Posters
Geometric Deformation for Reducing Optic Flow and Cybersickness Dose Value in VR
Ruding Lou, Richard H. Y. So, and Dominique Bechmann
RGB-D Neural Radiance Fields: Local Sampling for Faster Training
Arnab Dey and Andrew I. Comport
Fixed-radius Near Neighbors Searching for 2D Simulations on the GPU using Delaunay Triangulations
Heinich Porro, Benoît Crespin, Nancy Hitschfeld-Kahler, and Cristobal Navarro
Splash in a Flash: Sharpness-aware Minimization for Efficient Liquid Splash Simulation
Vishrut Jetly, Hikaru Ibayashi, and Aiichiro Nakano
Consistent Multi- and Single-View HDR-Image Reconstruction from Single Exposures
Aditya Mohan, Jing Zhang, Rémi Cozot, and Celine Loscos
A First Step Towards the Inference of Geological Topological Operations
Romain Pascual, Hakim Belhaouari, Agnès Arnould, and Pascale Le Gall
Multimodal Early Raw Data Fusion for Environment Sensing in Automotive Applications
Marcelo Eduardo Pederiva, José Mario De Martino, and Alessandro Zimmer
Fast and Fine Disparity Reconstruction for Wide-baseline Camera Arrays with Deep Neural Networks
Théo Barrios, Julien Gerhards, Stéphanie Prévost, and Celine Loscos
3D Human Shape and Pose from a Single Depth Image with Deep Dense Correspondence Enabled Model Fitting
Xiaofang Wang, Adnane Boukhayma, Stéphanie Prévost, Eric Desjardin, Celine Loscos, and Franck Multon
Seamless Compressed Textures
Andrea Maggiordomo and Marco Tarini
Stroke based Painterly Inbetweening
Nicolas Barroso, Amélie Fondevilla, and David Vanderhaeghe
Neural Denoising for Spectral Monte Carlo Rendering
Robin Rouphael, Mathieu Noizet, Stéphanie Prévost, Hervé Deleau, Luiz-Angelo Steffenel, and Laurent Lucas
Transfer Textures for Fast Precomputed Radiance Transfer
Sirikonda Dhawal, Aakash Kt, and P. J. Narayanan
SIG-based Curve Reconstruction
Diana Marin, Stefan Ohrhallinger, and Michael Wimmer
Time Series AMR Data Representation for Out-of-core Interactive Visualization
Welcome Alexandre-Barff, Hervé Deleau, Jonathan Sarton, Franck Ledoux, and Laurent Lucas
View Dependent Decompression for Web-based Massive Triangle Meshes Visualisation
Alice Cecchin, Paul Du, Mickaël Pastor, and Asma Agouzoul
Modeling and Enhancement of LiDAR Point Clouds from Natural Scenarios
José Antonio Collado, Alfonso López, J. Roberto Jiménez-Pérez, Lidia M. Ortega, Francisco R. Feito, and Juan Manuel Jurado
Hermite Interpolation of Heightmaps
Róbert Bán and Gábor Valasek

Recent Submissions

  • Hermite Interpolation of Heightmaps 

    Bán, Róbert; Valasek, Gábor (The Eurographics Association, 2022)
    Heightmaps are ubiquitous in real-time computer graphics. They are used to describe geometric detail over an underlying coarser surface. Various techniques, such as parallax occlusion mapping and relief mapping, use heightmap ...
  • EUROGRAPHICS 2022: Posters Frontmatter 

    Sauvage, Basile; Hasic-Telalovic, Jasminka (The Eurographics Association, 2022)
  • 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 ...
  • View Dependent Decompression for Web-based Massive Triangle Meshes Visualisation 

    Cecchin, Alice; Du, Paul; Pastor, Mickaël; Agouzoul, Asma (The Eurographics Association, 2022)
    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. ...
  • Time Series AMR Data Representation for Out-of-core Interactive Visualization 

    Alexandre-Barff, Welcome; Deleau, Hervé; Sarton, Jonathan; Ledoux, Franck; Lucas, Laurent (The Eurographics Association, 2022)
    Time-varying Adaptive Mesh Refinement (AMR) data have become an essential representation for 3D numerical simulations in many scientific fields. This observation is even more relevant considering that the data volumetry ...
  • SIG-based Curve Reconstruction 

    Marin, Diana; Ohrhallinger, Stefan; Wimmer, Michael (The Eurographics Association, 2022)
    We introduce a new method to compute the shape of an unstructured set of two-dimensional points. The algorithm exploits the to-date rarely used proximity-based graph called spheres-of-influence graph (SIG). We filter edges ...
  • Transfer Textures for Fast Precomputed Radiance Transfer 

    Dhawal, Sirikonda; Kt, Aakash; Narayanan, P. J. (The Eurographics Association, 2022)
    Precomputed Radiance Transfer (PRT) can achieve high-quality renders of glossy materials at real-time framerates. PRT involves precomputing a k-dimensional transfer vector or a k×k- matrix of Spherical Harmonic (SH) ...
  • Stroke based Painterly Inbetweening 

    Barroso, Nicolas; Fondevilla, Amélie; Vanderhaeghe, David (The Eurographics Association, 2022)
    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 ...
  • Neural Denoising for Spectral Monte Carlo Rendering 

    Rouphael, Robin; Noizet, Mathieu; Prévost, Stéphanie; Deleau, Hervé; Steffenel, Luiz-Angelo; Lucas, Laurent (The Eurographics Association, 2022)
    Spectral Monte Carlo (MC) rendering is still to be largely adopted partially due to the specific noise, called color noise, induced by wavelength-dependent phenomenons. Motivated by the recent advances in Monte Carlo noise ...
  • 3D Human Shape and Pose from a Single Depth Image with Deep Dense Correspondence Enabled Model Fitting 

    Wang, Xiaofang; Boukhayma, Adnane; Prévost, Stéphanie; Desjardin, Eric; Loscos, Celine; Multon, Franck (The Eurographics Association, 2022)
    We propose a two-stage hybrid method, with no initialization, for 3D human shape and pose estimation from a single depth image, combining the benefits of deep learning and optimization. First, a convolutional neural network ...
  • Seamless Compressed Textures 

    Maggiordomo, Andrea; Tarini, Marco (The Eurographics Association, 2022)
    We present an algorithm to hide discontinuity artifacts at seams in GPU compressed textures. Texture mapping requires UV-maps, and UV-maps (in general) require texture seams; texture seams (in general) cause small visual ...
  • Multimodal Early Raw Data Fusion for Environment Sensing in Automotive Applications 

    Pederiva, Marcelo Eduardo; Martino, José Mario De; Zimmer, Alessandro (The Eurographics Association, 2022)
    Autonomous Vehicles became every day closer to becoming a reality in ground transportation. Computational advancement has enabled powerful methods to process large amounts of data required to drive on streets safely. The ...
  • 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. ...