EG2022

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EUROGRAPHICS 2022: Short Papers Frontmatter
(The Eurographics Association, 2022) Pelechano, Nuria; Vanderhaeghe, David; Pelechano, Nuria; Vanderhaeghe, David
Virtual Ray Tracer
(The Eurographics Association, 2022) Verschoore de la Houssaije, Willard A.; Wezel, Chris S. van; Frey, Steffen; Kosinka, Jiri; Bourdin, Jean-Jacques; Paquette, Eric
Ray tracing is one of the more complicated techniques commonly taught in (introductory) Computer Graphics courses. Visualizations can help with understanding complex ray paths and interactions, but currently there are no openly accessible applications that focus on education. We present Virtual Ray Tracer, an interactive application that allows students/users to view and explore the ray tracing process in real-time. The application shows a scene containing a camera casting rays which interact with objects in the scene. Users are able to modify and explore ray properties such as their animation speed, the number of rays as well as the material properties of the objects in the scene. The goal of the application is to help the users-students of Computer Graphics and the general public-to better understand the ray tracing process and its characteristics. To invite users to learn and explore, various explanations and scenes are provided by the application at different levels of complexity. A user study showed the effectiveness of Virtual Ray Tracer in supporting the understanding and teaching of ray tracing. Our educational tool is built with the cross-platform engine Unity, and we make it fully available to be extended and/or adjusted to fit the requirements of courses at other institutions or of educational tutorials.
EUROGRAPHICS 2022: Education Papers Frontmatter
(The Eurographics Association, 2022) Bourdin, Jean-Jacques; Paquette, Eric; Bourdin, Jean-Jacques; Paquette, Eric
RGB-D Neural Radiance Fields: Local Sampling for Faster Training
(The Eurographics Association, 2022) Dey, Arnab; Comport, Andrew I.; Sauvage, Basile; Hasic-Telalovic, Jasminka
Learning a 3D representation of a scene has been a challenging problem for decades in computer vision. Recent advancements in implicit neural representation from images using neural radiance fields(NeRF) have shown promising results. Some of the limitations of previous NeRF based methods include longer training time, and inaccurate underlying geometry. The proposed method takes advantage of RGB-D data to reduce training time by leveraging depth sensing to improve local sampling. This paper proposes a depth-guided local sampling strategy and a smaller neural network architecture to achieve faster training time without compromising quality.
State-of-the-Art in the Architecture, Methods and Applications of StyleGAN
(The Eurographics Association and John Wiley & Sons Ltd., 2022) Bermano, Amit Haim; Gal, Rinon; Alaluf, Yuval; Mokady, Ron; Nitzan, Yotam; Tov, Omer; Patashnik, Or; Cohen-Or, Daniel; Meneveaux, Daniel; Patanè, Giuseppe
Generative Adversarial Networks (GANs) have established themselves as a prevalent approach to image synthesis. Of these, StyleGAN offers a fascinating case study, owing to its remarkable visual quality and an ability to support a large array of downstream tasks. This state-of-the-art report covers the StyleGAN architecture, and the ways it has been employed since its conception, while also analyzing its severe limitations. It aims to be of use for both newcomers, who wish to get a grasp of the field, and for more experienced readers that might benefit from seeing current research trends and existing tools laid out. Among StyleGAN's most interesting aspects is its learned latent space. Despite being learned with no supervision, it is surprisingly well-behaved and remarkably disentangled. Combined with StyleGAN's visual quality, these properties gave rise to unparalleled editing capabilities. However, the control offered by StyleGAN is inherently limited to the generator's learned distribution, and can only be applied to images generated by StyleGAN itself. Seeking to bring StyleGAN's latent control to real-world scenarios, the study of GAN inversion and latent space embedding has quickly gained in popularity. Meanwhile, this same study has helped shed light on the inner workings and limitations of StyleGAN. We map out StyleGAN's impressive story through these investigations, and discuss the details that have made StyleGAN the go-to generator. We further elaborate on the visual priors StyleGAN constructs, and discuss their use in downstream discriminative tasks. Looking forward, we point out StyleGAN's limitations and speculate on current trends and promising directions for future research, such as task and target specific fine-tuning.
Authoring Virtual Crowds: A Survey
(The Eurographics Association and John Wiley & Sons Ltd., 2022) Lemonari, Marilena; Blanco, Rafael; Charalambous, Panayiotis; Pelechano, Nuria; Avraamides, Marios; Pettré, Julien; Chrysanthou, Yiorgos; Meneveaux, Daniel; Patanè, Giuseppe
Recent advancements in crowd simulation unravel a wide range of functionalities for virtual agents, delivering highly-realistic, natural virtual crowds. Such systems are of particular importance to a variety of applications in fields such as: entertainment (e.g., movies, computer games); architectural and urban planning; and simulations for sports and training. However, providing their capabilities to untrained users necessitates the development of authoring frameworks. Authoring virtual crowds is a complex and multi-level task, varying from assuming control and assisting users to realise their creative intents, to delivering intuitive and easy to use interfaces, facilitating such control. In this paper, we present a categorisation of the authorable crowd simulation components, ranging from high-level behaviours and path-planning to local movements, as well as animation and visualisation. We provide a review of the most relevant methods in each area, emphasising the amount and nature of influence that the users have over the final result. Moreover, we discuss the currently available authoring tools (e.g., graphical user interfaces, drag-and-drop), identifying the trends of early and recent work. Finally, we suggest promising directions for future research that mainly stem from the rise of learning-based methods, and the need for a unified authoring framework.
Stochastic Light Culling for Single Scattering in Participating Media
(The Eurographics Association, 2022) Fujieda, Shin; Tokuyoshi, Yusuke; Harada, Takahiro; Pelechano, Nuria; Vanderhaeghe, David
We introduce a simple but efficient method to compute single scattering from point and arbitrarily shaped area light sources in participating media. Our method extends the stochastic light culling method to volume rendering by considering the intersection of a ray and spherical bounds of light influence ranges. For primary rays, this allows simple computation of the lighting in participating media without hierarchical data structures such as a light tree. First, we show how to combine equiangular sampling with the proposed light culling method in a simple case of point lights. We then apply it to arbitrarily shaped area lights by considering virtual point lights on the surface of area lights. Using our method, we are able to improve the rendering quality for scenes with many lights without tree construction and traversal.
CUDA and Applications to Task-based Programming
(The Eurographics Association, 2022) Kerbl, Bernhard; Kenzel, Michael; Winter, Martin; Steinberger, Markus; Hahmann, Stefanie; Patow, Gustavo A.
Since its inception, the CUDA programming model has been continuously evolving. Because the CUDA toolkit aims to consistently expose cutting-edge capabilities for general-purpose compute jobs to its users, the added features in each new version reflect the rapid changes that we observe in GPU architectures. Over the years, the changes in hardware, growing scope of built-in functions and libraries, as well as an advancing C++ standard compliance have expanded the design choices when coding for CUDA, and significantly altered the directives to achieve peak performance. In this tutorial, we give a thorough introduction to the CUDA toolkit, demonstrate how a contemporary application can benefit from recently introduced features and how they can be applied to task-based GPU scheduling in particular. For instance, we will provide detailed examples of use cases for independent thread scheduling, cooperative groups, and the CUDA standard library, libcu++, which are certain to become an integral part of clean coding for CUDA in the near future.
Stroke based Painterly Inbetweening
(The Eurographics Association, 2022) Barroso, Nicolas; Fondevilla, Amélie; Vanderhaeghe, David; Sauvage, Basile; Hasic-Telalovic, Jasminka
Creating a 2D animation with visible strokes is a tedious and time consuming task for an artist. Computer aided animation usually focus on cartoon stylized rendering, or is built from an automatic process as 3D animations stylization, loosing the painterly look and feel of hand made animation. We propose to simplify the creation of stroke-based animations: from a set of key frames, our methods automatically generates intermediate frames to depict the animation. Each intermediate frame looks as it could have been drawn by an artist, using the same high level stroke based representation as key frame, and in succession they display the subtle temporal incoherence usually found in hand-made animations.
Transparent Rendering and Slicing of Integral Surfaces Using Per-primitive Interval Arithmetic
(The Eurographics Association, 2022) Aydinlilar, Melike; Zanni, Cédric; Pelechano, Nuria; Vanderhaeghe, David
We present a method for efficient incorporation of integral surfaces within existing robust processing methods such as interval arithmetic and segment-tracing. We based our approach on high-level knowledge of the field function of the primitives. We show application to slicing and transparent rendering of integral surfaces based on interval arithmetic.
EUROGRAPHICS 2022: CGF 41-2 STARs Frontmatter
(The Eurographics Association and John Wiley & Sons Ltd., 2022) Meneveaux, Daniel; Patanè, Giuseppe; Meneveaux, Daniel; Patanè, Giuseppe
The Road to Vulkan: Teaching Modern Low-Level APIs in Introductory Graphics Courses
(The Eurographics Association, 2022) Unterguggenberger, Johannes; Kerbl, Bernhard; Wimmer, Michael; Bourdin, Jean-Jacques; Paquette, Eric
For over two decades, the OpenGL API provided users with the means for implementing versatile, feature-rich, and portable real-time graphics applications. Consequently, it has been widely adopted by practitioners and educators alike and is deeply ingrained in many curricula that teach real-time graphics for higher education. Over the years, the architecture of graphics processing units (GPUs) incrementally diverged from OpenGL's conceptual design. The more recently introduced Vulkan API provides a more modern, fine-grained approach for interfacing with the GPU. Various properties of this API and overall trends suggest that Vulkan could soon replace OpenGL in many areas. Hence, it stands to reason that educators who have their students' best interests at heart should provide them with corresponding lecture material. However, Vulkan is notoriously verbose and rather challenging for first-time users, thus transitioning to this new API bears a considerable risk of failing to achieve expected teaching goals. In this paper, we document our experiences after teaching Vulkan in an introductory graphics course side-by-side with conventional OpenGL. A final survey enables us to draw conclusions about perceived workload, difficulty, and students' acceptance of either approach and identify suitable conditions and recommendations for teaching Vulkan to undergraduate students.
Geometric Deformation for Reducing Optic Flow and Cybersickness Dose Value in VR
(The Eurographics Association, 2022) Lou, Ruding; So, Richard H. Y.; Bechmann, Dominique; Sauvage, Basile; Hasic-Telalovic, Jasminka
Today virtual reality technologies is becoming more and more widespread and has found strong applications in various domains. However, the fear to experience motion sickness is still an important barrier for VR users. Instead of moving physically, VR users experience virtual locomotion but their vestibular systems do not sense the self-motion that are visually induced by immersive displays. The mismatch in visual and vestibular senses causes sickness. Previous solutions actively reduce user's field-of-view and alter their navigation. In this paper we propose a passive approach that temporarily deforms geometrically the virtual environment according to user navigation. Two deformation methods have been prototyped and tested. The first one reduces the perceived optic flow which is the main cause of visually induced motion sickness. The second one encourages users to adopt smoother trajectories and reduce the cybersickness dose value. Both methods have the potential to be applied generically.
From Capture to Immersive Viewing of 3D HDR Point Clouds
(The Eurographics Association, 2022) Loscos, Celine; Souchet, Philippe; Barrios, Théo; Valenzise, Giuseppe; Cozot, Rémi; Hahmann, Stefanie; Patow, Gustavo A.
The collaborators of the ReVeRY project address the design of a specific grid of cameras, a cost-efficient system that acquires at once several viewpoints, possibly under several exposures and the converting of multiview, multiexposed, video stream into a high quality 3D HDR point cloud. In the last two decades, industries and researchers proposed significant advances in media content acquisition systems in three main directions: increase of resolution and image quality with the new ultra-high-definition (UHD) standard; stereo capture for 3D content; and high-dynamic range (HDR) imaging. Compression, representation, and interoperability of these new media are active research fields in order to reduce data size and be perceptually accurate. The originality of the project is to address both HDR and depth through the entire pipeline. Creativity is enhanced by several tools, which answer challenges at the different stages of the pipeline: camera setup, data processing, capture visualisation, virtual camera controller, compression, perceptually guided immersive visualisation. It is the experience acquired by the researchers of the project that is exposed in this tutorial.
Scene Synthesis with Automated Generation of Textual Descriptions
(The Eurographics Association, 2022) Müller-Huschke, Julian; Ritter, Marcel; Harders, Matthias; Pelechano, Nuria; Vanderhaeghe, David
Most current research on automatically captioning and describing scenes with spatial content focuses on images. We outline that generating descriptive text for a synthesized 3D scene can be achieved via a suitable intermediate representation employed in the synthesis algorithm. As an example, we synthesize scenes of medieval village settings, and generate their descriptions. Our system employs graph grammars, Markov Chain Monte Carlo optimization, and a natural language generation pipeline. Randomly placed objects are evaluated and optimized by a cost function capturing neighborhood relations, path layouts, and collisions. Further, in a pilot study we assess the performance of our framework by comparing the generated descriptions to others provided by human subjects. While the latter were often short and low-effort, the highest-rated ones clearly outperform our generated ones. Nevertheless, the average of all collected human descriptions was indeed rated by the study participants as being less accurate than the automated ones.
Inverse Computational Spectral Geometry
(The Eurographics Association, 2022) Rodolà, Emanuele; Cosmo, Luca; Ovsjanikov, Maks; Rampini, Arianna; Melzi, Simone; Bronstein, Michael; Marin, Riccardo; Hahmann, Stefanie; Patow, Gustavo A.
In the last decades, geometry processing has attracted a growing interest thanks to the wide availability of new devices and software that make 3D digital data available and manipulable to everyone. Typical issues faced by geometry processing algorithms include the variety of discrete representations for 3D data (point clouds, polygonal or tet-meshes and voxels), or the type of deformation this data may undergo. Powerful approaches to address these issues come from looking at the spectral decomposition of canonical differential operators, such as the Laplacian, which provides a rich, informative, robust, and invariant representation of the 3D objects. The focus of this tutorial is on computational spectral geometry. We will offer a different perspective on spectral geometric techniques, supported by recent successful methods in the graphics and 3D vision communities and older but notoriously overlooked results. We will discuss both the “forward” path typical of spectral geometry pipelines (e.g. computing Laplacian eigenvalues and eigenvectors of a given shape) with its widespread applicative relevance, and the inverse path (e.g. recovering a shape from given Laplacian eigenvalues, like in the classical “hearing the shape of the drum” problem) with its ill-posed nature and the benefits showcased on several challenging tasks in graphics and geometry processing.
EUROGRAPHICS 2022: Tutorials Frontmatter
(The Eurographics Association, 2022) Hahmann, Stefanie; Patow, Gustavo A.; Hahmann, Stefanie; Patow, Gustavo A.
Evaluating Bloom's Taxonomy-based Learning Modules for Parallel Coordinates Literacy
(The Eurographics Association, 2022) Peng, Ilena; Firat, Elif E.; Laramee, Robert S.; Joshi, Alark; Bourdin, Jean-Jacques; Paquette, Eric
In this paper, we present the results of an intervention designed to introduce parallel coordinates to students. The intervention contains six new modules inspired by Bloom's taxonomy that featured a combination of videos, tests, and tasks. We studied the impact of our modules with a corrective feedback mechanism inspired by Mastery Learning. Based on analyzing the data of our students, we found that students in the Corrective Immediate Feedback (CIF) group performed better on average on all the modules as compared to the students in the No Feedback (NF) group. In the tasks where students were required to construct parallel coordinates plots, students in the Corrective Immediate Feedback group produced plots with appropriate use of color, labels, legends, etc. Overall, students in both groups grew more confident in their ability to recognize parallel coordinates plots and expressed high confidence in their ability to interpret, create, and use parallel coordinates plots for data exploration and presentation in the future.
View Dependent Decompression for Web-based Massive Triangle Meshes Visualisation
(The Eurographics Association, 2022) Cecchin, Alice; Du, Paul; Pastor, Mickaël; Agouzoul, Asma; Sauvage, Basile; Hasic-Telalovic, Jasminka
We introduce a framework extending an existing progressive compression-decompression algorithm for 3D triangular meshes. First, a mesh is partitioned. Each resulting part is compressed, then joined with one of its neighbours. These steps are repeated following a binary tree of operations, until a single compressed mesh remains. Decompressing the mesh involves progressively performing those steps in reverse, per node, and locally, by selecting the branch of the tree to explore. This method creates a compact and lossless representation of the model that allows its progressive and local reconstruction. Previously unprocessable meshes can be visualized on the web and mobile devices using this technique.
Procedural Bridges-and-pillars Support Generation
(The Eurographics Association, 2022) Freire, Marco; Hornus, Samuel; Perchy, Salim; Lefebvre, Sylvain; Pelechano, Nuria; Vanderhaeghe, David
Additive manufacturing requires support structures to fabricate parts with overhangs. In this paper, we revisit a known support structure based on bridges-and-pillars (see Figure 1). The support structures are made of vertical pillars supporting horizontal bridges. Their scaffolding structure makes them stable and reliable to print. However, the algorithm heuristic search does not scale well and is prone to produce contacts with the parts, leaving scars after removal. We propose a novel algorithm for this type of supports, focusing on avoiding unnecessary contacts with the part as much as possible. Our approach builds upon example-based model synthesis to enable early detection of collision-free passages as well as non-reachable regions.

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