Does Computer Vision Matter for Action? was published in Science Robotics. The paper studies whether explicit intermediate representations of the kind studied in computer vision help action. We probe this question via controlled experiments in immersive simulation. Our main finding is that computer vision does matter. Models equipped with intermediate representations train faster, achieve higher task performance, and generalize better to previously unseen environments.
Paper accepted to SIGGRAPH 2019
Posted on May 5, 2019
The paper A Learned Shape-Adaptive Subsurface Scattering Model was accepted to SIGGRAPH 2019.