Tex2Shape: Detailed Full Human Body Geometry From a Single Image
This provides a solution for applications in computer graphics and virtual reality by enabling detailed 3D reconstruction from minimal input, though it is incremental as it builds on existing texture mapping and image-to-image translation techniques.
The paper tackles the problem of inferring detailed full human body geometry from a single image, achieving results that include occluded parts and details like wrinkles at interactive frame-rates.
We present a simple yet effective method to infer detailed full human body shape from only a single photograph. Our model can infer full-body shape including face, hair, and clothing including wrinkles at interactive frame-rates. Results feature details even on parts that are occluded in the input image. Our main idea is to turn shape regression into an aligned image-to-image translation problem. The input to our method is a partial texture map of the visible region obtained from off-the-shelf methods. From a partial texture, we estimate detailed normal and vector displacement maps, which can be applied to a low-resolution smooth body model to add detail and clothing. Despite being trained purely with synthetic data, our model generalizes well to real-world photographs. Numerous results demonstrate the versatility and robustness of our method.