16 citations · 35 across the 8 of their papers we have counts for
9 papers
BodyMap: Learning Full-Body Dense Correspondence Map
Anastasia Ianina, Nikolaos Sarafianos, Yuanlu Xu +2
Dense correspondence between humans carries powerful semantic information that can be utilized to solve fundamental problems for full-body understanding such as in-the-wild surface…
SPAMs: Structured Implicit Parametric Models
Pablo Palafox, Nikolaos Sarafianos, Tony Tung +1
Parametric 3D models have formed a fundamental role in modeling deformable objects, such as human bodies, faces, and hands; however, the construction of such parametric models requ…
Neural-GIF: Neural Generalized Implicit Functions for Animating People in Clothing
Garvita Tiwari, Nikolaos Sarafianos, Tony Tung +1
We present Neural Generalized Implicit Functions(Neural-GIF), to animate people in clothing as a function of the body pose. Given a sequence of scans of a subject in various poses,…
Semi-supervised Synthesis of High-Resolution Editable Textures for 3D Humans
Bindita Chaudhuri, Nikolaos Sarafianos, Linda Shapiro +1
We introduce a novel approach to generate diverse high fidelity texture maps for 3D human meshes in a semi-supervised setup. Given a segmentation mask defining the layout of the se…
TexMesh: Reconstructing Detailed Human Texture and Geometry from RGB-D Video
Tiancheng Zhi, Christoph Lassner, Tony Tung +3
We present TexMesh, a novel approach to reconstruct detailed human meshes with high-resolution full-body texture from RGB-D video. TexMesh enables high quality free-viewpoint rende…
SIZER: A Dataset and Model for Parsing 3D Clothing and Learning Size Sensitive 3D Clothing
Garvita Tiwari, Bharat Lal Bhatnagar, Tony Tung +1
While models of 3D clothing learned from real data exist, no method can predict clothing deformation as a function of garment size. In this paper, we introduce SizerNet to predict…