Now showing items 201-220 of 2886

    • Fast and Fine Disparity Reconstruction for Wide-baseline Camera Arrays with Deep Neural Networks 

      Barrios, Théo; Gerhards, Julien; Prévost, Stéphanie; Loscos, Celine (The Eurographics Association, 2022)
      Recently, disparity-based 3D reconstruction for stereo camera pairs and light field cameras have been greatly improved with the uprising of deep learning-based methods. However, only few of these approaches address ...
    • 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 ...
    • 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 ...
    • Splash in a Flash: Sharpness-aware Minimization for Efficient Liquid Splash Simulation 

      Jetly, Vishrut; Ibayashi, Hikaru; Nakano, Aiichiro (The Eurographics Association, 2022)
      We present sharpness-aware minimization (SAM) for fluid dynamics which can efficiently learn the plausible dynamics of liquid splashes. Due to its ability to achieve robust and generalizing solutions, SAM efficiently ...
    • Fixed-radius Near Neighbors Searching for 2D Simulations on the GPU using Delaunay Triangulations 

      Porro, Heinich; Crespin, Benoît; Hitschfeld-Kahler, Nancy; Navarro, Cristobal (The Eurographics Association, 2022)
      We propose to explore a GPU solution to the fixed-radius nearest-neighbor problem in 2D based on Delaunay triangulations. This problem is crucial for many particle-based simulation techniques for collision detection or ...
    • RGB-D Neural Radiance Fields: Local Sampling for Faster Training 

      Dey, Arnab; Comport, Andrew I. (The Eurographics Association, 2022)
      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 ...
    • Geometric Deformation for Reducing Optic Flow and Cybersickness Dose Value in VR 

      Lou, Ruding; So, Richard H. Y.; Bechmann, Dominique (The Eurographics Association, 2022)
      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. ...
    • Virtual Ray Tracer 

      Verschoore de la Houssaije, Willard A.; Wezel, Chris S. van; Frey, Steffen; Kosinka, Jiri (The Eurographics Association, 2022)
      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 ...
    • EUROGRAPHICS 2022: Education Papers Frontmatter 

      Bourdin, Jean-Jacques; Paquette, Eric (The Eurographics Association, 2022)
    • The Road to Vulkan: Teaching Modern Low-Level APIs in Introductory Graphics Courses 

      Unterguggenberger, Johannes; Kerbl, Bernhard; Wimmer, Michael (The Eurographics Association, 2022)
      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 ...
    • Mesh Smoothing for Teaching GLSL Programming 

      Ilinkin, Ivaylo (The Eurographics Association, 2022)
      This 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 ...
    • Digital Matte Painting - An Effective Undergraduate Assignment 

      Redford, Adam; Anderson, Eike Falk (The Eurographics Association, 2022)
      This paper presents an effective digital matte painting assignment from a course delivered as part of an undergraduate degree programme in visual effects. The assignment involves the creation of a final 3D shot from an ...
    • Evaluating Bloom's Taxonomy-based Learning Modules for Parallel Coordinates Literacy 

      Peng, Ilena; Firat, Elif E.; Laramee, Robert S.; Joshi, Alark (The Eurographics Association, 2022)
      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, ...
    • 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 ...
    • Introduction to Computer Graphics: A Visual Interactive Approach 

      Loscos, Celine (The Eurographics Association, 2022)
      Computer graphics is a difficult topic, requiring associating mathematics and programming skills. When initially taught at undergraduate levels, there are several factors which discourage students. First, programming a ...
    • 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 ...
    • Advances in Neural Rendering 

      Tewari, Ayush; Thies, Justus; Mildenhall, Ben; Srinivasan, Pratul; Tretschk, Edith; Wang, Yifan; Lassner, Christoph; Sitzmann, Vincent; Martin-Brualla, Ricardo; Lombardi, Stephen; Simon, Tomas; Theobalt, Christian; Nießner, Matthias; Barron, Jon T.; Wetzstein, Gordon; Zollhöfer, Michael; Golyanik, Vladislav (The Eurographics Association and John Wiley & Sons Ltd., 2022)
      Synthesizing photo-realistic images and videos is at the heart of computer graphics and has been the focus of decades of research. Traditionally, synthetic images of a scene are generated using rendering algorithms such ...
    • 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 ...
    • 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 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 ...