TL;DR该论文提出了一种从单张图像中推断物体的 3D 形状和姿态的学习方法，利用无定型图像集的分割输出进行监督，并采用体素表示和网格化表示相结合的方式进行形状-姿态分解和实例重建。
Abstract
We aim to infer 3d shape and pose of object from a single image and propose a learning-based approach that can train from unstructured image collections, supervised by only segmentation outputs from off-the-shelf