3D photography using depth inpainting
Layered depth inpainting. (Shih et al., 2020)
Here’s another cool AI art piece that can’t be done justice using just the static screenshot above: Shih et al. (2020) published 3D Photography using Context-aware Layered Depth Inpainting at this year’s CVPR conference. Here’s what that means:
We propose a method for converting a single RGB-D input image into a 3D photo, i.e., a multi-layer representation for novel view synthesis that contains hallucinated color and depth structures in regions occluded in the original view.
Based on a single image (plus depth information), they can generate a 2.5-dimensional representation, realistically re-rendering the scene from slightly different perspectives from which it was originally taken. Contrast that with recent work on neural radiance fields, which requires on the order of 20 - 50 images to work (see DT #36).
Shih et al. set up a website with some fancy demos, which is definitely worth a look; see these gifs on Twitter too. One of the authors also works at Facebook, so I wonder if we’ll one day see Instagram filters with this effect—or if it’ll be a part of Facebook’s virtual reality ambitions. Since the next generation of iPhones will likely have a depth sensor on the back too, I expect we’ll see a lot of this 2.5D photography stuff in the coming years.