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20202025
most citedSCANimate: Weakly Supervised Learning of Skinned Clothed Avatar Networks

5 citations · 6 across the 3 of their papers we have counts for

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cs.CV2022

Capturing and Animation of Body and Clothing from Monocular Video

Yao Feng, Jinlong Yang, Marc Pollefeys +2

While recent work has shown progress on extracting clothed 3D human avatars from a single image, video, or a set of 3D scans, several limitations remain. Most methods use a holisti…

cs.CV2022

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…

cs.CV2021

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…

cs.CV2021

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…

cs.CV20215 cited

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…

cs.CV2020

Grasping Field: Learning Implicit Representations for Human Grasps

Korrawe Karunratanakul, Jinlong Yang, Yan Zhang +3

Robotic grasping of house-hold objects has made remarkable progress in recent years. Yet, human grasps are still difficult to synthesize realistically. There are several key reason…