Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Tiwari, Garvita"'
Faithfully modeling the space of articulations is a crucial task that allows recovery and generation of realistic poses, and remains a notorious challenge. To this end, we introduce Neural Riemannian Distance Fields (NRDFs), data-driven priors modeli
Externí odkaz:
http://arxiv.org/abs/2403.03122
3D Clothing modeling and datasets play crucial role in the entertainment, animation, and digital fashion industries. Existing work often lacks detailed semantic understanding or uses synthetic datasets, lacking realism and personalization. To address
Externí odkaz:
http://arxiv.org/abs/2401.12051
Autor:
Tiwari, Garvita, Antic, Dimitrije, Lenssen, Jan Eric, Sarafianos, Nikolaos, Tung, Tony, Pons-Moll, Gerard
Publikováno v:
European Conference on Computer Vision (ECCV 2022), Oral Presentation
We present Pose-NDF, a continuous model for plausible human poses based on neural distance fields (NDFs). Pose or motion priors are important for generating realistic new poses and for reconstructing accurate poses from noisy or partial observations.
Externí odkaz:
http://arxiv.org/abs/2207.13807
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, we learn to animate the character for new poses. Existing methods hav
Externí odkaz:
http://arxiv.org/abs/2108.08807
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 3D clothing conditioned on human body shape and garment size parameter
Externí odkaz:
http://arxiv.org/abs/2007.11610
We present Multi-Garment Network (MGN), a method to predict body shape and clothing, layered on top of the SMPL model from a few frames (1-8) of a video. Several experiments demonstrate that this representation allows higher level of control when com
Externí odkaz:
http://arxiv.org/abs/1908.06903
Publikováno v:
2015 Eighth International Conference on Contemporary Computing (IC3); 2015, p144-149, 6p
