42-Issue 6

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https://diglib.eg.org/handle/10.2312/3543887

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Corrigendum to “Making Procedural Water Waves Boundary‐aware”, “Primal/Dual Descent Methods for Dynamics”, and “Detailed Rigid Body Simulation with Extended Position Based Dynamics”
(© 2023 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd., 2023) Hauser, Helwig and Alliez, Pierre
3D Generative Model Latent Disentanglement via Local Eigenprojection
(© 2023 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd., 2023) Foti, Simone; Koo, Bongjin; Stoyanov, Danail; Clarkson, Matthew J.; Hauser, Helwig and Alliez, Pierre
Designing realistic digital humans is extremely complex. Most data‐driven generative models used to simplify the creation of their underlying geometric shape do not offer control over the generation of local shape attributes. In this paper, we overcome this limitation by introducing a novel loss function grounded in spectral geometry and applicable to different neural‐network‐based generative models of 3D head and body meshes. Encouraging the latent variables of mesh variational autoencoders (VAEs) or generative adversarial networks (GANs) to follow the local eigenprojections of identity attributes, we improve latent disentanglement and properly decouple the attribute creation. Experimental results show that our local eigenprojection disentangled (LED) models not only offer improved disentanglement with respect to the state‐of‐the‐art, but also maintain good generation capabilities with training times comparable to the vanilla implementations of the models. Our code and pre‐trained models are available at .
MesoGAN: Generative Neural Reflectance Shells
(© 2023 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd., 2023) Diolatzis, Stavros; Novak, Jan; Rousselle, Fabrice; Granskog, Jonathan; Aittala, Miika; Ramamoorthi, Ravi; Drettakis, George; Hauser, Helwig and Alliez, Pierre
We introduce MesoGAN, a model for generative 3D neural textures. This new graphics primitive represents mesoscale appearance by combining the strengths of generative adversarial networks (StyleGAN) and volumetric neural field rendering. The primitive can be applied to surfaces as a neural reflectance shell; a thin volumetric layer above the surface with appearance parameters defined by a neural network. To construct the neural shell, we first generate a 2D feature texture using StyleGAN with carefully randomized Fourier features to support arbitrarily sized textures without repeating artefacts. We augment the 2D feature texture with a learned height feature, which aids the neural field renderer in producing volumetric parameters from the 2D texture. To facilitate filtering, and to enable end‐to‐end training within memory constraints of current hardware, we utilize a hierarchical texturing approach and train our model on multi‐scale synthetic datasets of 3D mesoscale structures. We propose one possible approach for conditioning MesoGAN on artistic parameters (e.g. fibre length, density of strands, lighting direction) and demonstrate and discuss integration into physically based renderers.
Immersive Free‐Viewpoint Panorama Rendering from Omnidirectional Stereo Video
(© 2023 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd., 2023) Mühlhausen, Moritz; Kappel, Moritz; Kassubeck, Marc; Wöhler, Leslie; Grogorick, Steve; Castillo, Susana; Eisemann, Martin; Magnor, Marcus; Hauser, Helwig and Alliez, Pierre
In this paper, we tackle the challenging problem of rendering real‐world 360° panorama videos that support full 6 degrees‐of‐freedom (DoF) head motion from a prerecorded omnidirectional stereo (ODS) video. In contrast to recent approaches that create novel views for individual panorama frames, we introduce a video‐specific temporally‐consistent multi‐sphere image (MSI) scene representation. Given a conventional ODS video, we first extract information by estimating framewise descriptive feature maps. Then, we optimize the global MSI model using theory from recent research on neural radiance fields. Instead of a continuous scene function, this multi‐sphere image (MSI) representation depicts colour and density information only for a discrete set of concentric spheres. To further improve the temporal consistency of our results, we apply an ancillary refinement step which optimizes the temporal coherency between successive video frames. Direct comparisons to recent baseline approaches show that our global MSI optimization yields superior performance in terms of visual quality. Our code and data will be made publicly available.
Numerical Coarsening with Neural Shape Functions
(© 2023 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd., 2023) Ni, Ning; Xu, Qingyu; Li, Zhehao; Fu, Xiao‐Ming; Liu, Ligang; Hauser, Helwig and Alliez, Pierre
We propose to use nonlinear shape functions represented as neural networks in numerical coarsening to achieve generalization capability as well as good accuracy. To overcome the challenge of generalization to different simulation scenarios, especially nonlinear materials under large deformations, our key idea is to replace the linear mapping between coarse and fine meshes adopted in previous works with a nonlinear one represented by neural networks. However, directly applying an end‐to‐end neural representation leads to poor performance due to over‐huge parameter space as well as failing to capture some intrinsic geometry properties of shape functions. Our solution is to embed geometry constraints as the prior knowledge in learning, which greatly improves training efficiency and inference robustness. With the trained neural shape functions, we can easily adopt numerical coarsening in the simulation of various hyperelastic models without any other preprocessing step required. The experiment results demonstrate the efficiency and generalization capability of our method over previous works.
A Semi‐Procedural Convolutional Material Prior
(© 2023 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd., 2023) Zhou, Xilong; Hašan, Miloš; Deschaintre, Valentin; Guerrero, Paul; Sunkavalli, Kalyan; Kalantari, Nima Khademi; Hauser, Helwig and Alliez, Pierre
Lightweight material capture methods require a material prior, defining the subspace of plausible textures within the large space of unconstrained texel grids. Previous work has either used deep neural networks (trained on large synthetic material datasets) or procedural node graphs (constructed by expert artists) as such priors. In this paper, we propose a semi‐procedural differentiable material prior that represents materials as a set of (typically procedural) grayscale noises and patterns that are processed by a sequence of lightweight learnable convolutional filter operations. We demonstrate that the restricted structure of this architecture acts as an inductive bias on the space of material appearances, allowing us to optimize the weights of the convolutions per‐material, with no need for pre‐training on a large dataset. Combined with a differentiable rendering step and a perceptual loss, we enable single‐image tileable material capture comparable with state of the art. Our approach does not target the pixel‐perfect recovery of the material, but rather uses noises and patterns as input to match the target appearance. To achieve this, it does not require complex procedural graphs, and has a much lower complexity, computational cost and storage cost. We also enable control over the results, through changing the provided patterns and using guide maps to push the material properties towards a user‐driven objective.
Adversarial Interactive Cartoon Sketch Colourization with Texture Constraint and Auxiliary Auto‐Encoder
(© 2023 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd., 2023) Liu, Xiaoyu; Zhu, Shaoqiang; Zeng, Yao; Zhang, Junsong; Hauser, Helwig and Alliez, Pierre
Colouring cartoon sketches can help children develop their intellect and inspire their artistic creativity. Unlike photo colourization or anime line art colourization, cartoon sketch colourization is challenging due to the scarcity of texture information and the irregularity of the line structure, which is mainly reflected in the phenomenon of colour‐bleeding artifacts in generated images. We propose a colourization approach for cartoon sketches, which takes both sketches and colour hints as inputs to produce impressive images. To solve the problem of colour‐bleeding artifacts, we propose a multi‐discriminator colourization framework that introduces a texture discriminator in the conditional generative adversarial network (cGAN). Then we combined this framework with a pre‐trained auxiliary auto‐encoder, where an auxiliary feature loss is designed to further improve colour quality, and a condition input is introduced to increase the generalization ability over hand‐drawn sketches. We present both quantitative and qualitative evaluations, which prove the effectiveness of our proposed method. We test our method on sketches of varying complexity and structure, then build an interactive programme based on our model for user study. Experimental results demonstrate that the method generates natural and consistent colour images in real time from sketches drawn by non‐professionals.
Faster Edge‐Path Bundling through Graph Spanners
(© 2023 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd., 2023) Wallinger, Markus; Archambault, Daniel; Auber, David; Nöllenburg, Martin; Peltonen, Jaakko; Hauser, Helwig and Alliez, Pierre
Edge‐Path bundling is a recent edge bundling approach that does not incur ambiguities caused by bundling disconnected edges together. Although the approach produces less ambiguous bundlings, it suffers from high computational cost. In this paper, we present a new Edge‐Path bundling approach that increases the computational speed of the algorithm without reducing the quality of the bundling. First, we demonstrate that biconnected components can be processed separately in an Edge‐Path bundling of a graph without changing the result. Then, we present a new edge bundling algorithm that is based on observing and exploiting a strong relationship between Edge‐Path bundling and graph spanners. Although the worst case complexity of the approach is the same as of the original Edge‐Path bundling algorithm, we conduct experiments to demonstrate that the new approach is – times faster than Edge‐Path bundling depending on the dataset, which brings its practical running time more in line with traditional edge bundling algorithms.
It's about Time: Analytical Time Periodization
(© 2023 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd., 2023) Andrienko, Natalia; Andrienko, Gennady; Hauser, Helwig and Alliez, Pierre
This paper presents a novel approach to the problem of time periodization, which involves dividing the time span of a complex dynamic phenomenon into periods that enclose different relatively stable states or development trends. The challenge lies in finding such a division of the time that takes into account diverse behaviours of multiple components of the phenomenon while being simple and easy to interpret. Despite the importance of this problem, it has not received sufficient attention in the fields of visual analytics and data science. We use a real‐world example from aviation and an additional usage scenario on analysing mobility trends during the COVID‐19 pandemic to develop and test an analytical workflow that combines computational and interactive visual techniques. We highlight the differences between the two cases and show how they affect the use of different techniques. Through our investigation of possible variations in the time periodization problem, we discuss the potential of our approach to be used in various applications. Our contributions include defining and investigating an earlier neglected problem type, developing a practical and reproducible approach to solving problems of this type, and uncovering potential for formalization and development of computational methods.
Visual Parameter Space Exploration in Time and Space
(© 2023 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd., 2023) Piccolotto, Nikolaus; Bögl, Markus; Miksch, Silvia; Hauser, Helwig and Alliez, Pierre
Computational models, such as simulations, are central to a wide range of fields in science and industry. Those models take input parameters and produce some output. To fully exploit their utility, relations between parameters and outputs must be understood. These include, for example, which parameter setting produces the best result (optimization) or which ranges of parameter settings produce a wide variety of results (sensitivity). Such tasks are often difficult to achieve for various reasons, for example, the size of the parameter space, and supported with visual analytics. In this paper, we survey visual parameter space exploration (VPSE) systems involving spatial and temporal data. We focus on interactive visualizations and user interfaces. Through thematic analysis of the surveyed papers, we identify common workflow steps and approaches to support them. We also identify topics for future work that will help enable VPSE on a greater variety of computational models.
Multilevel Robustness for 2D Vector Field Feature Tracking, Selection and Comparison
(© 2023 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd., 2023) Yan, Lin; Ullrich, Paul Aaron; Van Roekel, Luke P.; Wang, Bei; Guo, Hanqi; Hauser, Helwig and Alliez, Pierre
Critical point tracking is a core topic in scientific visualization for understanding the dynamic behaviour of time‐varying vector field data. The topological notion of robustness has been introduced recently to quantify the structural stability of critical points, that is, the robustness of a critical point is the minimum amount of perturbation to the vector field necessary to cancel it. A theoretical basis has been established previously that relates critical point tracking with the notion of robustness, in particular, critical points could be tracked based on their closeness in stability, measured by robustness, instead of just distance proximity within the domain. However, in practice, the computation of classic robustness may produce artifacts when a critical point is close to the boundary of the domain; thus, we do not have a complete picture of the vector field behaviour within its local neighbourhood. To alleviate these issues, we introduce a multilevel robustness framework for the study of 2D time‐varying vector fields. We compute the robustness of critical points across varying neighbourhoods to capture the multiscale nature of the data and to mitigate the boundary effect suffered by the classic robustness computation. We demonstrate via experiments that such a new notion of robustness can be combined seamlessly with existing feature tracking algorithms to improve the visual interpretability of vector fields in terms of feature tracking, selection and comparison for large‐scale scientific simulations. We observe, for the first time, that the minimum multilevel robustness is highly correlated with physical quantities used by domain scientists in studying a real‐world tropical cyclone dataset. Such an observation helps to increase the physical interpretability of robustness.
ARAP Revisited Discretizing the Elastic Energy using Intrinsic Voronoi Cells
(© 2023 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd., 2023) Finnendahl, Ugo; Schwartz, Matthias; Alexa, Marc; Hauser, Helwig and Alliez, Pierre
As‐rigid‐as‐possible (ARAP) surface modelling is widely used for interactive deformation of triangle meshes. We show that ARAP can be interpreted as minimizing a discretization of an elastic energy based on non‐conforming elements defined over dual orthogonal cells of the mesh. Using the Voronoi cells rather than an orthogonal dual of the extrinsic mesh guarantees that the energy is non‐negative over each cell. We represent the intrinsic Delaunay edges extrinsically as polylines over the mesh, encoded in barycentric coordinates relative to the mesh vertices. This modification of the original ARAP energy, which we term , remedies problems stemming from non‐Delaunay edges in the original approach. Unlike the spokes‐and‐rims version of the ARAP approach it is less susceptible to the triangulation of the surface. We provide examples of deformations generated with iARAP and contrast them with other versions of ARAP. We also discuss the properties of the Laplace‐Beltrami operator implicitly introduced with the new discretization.
Line Drawing Vectorization via Coarse‐to‐Fine Curve Network Optimization
(© 2023 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd., 2023) Bao, Bin; Fu, Hongbo; Hauser, Helwig and Alliez, Pierre
Vectorizing line drawings is a fundamental component of the workflow in various applications such as graphic design and computer animation. A practical vectorization tool is desired to produce high‐quality curves that are faithful to the original inputs and close to the connectivity of human drawings. The existing line vectorization approaches either suffer from low geometry accuracy or incorrect connectivity for noisy inputs or detailed complex drawings. We propose a novel line drawing vectorization framework based on coarse‐to‐fine curve network optimization. Our technique starts with an initial curve network generated by an existing tracing method. It then performs a global optimization which fits the curve network to image centrelines. Finally, our method performs a finer optimization in local junction regions to achieve better connectivity and curve geometry around junctions. We qualitatively and quantitatively evaluate our system on line drawings with varying image quality and shape complexity, and show that our technique outperforms existing works in terms of curve quality and computational time.
Distributed Poisson Surface Reconstruction
(© 2023 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd., 2023) Kazhdan, M.; Hoppe, H.; Hauser, Helwig and Alliez, Pierre
Screened Poisson surface reconstruction robustly creates meshes from oriented point sets. For large datasets, the technique requires hours of computation and significant memory. We present a method to parallelize and distribute this computation over multiple commodity client nodes. The method partitions space on one axis into adaptively sized slabs containing balanced subsets of points. Because the Poisson formulation involves a global system, the challenge is to maintain seamless consistency at the slab boundaries and obtain a reconstruction that is indistinguishable from the serial result. To this end, we express the reconstructed indicator function as a sum of a low‐resolution term computed on a server and high‐resolution terms computed on distributed clients. Using a client–server architecture, we map the computation onto a sequence of serial server tasks and parallel client tasks, separated by synchronization barriers. This architecture also enables low‐memory evaluation on a single computer, albeit without speedup. We demonstrate a 700 million vertex reconstruction of the billion point David statue scan in less than 20 min on a 65‐node cluster with a maximum memory usage of 45 GB/node, or in 14 h on a single node.
Visually Abstracting Event Sequences as Double Trees Enriched with Category‐Based Comparison
(© 2023 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd., 2023) Krause, Cedric; Agarwal, Shivam; Burch, Michael; Beck, Fabian; Hauser, Helwig and Alliez, Pierre
Event sequence visualization aids analysts in many domains to better understand and infer new insights from event data. Analysing behaviour before or after a certain event of interest is a common task in many scenarios. In this paper, we introduce, formally define, and position as a domain‐agnostic tree visualization approach for this task. The visualization shows the sequences that led to the event of interest as a tree on the left, and those that followed on the right. Moreover, our approach enables users to create selections based on event attributes to interactively compare the events and sequences along colour‐coded categories. We integrate the double tree and category‐based comparison into a user interface for event sequence analysis. In three application examples, we show a diverse set of scenarios, covering short and long time spans, non‐spatial and spatial events, human and artificial actors, to demonstrate the general applicability of the approach.
Model‐based Crowd Behaviours in Human‐solution Space
(© 2023 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd., 2023) Xiang, Wei; Wang, He; Zhang, Yuqing; Yip, Milo K.; Jin, Xiaogang; Hauser, Helwig and Alliez, Pierre
Realistic crowd simulation has been pursued for decades, but it still necessitates tedious human labour and a lot of trial and error. The majority of currently used crowd modelling is either empirical (model‐based) or data‐driven (model‐free). Model‐based methods cannot fit observed data precisely, whereas model‐free methods are limited by the availability/quality of data and are uninterpretable. In this paper, we aim at taking advantage of both model‐based and data‐driven approaches. In order to accomplish this, we propose a new simulation framework built on a physics‐based model that is designed to be data‐friendly. Both the general prior knowledge about crowds encoded by the physics‐based model and the specific real‐world crowd data at hand jointly influence the system dynamics. With a multi‐granularity physics‐based model, the framework combines microscopic and macroscopic motion control. Each simulation step is formulated as an energy optimization problem, where the minimizer is the desired crowd behaviour. In contrast to traditional optimization‐based methods which seek the theoretical minimizer, we designed an acceleration‐aware data‐driven scheme to compute the minimizer from real‐world data in order to achieve higher realism by parameterizing both velocity and acceleration. Experiments demonstrate that our method can produce crowd animations that are more realistically behaved in a variety of scales and scenarios when compared to the earlier methods.
OaIF: Occlusion‐Aware Implicit Function for Clothed Human Re‐construction
(© 2023 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd., 2023) Tan, Yudi; Guan, Boliang; Zhou, Fan; Su, Zhuo; Hauser, Helwig and Alliez, Pierre
Clothed human re‐construction from a monocular image is challenging due to occlusion, depth‐ambiguity and variations of body poses. Recently, shape representation based on an implicit function, compared to explicit representation such as mesh and voxel, is more capable with complex topology of clothed human. This is mainly achieved by using pixel‐aligned features, facilitating implicit function to capture local details. But such methods utilize an identical feature map for all sampled points to get local features, making their models occlusion‐agnostic in the encoding stage. The decoder, as implicit function, only maps features and does not take occlusion into account explicitly. Thus, these methods fail to generalize well in poses with severe self‐occlusion. To address this, we present OaIF to encode local features conditioned in visibility of SMPL vertices. OaIF projects SMPL vertices onto image plane to obtain image features masked by visibility. Vertices features integrated with geometry information of mesh are then feed into a GAT network to encode jointly. We query hybrid features and occlusion factors for points through cross attention and learn occupancy fields for clothed human. The experiments demonstrate that OaIF achieves more robust and accurate re‐construction than the state of the art on both public datasets and wild images.
Triangle Influence Supersets for Fast Distance Computation
(© 2023 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd., 2023) Pujol, Eduard; Chica, Antonio; Hauser, Helwig and Alliez, Pierre
We present an acceleration structure to efficiently query the Signed Distance Field (SDF) of volumes represented by triangle meshes. The method is based on a discretization of space. In each node, we store the triangles defining the SDF behaviour in that region. Consequently, we reduce the cost of the nearest triangle search, prioritizing query performance, while avoiding approximations of the field. We propose a method to conservatively compute the set of triangles influencing each node. Given a node, each triangle defines a region of space such that all points inside it are closer to a point in the node than the triangle is. This property is used to build the SDF acceleration structure. We do not need to explicitly compute these regions, which is crucial to the performance of our approach. We prove the correctness of the proposed method and compare it to similar approaches, confirming that our method produces faster query times than other exact methods.
A Survey of Personalized Interior Design
(© 2023 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd., 2023) Wang, Y.T.; Liang, C.; Huai, N.; Chen, J.; Zhang, C.J.; Hauser, Helwig and Alliez, Pierre
Interior design is the core step of interior decoration, and it determines the overall layout and style of furniture. Traditional interior design is usually laborious and time‐consuming work carried out by professional designers and cannot always meet clients' personalized requirements. With the development of computer graphics, computer vision and machine learning, computer scientists have carried out much fruitful research work in computer‐aided personalized interior design (PID). In general, personalization research in interior design mainly focuses on furniture selection and floor plan preparation. In terms of the former, personalized furniture selection is achieved by selecting furniture that matches the resident's preference and style, while the latter allows the resident to personalize their floor plan design and planning. Finally, the automatic furniture layout task generates a stylistically matched and functionally complete furniture layout result based on the selected furniture and prepared floor plan. Therefore, the main challenge for PID is meeting residents' personalized requirements in terms of both furniture and floor plans. This paper answers the above question by reviewing recent progress in five separate but correlated areas, including furniture style analysis, furniture compatibility prediction, floor plan design, floor plan analysis and automatic furniture layout. For each topic, we review representative methods and compare and discuss their strengths and shortcomings. In addition, we collect and summarize public datasets related to PID and finally discuss its future research directions.
Reference‐based Screentone Transfer via Pattern Correspondence and Regularization
(© 2023 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd., 2023) Li, Zhansheng; Zhao, Nanxuan; Wu, Zongwei; Dai, Yihua; Wang, Junle; Jing, Yanqing; He, Shengfeng; Hauser, Helwig and Alliez, Pierre
Adding screentone to initial line drawings is a crucial step for manga generation, but is a tedious and human‐laborious task. In this work, we propose a novel data‐driven method aiming to transfer the screentone pattern from a reference manga image. This not only ensures the quality, but also adds controllability to the generated manga results. The reference‐based screentone translation task imposes several unique challenges. Since manga image often contains multiple screentone patterns interweaved with line drawing, as an abstract art, this makes it even more difficult to extract disentangled style code from the reference. Also, finding correspondence for mapping between the reference and the input line drawing without any screentone is hard. As screentone contains many subtle details, how to guarantee the style consistency to the reference remains challenging. To suit our purpose and resolve the above difficulties, we propose a novel Reference‐based Screentone Transfer Network (RSTN). We encode the screentone style through a 1D stylegram. A patch correspondence loss is designed to build a similarity mapping function for guiding the translation. To mitigate the generated artefacts, a pattern regularization loss is introduced in the patch‐level. Through extensive experiments and a user study, we have demonstrated the effectiveness of our proposed model.

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