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20192024
most citedMetaAvatar: Learning Animatable Clothed Human Models from Few Depth Images

48 citations · 56 across the 8 of their papers we have counts for

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Showing 2021Show all

5 papers · 1 filter

cs.CV2021★ 1 cited

EgoBody: Human Body Shape and Motion of Interacting People from Head-Mounted Devices

Siwei Zhang, Qianli Ma, Yan Zhang +5

Understanding social interactions from egocentric views is crucial for many applications, ranging from assistive robotics to AR/VR. Key to reasoning about interactions is to unders…

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★ 48 cited

MetaAvatar: Learning Animatable Clothed Human Models from Few Depth Images

Shaofei Wang, Marko Mihajlovic, Qianli Ma +2

In this paper, we aim to create generalizable and controllable neural signed distance fields (SDFs) that represent clothed humans from monocular depth observations. Recent advances…

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.CV2021★ 5 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…