Thanks @_akhaliq for tweeting our work! It has been shown in our prior work Zero123 that Stable Diffusion has learned powerful visual priors that can be serve as the foundation of zero-shot generalization ability for many vision tasks. In our recent work pix2gestalt, we show that Stable Diffusion, when finetuned on the task of amodal segmentation, performs incredibly well on data far outside of training distribution. We've demonstrated that this model can serves as a unified solution for occlusion reasoning, benefiting many other tasks whose performance is greatly hindered by occlusion in images such as recognition, novel view synthesis, 3D reconstruction etc. Work led by Ege Ozguroglu who is currently applying for PhD!