ │ ├── focus_stack/ │ │ ├── img_run_1_motor_6D3E_aperture_F1.4.jpg │ │ ├── img_run_1_motor_6D3E_aperture_F2.0.jpg │ │ └── ... │ └── gt/ │ ├── depth_vis.jpg │ ├── depth.npy │ ├── K.txt │ └── overlay.jpg └── ... ``` ## Citation ```bibtex @article{ZeroShotDepthFromDefocus, author = {Zuo, Yiming and Wen, Hongyu and Subramanian, Venkat and Chen, Patrick and Kayan, Karhan and Bijelic, Mario and Heide, Felix and Deng, Jia}, title = {Zero-Shot Depth from Defocus}, journal = {arXiv preprint arXiv:2603.26658}, year = {2026}, url = {https://arxiv.org/abs/2603.26658} } ```