We present a user-friendly image editing system that supports a drag-and-drop object insertion (where the user merely drags objects into the image, and the system automatically places them in 3D and relights them appropriately), post-process illumination editing, and depth-of-field manipulation. Underlying our system is a fully automatic technique for recovering a comprehensive 3D scene model (geometry, illumination, diffuse albedo and camera parameters) from a single, low dynamic range photograph. This is made possible by two novel contributions: an illumination inference algorithm that recovers a full lighting model of the scene (including light sources that are not directly visible in the photograph), and a depth estimation algorithm that combines data-driven depth transfer with geometric reasoning about the scene layout. A user study shows that our system produces perceptually convincing results, and achieves the same level of realism as techniques that require significant user interaction.
@article{arxiv.1912.12297,
title = {Automatic Scene Inference for 3D Object Compositing},
author = {Kevin Karsch and Kalyan Sunkavalli and Sunil Hadap and Nathan Carr and Hailin Jin and Rafael Fonte and Michael Sittig},
journal= {arXiv preprint arXiv:1912.12297},
year = {2020}
}