  This paper proposes a practical photometric solution for the challenging
problem of in-the-wild inverse rendering under unknown ambient lighting. Our
system recovers scene geometry and reflectance using only multi-view images
captured by a smartphone. The key idea is to exploit smartphone's built-in
flashlight as a minimally controlled light source, and decompose image
intensities into two photometric components -- a static appearance corresponds
to ambient flux, plus a dynamic reflection induced by the moving flashlight.
Our method does not require flash/non-flash images to be captured in pairs.
Building on the success of neural light fields, we use an off-the-shelf method
to capture the ambient reflections, while the flashlight component enables
physically accurate photometric constraints to decouple reflectance and
illumination. Compared to existing inverse rendering methods, our setup is
applicable to non-darkroom environments yet sidesteps the inherent difficulties
of explicit solving ambient reflections. We demonstrate by extensive
experiments that our method is easy to implement, casual to set up, and
consistently outperforms existing in-the-wild inverse rendering techniques.
Finally, our neural reconstruction can be easily exported to PBR textured
triangle mesh ready for industrial renderers.
