Now showing items 1-20 of 66

    • Authoring Virtual Crowds: A Survey 

      Lemonari, Marilena; Blanco, Rafael; Charalambous, Panayiotis; Pelechano, Nuria; Avraamides, Marios; Pettré, Julien; Chrysanthou, Yiorgos (The Eurographics Association and John Wiley & Sons Ltd., 2022)
      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 ...
    • Procedural Bridges-and-pillars Support Generation 

      Freire, Marco; Hornus, Samuel; Perchy, Salim; Lefebvre, Sylvain (The Eurographics Association, 2022)
      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 ...
    • EUROGRAPHICS 2022: Tutorials Frontmatter 

      Hahmann, Stefanie; Patow, Gustavo A. (The Eurographics Association, 2022)
    • Practical Machine Learning for Rendering: From Research to Deployment 

      Marshall, Carl S.; Vembar, Deepak S.; Ganguly, Sujoy; Guinier, Florent (The Eurographics Association, 2022)
      Applying machine learning to improve graphics rendering or asset pipelines is challenging. Practicalities such as proprietary datasets, network retraining, and deployment issues make it difficult to translate published ...
    • State-of-the-Art in the Architecture, Methods and Applications of StyleGAN 

      Bermano, Amit Haim; Gal, Rinon; Alaluf, Yuval; Mokady, Ron; Nitzan, Yotam; Tov, Omer; Patashnik, Or; Cohen-Or, Daniel (The Eurographics Association and John Wiley & Sons Ltd., 2022)
      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 ...
    • A Survey on SPH Methods in Computer Graphics 

      Koschier, Dan; Bender, Jan; Solenthaler, Barbara; Teschner, Matthias (The Eurographics Association and John Wiley & Sons Ltd., 2022)
      Throughout the past decades, the graphics community has spent major resources on the research and development of physics simulators on the mission to computer-generate behaviors achieving outstanding visual effects or to ...
    • A Halfedge Refinement Rule for Parallel Loop Subdivision 

      Vanhoey, Kenneth; Dupuy, Jonathan (The Eurographics Association, 2022)
      We observe that a Loop refinement step invariably splits halfedges into four new ones. We leverage this observation to formulate a breadth-first uniform Loop subdivision algorithm: Our algorithm iterates over halfedges to ...
    • RePiX VR - Learning environment for the Rendering Pipeline in Virtual Reality 

      Heinemann, Birte; Görzen, Sergej; Schroeder, Ulrik (The Eurographics Association, 2022)
      Virtual reality can be used to support computer graphics teaching, e.g. by offering the chance to illustrate 3D processes that are difficult to convey. This paper describes the development and first evaluations of RePiX ...
    • Transparent Rendering and Slicing of Integral Surfaces Using Per-primitive Interval Arithmetic 

      Aydinlilar, Melike; Zanni, Cédric (The Eurographics Association, 2022)
      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 ...
    • Simple Techniques for a Novel Human Body Pose Optimisation Using Differentiable Inverse Rendering 

      Battogtokh, Munkhtulga; Borgo, Rita (The Eurographics Association, 2022)
      Human body 3D reconstruction has a wide range of applications including 3D-printing, art, games, and even technical sport analysis. This is a challenging problem due to 2D ambiguity, diversity of human poses, and costs in ...
    • Real-Time Path-Guiding Based on Parametric Mixture Models 

      Derevyannykh, Mikhail (The Eurographics Association, 2022)
      Path-Guiding algorithms for sampling scattering directions can drastically decrease the variance of Monte Carlo estimators of Light Transport Equation, but their production usage was limited to offline rendering because ...
    • A First Step Towards the Inference of Geological Topological Operations 

      Pascual, Romain; Belhaouari, Hakim; Arnould, Agnès; Le Gall, Pascale (The Eurographics Association, 2022)
      Procedural 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 ...
    • CUDA and Applications to Task-based Programming 

      Kerbl, Bernhard; Kenzel, Michael; Winter, Martin; Steinberger, Markus (The Eurographics Association, 2022)
      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 ...
    • A Survey on Reinforcement Learning Methods in Character Animation 

      Kwiatkowski, Ariel; Alvarado, Eduardo; Kalogeiton, Vicky; Liu, C. Karen; Pettré, Julien; Panne, Michiel van de; Cani, Marie-Paule (The Eurographics Association and John Wiley & Sons Ltd., 2022)
      Reinforcement Learning is an area of Machine Learning focused on how agents can be trained to make sequential decisions, and achieve a particular goal within an arbitrary environment. While learning, they repeatedly take ...
    • Scene Synthesis with Automated Generation of Textual Descriptions 

      Müller-Huschke, Julian; Ritter, Marcel; Harders, Matthias (The Eurographics Association, 2022)
      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 ...
    • NeuralMLS: Geometry-Aware Control Point Deformation 

      Shechter, Meitar; Hanocka, Rana; Metzer, Gal; Giryes, Raja; Cohen-Or, Daniel (The Eurographics Association, 2022)
      We 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. ...
    • Fitness of General-Purpose Monocular Depth Estimation Architectures for Transparent Structures 

      Wirth, Tristan; Jamili, Aria; Buelow, Max von; Knauthe, Volker; Guthe, Stefan (The Eurographics Association, 2022)
      Due to material properties, monocular depth estimation of transparent structures is inherently challenging. Recent advances leverage additional knowledge that is not available in all contexts, i.e., known shape or depth ...
    • Neural Motion Compression with Frequency-adaptive Fourier Feature Network 

      Tojo, Kenji; Chen, Yifei; Umetani, Nobuyuki (The Eurographics Association, 2022)
      We present a neural-network-based compression method to alleviate the storage cost of motion capture data. Human motions such as locomotion, often consist of periodic movements. We leverage this periodicity by applying ...
    • Consistent Multi- and Single-View HDR-Image Reconstruction from Single Exposures 

      Mohan, Aditya; Zhang, Jing; Cozot, Rémi; Loscos, Celine (The Eurographics Association, 2022)
      We propose a CNN-based approach for reconstructing HDR images from just a single exposure. It predicts the saturated areas of LDR images and then blends the linearized input with the predicted outputs. Two loss functions ...
    • Modeling and Enhancement of LiDAR Point Clouds from Natural Scenarios 

      Collado, José Antonio; López, Alfonso; Jiménez-Pérez, J. Roberto; Ortega, Lidia M.; Feito, Francisco R.; Jurado, Juan Manuel (The Eurographics Association, 2022)
      The generation of realistic natural scenarios is a longstanding and ongoing challenge in Computer Graphics. A common source of real-environmental scenarios is open point cloud datasets acquired by LiDAR (Laser Imaging ...