5 citations · 5 across the 2 of their papers we have counts for
7 papers
Neural Point-based Shape Modeling of Humans in Challenging Clothing
Qianli Ma, Jinlong Yang, Michael J. Black +1
Parametric 3D body models like SMPL only represent minimally-clothed people and are hard to extend to clothing because they have a fixed mesh topology and resolution. To address th…
The Power of Points for Modeling Humans in Clothing
Qianli Ma, Jinlong Yang, Siyu Tang +1
Currently it requires an artist to create 3D human avatars with realistic clothing that can move naturally. Despite progress on 3D scanning and modeling of human bodies, there is s…
SCALE: Modeling Clothed Humans with a Surface Codec of Articulated Local Elements
Qianli Ma, Shunsuke Saito, Jinlong Yang +2
Learning to model and reconstruct humans in clothing is challenging due to articulation, non-rigid deformation, and varying clothing types and topologies. To enable learning, the c…
SCANimate: Weakly Supervised Learning of Skinned Clothed Avatar Networks
Shunsuke Saito, Jinlong Yang, Qianli Ma +1
We present SCANimate, an end-to-end trainable framework that takes raw 3D scans of a clothed human and turns them into an animatable avatar. These avatars are driven by pose parame…
PLACE: Proximity Learning of Articulation and Contact in 3D Environments
Siwei Zhang, Yan Zhang, Qianli Ma +2
High fidelity digital 3D environments have been proposed in recent years, however, it remains extremely challenging to automatically equip such environment with realistic human bod…
Learning to Dress 3D People in Generative Clothing
Qianli Ma, Jinlong Yang, Anurag Ranjan +4
Three-dimensional human body models are widely used in the analysis of human pose and motion. Existing models, however, are learned from minimally-clothed 3D scans and thus do not…