Skip to Main Content
This paper introduces an approach to predict the three-dimensional shape of an object belonging to a specific class of shapes shown in an input image. We use suggestive contour, a shape-suggesting image feature developed in computer graphics in the context of non-photorealistic rendering, to reconstruct 3D shapes. We learn a functional mapping from the shape space of suggestive contours to the space of 3D shapes and use this mapping to predict 3D shapes based on a single input image. We demonstrate that the method can be used to predict the shape of deformable objects and to predict the shape of human faces using synthetic experiments and experiments based on artist drawn sketches and photographs.