Perceiving Systems, Computer Vision

DART: Articulated Hand Model with Diverse Accessories and Rich Textures

2022

Conference Paper

ps

Hand, the bearer of human productivity and intelligence, is receiving much attention due to the recent fever of 3D digital avatars. Among different hand morphable models, MANO has been widely used in various vision & graphics tasks. However, MANO disregards textures and accessories, which largely limits its power to synthesize photorealistic & lifestyle hand data. In this paper, we extend MANO with more Diverse Accessories and Rich Textures, namely DART. DART is comprised of 325 exquisite hand-crafted texture maps which vary in appearance and cover different kinds of blemishes, make-ups, and accessories. We also provide the Unity GUI which allows people to render hands with user-specific settings, e.g. pose, camera, background, lighting, and DART textures. In this way, we generate large-scale (800K), diverse, and high-fidelity hand images, paired with perfect-aligned 3D labels, called DARTset. Experiments demonstrate its superiority in generalization and diversity. As a great complement to existing datasets, DARTset could boost hand pose estimation & surface reconstruction tasks. DART and Unity software will be publicly available for research purposes.

Author(s): Daiheng Gao* and Yuliang Xiu* and Kailin Li* and Lixin Yang* and Feng Wang and Peng Zhang and Bang Zhang and Cewu Lu and Ping Tan
Book Title: Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS)
Year: 2022
Month: November
Department(s): Perceiving Systems
Bibtex Type: Conference Paper (conference)
Paper Type: Conference
Event Name: NeurIPS 2022-Datasets and Benchmarks Track
Event Place: New Orleans, Louisiana
State: In press
Additional (custom) Fields:
title: {DART: Articulated Hand Model with Diverse Accessories and Rich Textures}
author: Gao, Daiheng and Xiu, Yuliang and Li, Kailin and Yang, Lixin and Wang, Feng and Zhang, Peng and Zhang, Bang and Lu, Cewu and Tan, Ping
booktitle: Thirty-sixth Conference on Neural Information Processing Systems Datasets and Benchmarks Track
year: 2022
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BibTex 

@conference{dart2022,
  title = {{DART}: {A}rticulated {H}and {M}odel with {D}iverse {A}ccessories and {R}ich {T}extures},
  author = {Gao*, Daiheng and Xiu*, Yuliang and Li*, Kailin and Yang*, Lixin and Wang, Feng and Zhang, Peng and Zhang, Bang and Lu, Cewu and Tan, Ping},
  booktitle = {Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS)},
  month = nov,
  year = {2022},
  doi = {},
  month_numeric = {11}
}