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A Surface Subdivision Scheme Based on Four-Directional S¹3 Non-Box Splines

COMPUTER GRAPHICS FORUM 2023年第7期42卷 e14933-e14933页

作者： Huang, Z. Univ Sci & Technol China Langfang Hebei Peoples R China Anhui Prov Key Lab Software Comp & Commun Hefei Anhui Peoples R China USTC Deqing Alpha Innovat Res Inst Huzhou Peoples R China

In this paper, we propose a novel surface subdivision scheme called non-box subdivision, which is generalized from four-directional S-3(1) non-box splines. The resulting subdivision surfaces achieve C-1 continuity with the convex hull property. This scheme can be regarded as either a four-directional subdivision or a special quadrilateral subdivision. When used as a quadrilateral subdivision, the proposed scheme can control the shape of the limit surface more flexibly than traditional schemes due to the natural introduction of auxiliary face control vertices.

关键词： CCS Concepts center dot computing methodologies -> shape modeling

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Interactive Editing of Discrete Chebyshev Nets

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COMPUTER GRAPHICS FORUM 2022年第2期41卷 111-120页

作者： Li, Rui-Zeng Guo, Jia-Peng Wang, Qi Chai, Shuangming Liu, Ligang Fu, Xiao-Ming Univ Sci & Technol China Hefei Anhui Peoples R China

We propose an interactive method to edit a discrete Chebyshev net, which is a quad mesh with edges of the same length. To ensure that the edited mesh is always a discrete Chebyshev net, the maximum difference of all edge lengths should be zero during the editing process. Hence, we formulate an objective function using l(p)-norm (p > 2) to force the maximum length deviation to approach zero in practice. To optimize the nonlinear and non-convex objective function interactively and efficiently, we develop a novel second-order solver. The core of the solver is to construct a new convex majorizer for our objective function to achieve fast convergence. We present two acceleration strategies to further reduce the optimization time, including adaptive p change and adaptive variables reduction. A large number of experiments demonstrate the capability and feasibility of our method for interactively editing complex discrete Chebyshev nets.

关键词： CCS Concepts center dot computing methodologies -> shape modeling

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Deep Reconstruction of 3D Smoke Densities from Artist Sketches

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COMPUTER GRAPHICS FORUM 2022年第2期41卷 97-110页

作者： Kim, Byungsoo Huang, Xingchang Wuelfroth, Laura Tang, Jingwei Cordonnier, Guillaume Gross, Markus Solenthaler, Barbara Swiss Fed Inst Technol Zurich Switzerland Max Planck Inst Informat Munich Germany Univ Cote Azur Inria Nice France

Creative processes of artists often start with hand-drawn sketches illustrating an object. Pre-visualizing these keyframes is especially challenging when applied to volumetric materials such as smoke. The authored 3D density volumes must capture realistic flow details and turbulent structures, which is highly non-trivial and remains a manual and time-consuming process. We therefore present a method to compute a 3D smoke density field directly from 2D artist sketches, bridging the gap between early-stage prototyping of smoke keyframes and pre-visualization. From the sketch inputs, we compute an initial volume estimate and optimize the density iteratively with an updater CNN. Our differentiable sketcher is embedded into the end-to-end training, which results in robust reconstructions. Our training data set and sketch augmentation strategy are designed such that it enables general applicability. We evaluate the method on synthetic inputs and sketches from artists depicting both realistic smoke volumes and highly non-physical smoke shapes. The high computational performance and robustness of our method at test time allows interactive authoring sessions of volumetric density fields for rapid prototyping of ideas by novice users.

关键词： CCS Concepts center dot computing methodologies -> shape modeling Neural networks

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Closed space-filling curves with controlled orientation for 3D printing

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COMPUTER GRAPHICS FORUM 2022年第2期41卷 473-492页

作者： Bedel, A. Coudert-Osmont, Y. Martinez, J. Nishat, R. I. Whitesides, S. Lefebvre, S. Univ Lorraine CNRS INRIA LORIA Nancy France Ryerson Univ Toronto ON Canada Univ Victoria Victoria BC Canada

We explore the optimization of closed space-filling curves under orientation objectives. By solidifying material along the closed curve, solid layers of 3D prints can be manufactured in a single continuous extrusion motion. The control over orientation enables the deposition to align with specific directions in different areas, or to produce a locally uniform distribution of orientations, patterning the solidified volume in a precisely controlled manner. Our optimization framework proceeds in two steps. First, we cast a combinatorial problem, optimizing Hamiltonian cycles within a specially constructed graph. We rely on a stochastic optimization process based on local operators that modify a cycle while preserving its Hamiltonian property. Second, we use the result to initialize a geometric optimizer that improves the smoothness and uniform coverage of the cycle while further optimizing for alignment and orientation objectives.

关键词： CCS Concepts center dot computing methodologies -> shape modeling center dot Applied computing -> Computer-aided design

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Differentiable 3D CAD Programs for Bidirectional Editing

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COMPUTER GRAPHICS FORUM 2022年第2期41卷 309-323页

作者： Cascaval, D. Shalah, M. Quinn, P. Bodik, R. Agrawala, M. Schulz, A. Univ Washington Seattle WA 98195 USA Stanford Univ Stanford CA 94305 USA

Modern CAD tools represent 3D designs not only as geometry, but also as a program composed of geometric operations, each of which depends on a set of parameters. Program representations enable meaningful and controlled shape variations via parameter changes. However, achieving desired modifications solely through parameter editing is challenging when CAD models have not been explicitly authored to expose select degrees of freedom in advance. We introduce a novel bidirectional editing system for 3D CAD programs. In addition to editing the CAD program, users can directly manipulate 3D geometry and our system infers parameter updates to keep both representations in sync. We formulate inverse edits as a set of constrained optimization objectives, returning plausible updates to program parameters that both match user intent and maintain program validity. Our approach implements an automatically differentiable domain-specific language for CAD programs, providing derivatives for this optimization to be performed quickly on any expressed program. Our system enables rapid, interactive exploration of a constrained 3D design space by allowing users to manipulate the program and geometry interchangeably during design iteration. While our approach is not designed to optimize across changes in geometric topology, we show it is expressive and performant enough for users to produce a diverse set of design variants, even when the CAD program contains a relatively large number of parameters.

关键词： CCS Concepts center dot computing methodologies -> shape modeling Graphics systems and interfaces

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Automatic Differentiable Procedural modeling

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COMPUTER GRAPHICS FORUM 2022年第2期41卷 289-307页

作者： Gaillard, Mathieu Krs, Vojtech Gori, Giorgio Mech, Radomir Benes, Bedrich Purdue Univ Comp Sci W Lafayette IN 47907 USA Adobe Res San Jose CA USA

Procedural modeling allows for an automatic generation of large amounts of similar assets, but there is limited control over the generated output. We address this problem by introducing Automatic Differentiable Procedural modeling (ADPM). The forward procedural model generates a final editable model. The user modifies the output interactively, and the modifications are transferred back to the procedural model as its parameters by solving an inverse procedural modeling problem. We present an auto-differentiable representation of the procedural model that significantly accelerates optimization. In ADPM the procedural model is always available, all changes are non-destructive, and the user can interactively model the 3D object while keeping the procedural representation. ADPM provides the user with precise control over the resulting model comparable to non-procedural interactive modeling. ADPM is node-based, and it generates hierarchical 3D scene geometry converted to a differentiable computational graph. Our formulation focuses on the differentiability of high-level primitives and bounding volumes of components of the procedural model rather than the detailed mesh geometry. Although this high-level formulation limits the expressiveness of user edits, it allows for efficient derivative computation and enables interactivity. We designed a new optimizer to solve for inverse procedural modeling. It can detect that an edit is under-determined and has degrees of freedom. Leveraging cheap derivative evaluation, it can explore the region of optimality of edits and suggest various configurations, all of which achieve the requested edit differently. We show our system's efficiency on several examples, and we validate it by a user study.

关键词： CCS Concepts center dot computing methodologies -> shape modeling Interactive simulation

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Gradient Terrain Authoring

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COMPUTER GRAPHICS FORUM 2022年第2期41卷 85-95页

作者： Guerin, Eric Peytavie, Adrien Masnou, Simon Digne, Julie Sauvage, Basile Gain, James Galin, Eric Univ Lyon INSA Lyon CNRS UCBLLIRISUMR5205 F-69621 Villeurbanne France Univ Lyon UCBL CNRS UMR 5208 Inst Camille Jordan F-69622 Villeurbanne France Univ Strasbourg CNRS ICube UMR 7357 Strasbourg France Univ Cape Town Cape Town South Africa

Digital terrains are a foundational element in the computer-generated depiction of natural scenes. Given the variety and complexity of real-world landforms, there is a need for authoring solutions that achieve perceptually realistic outcomes without sacrificing artistic control. In this paper, we propose setting aside the elevation domain in favour of modelling in the gradient domain. Such a slope-based representation is height independent and allows a seamless blending of disparate landforms from procedural, simulation, and real-world sources. For output, an elevation model can always be recovered using Poisson reconstruction, which can include Dirichlet conditions to constrain the elevation of points and curves. In terms of authoring our approach has numerous benefits. It provides artists with a complete toolbox, including: cut-and-paste operations that support warping as needed to fit the destination terrain, brushes to modify region characteristics, and sketching to provide point and curve constraints on both elevation and gradient. It is also a unifying representation that enables the inclusion of tools from the spectrum of existing procedural and simulation methods, such as painting localised high-frequency noise or hydraulic erosion, without breaking the formalism. Finally, our constrained reconstruction is GPU optimized and executes in real-time, which promotes productive cycles of iterative authoring.

关键词： CCS Concepts center dot computing methodologies -> shape modeling

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shape Transformers: Topology-Independent 3D shape Models Using Transformers

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COMPUTER GRAPHICS FORUM 2022年第2期41卷 195-207页

作者： Chandran, Prashanth Zoss, Gaspard Gross, Markus Gotardo, Paulo Bradley, Derek Swiss Fed Inst Technol Zurich Switzerland DisneyRes Studios Zurich Switzerland

Parametric 3D shape models are heavily utilized in computer graphics and vision applications to provide priors on the observed variability of an object's geometry (e.g., for faces). Original models were linear and operated on the entire shape at once. They were later enhanced to provide localized control on different shape parts separately. In deep shape models, nonlinearity was introduced via a sequence of fully-connected layers and activation functions, and locality was introduced in recent models that use mesh convolution networks. As common limitations, these models often dictate, in one way or another, the allowed extent of spatial correlations and also require that a fixed mesh topology be specified ahead of time. To overcome these limitations, we present shape Transformers, a new nonlinear parametric 3D shape model based on transformer architectures. A key benefit of this new model comes from using the transformer's self-attention mechanism to automatically learn nonlinear spatial correlations for a class of 3D shapes. This is in contrast to global models that correlate everything and local models that dictate the correlation extent. Our transformer 3D shape autoencoder is a better alternative to mesh convolution models, which require specially-crafted convolution, and down/up-sampling operators that can be difficult to design. Our model is also topologically independent: it can be trained once and then evaluated on any mesh topology, unlike most previous methods. We demonstrate the application of our model to different datasets, including 3D faces, 3D hand shapes and full human bodies. Our experiments demonstrate the strong potential of our shape Transformer model in several applications in computer graphics and vision.

关键词： CCS Concepts center dot computing methodologies -> shape modeling modeling methodologies

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MoCo-Flow: Neural Motion Consensus Flow for Dynamic Humans in Stationary Monocular Cameras

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COMPUTER GRAPHICS FORUM 2022年第2期41卷 147-161页

作者： Chen, Xuelin Li, Weiyu Cohen-Or, Daniel Mitra, Niloy J. Chen, Baoquan Tencent AI Lab Bellevue WA 98004 USA Shandong Univ Jinan Peoples R China Tel Aviv Univ Tel Aviv Israel UCL London England Adobe Res San Jose CA USA Peking Univ CFCS Beijing Peoples R China

Synthesizing novel views of dynamic humans from stationary monocular cameras is a specialized but desirable setup. This is particularly attractive as it does not require static scenes, controlled environments, or specialized capture hardware. In contrast to techniques that exploit multi-view observations, the problem of modeling a dynamic scene from a single view is significantly more under-constrained and ill-posed. In this paper, we introduce Neural Motion Consensus Flow (MoCo-Flow), a representation that models dynamic humans in stationary monocular cameras using a 4D continuous time-variant function. We learn the proposed representation by optimizing for a dynamic scene that minimizes the total rendering error, over all the observed images. At the heart of our work lies a carefully designed optimization scheme, which includes a dedicated initialization step and is constrained by a motion consensus regularization on the estimated motion flow. We extensively evaluate MoCo-Flow on several datasets that contain human motions of varying complexity, and compare, both qualitatively and quantitatively, to several baselines and ablated variations of our methods, showing the efficacy and merits of the proposed approach. Pretrained model, code, and data will be released for research purposes upon paper acceptance.

关键词： CCS Concepts center dot computing methodologies -> shape modeling Rendering

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VRSurf: Surface Creation from Sparse, Unoriented 3D Strokes

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COMPUTER GRAPHICS FORUM 2025年

作者： Sureshkumar, Anandhu Parakkat, Amal Dev Bonneau, Georges-Pierre Hahmann, Stefanie Cani, Marie-Paule Inst Polytech Paris LTCI Telecom Paris Paris France Univ Grenoble Alpes CNRS INRIA Grenoble INPLKJ Grenoble France CNRS Ecole Polytech Inst Polytech Paris LIX Paris France

Although intuitive, sketching a closed 3D shape directly in an immersive environment results in an unordered set of arbitrary strokes, which can be difficult to assemble into a closed surface. We tackle this challenge by introducing VRSurf, a surfacing method inspired by a balloon inflation metaphor: Seeded in the sparse scaffold formed by the strokes, a smooth, closed surface is inflated to progressively interpolate the input strokes, sampled into lists of points. These are treated in a divide-and-conquer manner, which allows for automatically triggering some additional balloon inflation followed byfusion ifthe current inflation stops due to a detected concavity. While the input strokes are intended to belong to the same smooth 3D shape, our method is robust to coarse VR input and does not require strokes to be aligned. We simply avoid intersecting strokes that might give an inconsistent surface position due to the roughness of the VR drawing. Moreover, no additional topological information is required, and all the user needs to do is specify the initial seeding location for the first balloon. The results show that VRsurf can efficiently generate smooth surfaces that interpolate sparse sets of unoriented strokes. Validation includes a side-by-side comparison with other reconstruction methods on the same input VR sketch. We also check that our solution matches the user's intent by applying it to strokes that were sketched on an existing 3D shape and comparing what we get to the original one.

关键词： center dot computing methodologies -> shape modeling center dot Human-centered computing -> Virtual reality center dot Applied computing -> Arts and humanities

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