ICCV 2025poster0 citations

Spatially-Varying Autofocus

Yingsi Qin, Aswin C. Sankaranarayanan, Matthew O'Toole

Abstract

A lens brings a single plane into focus on a planar sensor; hence, parts of the scene that are outside this planar focus plane are resolved on the sensor under defocus. Can we break this precept by enabling a "lens" that can change its depth-of-field arbitrarily? This work investigates the design and implementation of such a computational lens with spatially-selective focusing. Our design uses an optical arrangement of a Lohmann lens and a phase-only spatial light modulator to allow each pixel to focus at a different depth. We extend classical techniques used in autofocusing to the spatially-varying scenario where the depth map is iteratively estimated using contrast and disparity cues, enabling the camera to progressively shape its depth-of-field to the scene's depth. By obtaining an optical all-in-focus image, our technique advances upon a broad swathe of prior work ranging from depth-from-focus/defocus to coded aperture techniques in two key aspects: the ability to bring an entire scene in focus simultaneously, and the ability to maintain the highest possible spatial resolution.

BibTeX
@InProceedings{Qin_2025_ICCV,
    author    = {Qin, Yingsi and Sankaranarayanan, Aswin C. and O'Toole, Matthew},
    title     = {Spatially-Varying Autofocus},
    booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
    month     = {October},
    year      = {2025},
    pages     = {24645-24654}
}
Spatially-Varying Autofocus · ICCV 2025