Boundary-aided Human Body Shape and Pose Estimation from a Single Image for Garment Design and Manufacture

The template can then be used to recover dense 3D shape very efficiently from affine image motion via unambiguous planar pose estimation combined with surface

The main purpose of this paper consists of demonstrating advantages of using implicit filtering schemes (non- causal IIR filters, in the signal processing language) for some basic

[SBB07] use a Shape Con- text driven pose reconstruction as a prior for optimizing body shape parameters (using SCAPE) to find a best fitting pose and body shape from a single

Fortunately, in garment fit- ting a human model is a usually watertight surface, and body sur- face normals always point to the outside so that no cloth vertices are allowed to

Based on its color map shading representation, we propose a simple method to decompose the input shading to a smooth shape with a nonlinear reflectance property.. We have

There are many factors that come into play when creating such a dataset such as the artistic quality of the reference garment design, the resolution of the mesh, the versatility of

In the case of using the proposed network including the pose estimation part, we used 256 × 256 images as input be- cause the size of the input image must be power of two so that

Considering the scenario of virtual dressing where people are usually in stable poses, we define a stable pose prior from CMU motion capture (mocap) dataset for further