License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/DagRep.12.3.97
URN: urn:nbn:de:0030-drops-172701
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2022/17270/
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Gardner, James ; Egger, Bernhard ; Smith, William ; Theobalt, Christian ; Wuhrer, Stefanie
Weitere Beteiligte (Hrsg. etc.): James Gardner and Bernhard Egger and William Smith and Christian Theobalt and Stefanie Wuhrer

3D Morphable Models and Beyond (Dagstuhl Seminar 22121)

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dagrep_v012_i003_p097_22121.pdf (0.6 MB)

Abstract

3D Morphable Models are models separating shape from appearance variation. Typically, they are used as a statistical prior in computer graphics and vision. Recent success with neural representations have caused a resurgence of interest in visual computing problems, leading to more accurate, higher fidelity, more expressive, and memory-efficient solutions. This report documents the program and the outcomes of Dagstuhl Seminar 22121, "3D Morphable Models and Beyond". This meeting of 39 researchers covered various topics, including 3D morphable models, implicit neural representations, physics-inspired approaches, and more. We summarise the discussions, presentations and results of this workshop.

BibTeX - Entry

@Article{gardner_et_al:DagRep.12.3.97,
  author =	{Gardner, James and Egger, Bernhard and Smith, William and Theobalt, Christian and Wuhrer, Stefanie},
  title =	{{3D Morphable Models and Beyond (Dagstuhl Seminar 22121)}},
  pages =	{97--116},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2022},
  volume =	{12},
  number =	{3},
  editor =	{Gardner, James and Egger, Bernhard and Smith, William and Theobalt, Christian and Wuhrer, Stefanie},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2022/17270},
  URN =		{urn:nbn:de:0030-drops-172701},
  doi =		{10.4230/DagRep.12.3.97},
  annote =	{Keywords: 3D Computer Vision, Generative Models, Neural Rendering, Implicit Representations, Computer Graphics, Statistical Modelling}
}

Keywords: 3D Computer Vision, Generative Models, Neural Rendering, Implicit Representations, Computer Graphics, Statistical Modelling
Collection: DagRep, Volume 12, Issue 3
Issue Date: 2022
Date of publication: 14.11.2022

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