图形学学术速递[1.10]
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cs.GR图形学，共计3篇
【1】 Embodied Hands: Modeling and Capturing Hands and Bodies Together
标题：具体化的手：一起建模和捕捉手和身体
链接：https://arxiv.org/abs/2201.02610
备注：None
摘要：Humans move their hands and bodies together to communicate and solve tasks.
Capturing and replicating such coordinated activity is critical for virtual
characters that behave realistically. Surprisingly, most methods treat the 3D
modeling and tracking of bodies and hands separately. Here we formulate a model
of hands and bodies interacting together and fit it to full-body 4D sequences.
When scanning or capturing the full body in 3D, hands are small and often
partially occluded, making their shape and pose hard to recover. To cope with
low-resolution, occlusion, and noise, we develop a new model called MANO (hand
Model with Articulated and Non-rigid defOrmations). MANO is learned from around
1000 high-resolution 3D scans of hands of 31 subjects in a wide variety of hand
poses. The model is realistic, low-dimensional, captures non-rigid shape
changes with pose, is compatible with standard graphics packages, and can fit
any human hand. MANO provides a compact mapping from hand poses to pose blend
shape corrections and a linear manifold of pose synergies. We attach MANO to a
standard parameterized 3D body shape model (SMPL), resulting in a fully
articulated body and hand model (SMPL+H). We illustrate SMPL+H by fitting
complex, natural, activities of subjects captured with a 4D scanner. The
fitting is fully automatic and results in full body models that move naturally
with detailed hand motions and a realism not seen before in full body
performance capture. The models and data are freely available for research
purposes in our website (http://mano.is.tue.mpg.de).
【2】 As-Continuous-As-Possible Ceramics Printing for Shell Models
标题：贝壳模型的尽可能连续的陶瓷印刷
链接：https://arxiv.org/abs/2201.02374
备注：15 pages, 21 figures
摘要：We propose a novel computational framework for fabricating thin shell models
on an extrusion-based Cartesian 3D printer with the clay material.
Extrusion-based ceramics printing involves several inevitable challenges to
achieve acceptable print quality, including continuous toolpath with the
minimal number of transfer moves, separation of non-model and model structures,
etc. Inertia of the extruded material may damage the surface quality during
transfer moves. The viscosity also makes support material hard to remove. These
challenges even increase for thin shell surfaces, as both sides are of visual
significance, making it impossible to hide any intermediate structures in the
interiors. To conquer these challenges, we adopt a curved layer scheme for
ceramics printing. Then we introduce an original criterion "one-path patch"
(OPP), for representing a shell surface patch that can be traversed in one path
in the context of curved layer printing considering fabrication constraints. We
propose a bottom-up OPP merging procedure for decomposing the given shell
surface into a minimal number of OPPs and generating the
"as-continuous-as-possible" (ACAP) toolpath. Furthermore, we customize the path
planning algorithm with a decoupled orientation and support structures
computation method. Results demonstrate that our ACAP algorithm prints shell
models with both efficiency and surface quality.
【3】 Deep Generative Framework for Interactive 3D Terrain Authoring and Manipulation
标题：交互式三维地形创作和操纵的深度生成框架
链接：https://arxiv.org/abs/2201.02369
摘要：Automated generation and (user) authoring of the realistic virtual terrain is
most sought for by the multimedia applications like VR models and gaming. The
most common representation adopted for terrain is Digital Elevation Model
(DEM). Existing terrain authoring and modeling techniques have addressed some
of these and can be broadly categorized as: procedural modeling, simulation
method, and example-based methods. In this paper, we propose a novel realistic
terrain authoring framework powered by a combination of VAE and generative
conditional GAN model. Our framework is an example-based method that attempts
to overcome the limitations of existing methods by learning a latent space from
a real-world terrain dataset. This latent space allows us to generate multiple
variants of terrain from a single input as well as interpolate between terrains
while keeping the generated terrains close to real-world data distribution. We
also developed an interactive tool, that lets the user generate diverse
terrains with minimalist inputs. We perform thorough qualitative and
quantitative analysis and provide comparisons with other SOTA methods. We
intend to release our code/tool to the academic community.
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