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Item Mesh Smoothing for Teaching GLSL Programming(The Eurographics Association, 2022) Ilinkin, Ivaylo; Bourdin, Jean-Jacques; Paquette, EricThis paper shares ideas for effective assignment that can be used to introduce a number of advanced GLSL concepts including shader storage buffer objects, transform feedback, and compute shaders. The assignment is based on published research on mesh smoothing which serves as a motivating factor and offers a sense of accomplishment.Item A Survey of Optimal Transport for Computer Graphics and Computer Vision(The Eurographics Association and John Wiley & Sons Ltd., 2023) Bonneel, Nicolas; Digne, Julie; Bousseau, Adrien; Theobalt, ChristianOptimal transport is a long-standing theory that has been studied in depth from both theoretical and numerical point of views. Starting from the 50s this theory has also found a lot of applications in operational research. Over the last 30 years it has spread to computer vision and computer graphics and is now becoming hard to ignore. Still, its mathematical complexity can make it difficult to comprehend, and as such, computer vision and computer graphics researchers may find it hard to follow recent developments in their field related to optimal transport. This survey first briefly introduces the theory of optimal transport in layman's terms as well as most common numerical techniques to solve it. More importantly, it presents applications of these numerical techniques to solve various computer graphics and vision related problems. This involves applications ranging from image processing, geometry processing, rendering, fluid simulation, to computational optics, and many more. It is aimed at computer graphics researchers desiring to follow optimal transport research in their field as well as optimal transport researchers willing to find applications for their numerical algorithms.Item 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, GiuseppeGenerative 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.Item Scene Synthesis with Automated Generation of Textual Descriptions(The Eurographics Association, 2022) Müller-Huschke, Julian; Ritter, Marcel; Harders, Matthias; Pelechano, Nuria; Vanderhaeghe, DavidMost 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.Item A First Step Towards the Inference of Geological Topological Operations(The Eurographics Association, 2022) Pascual, Romain; Belhaouari, Hakim; Arnould, Agnès; Le Gall, Pascale; Sauvage, Basile; Hasic-Telalovic, JasminkaProcedural modeling enables building complex geometric objects and scenes in a wide panel of applications. The traditional approach relies on the sequential application of a reduced set of construction rules. We offer to automatically generate new topological rules based on an initial object and the expected result of the future operation. Non-expert users can thereby develop their own operations. We exploited our approach for the modeling of the geological subsoil.Item Synthetic Dataset for Panic Detection in Human Crowded Scenes(The Eurographics Association, 2023) Calle, Javier; Leskovsky, Peter; Garcia, Jorge; Sanchez, Marti; Singh, Gurprit; Chu, Mengyu (Rachel)AI is increasingly being used in public protection by using crowd anomaly detection. This is useful for identifying panic events enabling control forces to act faster. A significant challenge in this field is the lack of data for training these algorithms. Recreating panic events with big crowds can be both expensive and hazardous. To address this issue, this paper proposes the creation of a synthetic dataset for crowd panic behaviour. The process involves defining the scenario and setting up the appropriate CCTV cameras. Many scenarios are prepared, including variations in weather conditions. Next is the scene population with pedestrians and vehicles, with different crowd sizes and vehicle trajectories. To recreate panic, the behaviour of each person is programmed. The final videos show normality situations before the panic events start. Finally, we achieved 1717 simulations.Item Color Reproduction Framework for Inkjet FDM 3D Printers(The Eurographics Association, 2021) Silapasuphakornwong, Piyarat; Punpongsanon, Parinya; Panichkriangkrai, Chulapong; Sueeprasan, Suchitra; Uehira, Kazutake; Bittner, Jirà and Waldner, ManuelaRecent advances in consumer-grade 3D printers have enabled the fabrication of personal artifacts in aesthetically pleasing full color. However, the printed colors are usually different from the actual user desired colors due to the mismatching of droplets when the color reproduction workflow has been changed or the color profile setup is missing. In this paper, we present a preliminary experiment to investigate color reproduction errors in consumer-grade inkjet FDM 3D printers. Our results suggest that solving the problem requires initiating the workflow to minimize color reproduction errors such as using CMYK or sRGB color profiles. We also found that the mismatched color gamut between the input's desired texture and the 3D printed output depends on different file formats, and this finding requires future investigation.Item A Survey of Control Mechanisms for Creative Pattern Generation(The Eurographics Association and John Wiley & Sons Ltd., 2021) Gieseke, Lena; Asente, Paul; Mech, Radomir; Benes, Bedrich; Fuchs, Martin; Bühler, Katja and Rushmeier, HollyWe review recent methods in 2D creative pattern generation and their control mechanisms, focusing on procedural methods. The review is motivated by an artist's perspective and investigates interactive pattern generation as a complex design problem. While the repetitive nature of patterns is well-suited to algorithmic creation and automation, an artist needs more flexible control mechanisms for adaptable and inventive designs. We organize the state of the art around pattern design features, such as repetition, frames, curves, directionality, and single visual accents. Within those areas, we summarize and discuss the techniques' control mechanisms for enabling artist intent. The discussion includes questions of how input is given by the artist, what type of content the artist inputs, where the input affects the canvas spatially, and when input can be given in the timeline of the creation process. We categorize the available control mechanisms on an algorithmic level and categorize their input modes based on exemplars, parameterization, handling, filling, guiding, and placing interactions. To better understand the potential of the current techniques for creative design and to make such an investigation more manageable, we motivate our discussion with how navigation, transparency, variation, and stimulation enable creativity. We conclude our review by identifying possible new directions that can inspire innovation for artist-centered creation processes and algorithms.Item Interactive Synthesis of 3D Geometries of Blood Vessels(The Eurographics Association, 2021) Rauch, Nikolaus; Harders, Matthias; Theisel, Holger and Wimmer, MichaelIn surgical training simulators, where various organ surfaces make up the majority of the scene, the visual appearance is highly dependent on the quality of the surface textures. Blood vessels are an important detail in this; they need to be incorporated into an organ's texture. Moreover, the actual blood vessel geometries also have to be part of the simulated surgical procedure itself, e.g. during cutting. Since the manual creation of vessel geometry or branching details on textures is highly tedious, an automatic synthesis technique capable of generating a wide range of blood vessel patterns is needed.We propose a new synthesis approach based on the space colonization algorithm. As extension, physiological constraints on the proliferation of branches are enforced to create realistic vascular structures. Our framework is capable of generating three-dimensional blood vessel networks in a matter of milliseconds, thus allowing a 3D modeller to tweak parameters in real-time to obtain a desired appearance.Item NeuralMLS: Geometry-Aware Control Point Deformation(The Eurographics Association, 2022) Shechter, Meitar; Hanocka, Rana; Metzer, Gal; Giryes, Raja; Cohen-Or, Daniel; Pelechano, Nuria; Vanderhaeghe, DavidWe introduce NeuralMLS, a space-based deformation technique, guided by a set of displaced control points. We leverage the power of neural networks to inject the underlying shape geometry into the deformation parameters. The goal of our technique is to enable a realistic and intuitive shape deformation. Our method is built upon moving least-squares (MLS), since it minimizes a weighted sum of the given control point displacements. Traditionally, the influence of each control point on every point in space (i.e., the weighting function) is defined using inverse distance heuristics. In this work, we opt to learn the weighting function, by training a neural network on the control points from a single input shape, and exploit the innate smoothness of neural networks. Our geometry-aware control point deformation is agnostic to the surface representation and quality; it can be applied to point clouds or meshes, including non-manifold and disconnected surface soups. We show that our technique facilitates intuitive piecewise smooth deformations, which are well suited for manufactured objects. We show the advantages of our approach compared to existing surface and space-based deformation techniques, both quantitatively and qualitatively.