Now showing items 1-16 of 16

    • Parallel Loop Subdivision with Sparse Adjacency Matrix 

      Wang, Kechun; Chen, Renjie (The Eurographics Association, 2023)
      Subdivision surface is a popular technique for geometric modeling. Recently, several parallel implementations have been developed for Loop subdivision on the GPU. However, these methods are built on complex data structures ...
    • Tight Bounding Boxes for Voxels and Bricks in a Signed Distance Field Ray Tracer 

      Hansson-Söderlund, Herman; Akenine-Möller, Tomas (The Eurographics Association, 2023)
      We present simple methods to compute tight axis-aligned bounding boxes for voxels and for bricks of voxels in a signed distance function renderer based on ray tracing. Our results show total frame time reductions of 20-31% ...
    • EUROGRAPHICS 2023: Short Papers Frontmatter 

      Babaei, Vahid; Skouras, Melina (Eurographics Association, 2023)
    • Velocity-Based LOD Reduction in Virtual Reality: A Psychophysical Approach 

      Petrescu, David; Warren, Paul A.; Montazeri, Zahra; Pettifer, Steve (The Eurographics Association, 2023)
      Virtual Reality headsets enable users to explore the environment by performing self-induced movements. The retinal velocity produced by such motion reduces the visual system's ability to resolve fine detail. We measured ...
    • Text2PointCloud: Text-Driven Stylization for Sparse PointCloud 

      Hwang, Inwoo; Kim, Hyeonwoo; Lim, Donggeun; Park, Inbum; Kim, Young Min (The Eurographics Association, 2023)
      We present Text2PointCloud, a method to process sparse, noisy point cloud input and generate high-quality stylized output. Given point cloud data, our iterative pipeline stylizes and deforms points guided by a text description ...
    • CLIP-based Neural Neighbor Style Transfer for 3D Assets 

      Mishra, Shailesh; Granskog, Jonathan (The Eurographics Association, 2023)
      We present a method for transferring the style from a set of images to the texture of a 3D object. The texture of an asset is optimized with a differentiable renderer and losses using pretrained deep neural networks. More ...
    • Is Drawing Order Important? 

      Qiu, Sherry; Wang, Zeyu; McMillan, Leonard; Rushmeier, Holly; Dorsey, Julie (The Eurographics Association, 2023)
      The drawing process is crucial to understanding the final result of a drawing. There has been a long history of understanding human drawing; what kinds of strokes people use and where they are placed. An area of interest ...
    • Quick-Pro-Build: A Web-based Approach for Quick Procedural 3D Reconstructions of Buildings 

      Bohlender, Bela; Mühlhäuser, Max; Guinea, Alejandro Sanchez (The Eurographics Association, 2023)
      We present Quick-Pro-Build, a web-based approach for quick procedural 3D reconstruction of buildings. Our approach allows users to quickly and easily create realistic 3D models using two integrated reference views: street ...
    • Efficient Needle Insertion Simulation using Hybrid Constraint Solver and Isolated DOFs 

      Martin, Claire; Zeng, Ziqiu; Courtecuisse, Hadrien (The Eurographics Association, 2023)
      This paper introduces a real-time compatible method to improve the location of constraints between a needle and tissues in the context of needle insertion simulation. This method is based on intersections between the Finite ...
    • Luminance-Preserving and Temporally Stable Daltonization 

      Ebelin, Pontus; Crassin, Cyril; Denes, Gyorgy; Oskarsson, Magnus; Åström, Kalle; Akenine-Möller, Tomas (The Eurographics Association, 2023)
      We propose a novel, real-time algorithm for recoloring images to improve the experience for a color vision deficient observer. The output is temporally stable and preserves luminance, the most important visual cue. It runs ...
    • Automatic Step Size Relaxation in Sphere Tracing 

      Bán, Róbert; Valasek, Gábor (The Eurographics Association, 2023)
      We propose a robust auto-relaxed sphere tracing method that automatically scales its step sizes based on data from previous iterations. It possesses a scalar hyperparemeter that is used similarly to the learning rate of ...
    • Guiding Light Trees for Many-Light Direct Illumination 

      Hamann, Eric; Jung, Alisa; Dachsbacher, Carsten (The Eurographics Association, 2023)
      Path guiding techniques reduce the variance in path tracing by reusing knowledge from previous samples to build adaptive sampling distributions. The Practical Path Guiding (PPG) approach stores and iteratively refines an ...
    • Photogrammetric Reconstruction of a Stolen Statue 

      Liu, Zishun; Doubrovski, Eugeni L.; Geraedts, Jo M. P.; Wang, Wenting; Yam, Yeung; Wang, Charlie C. L. (The Eurographics Association, 2023)
      In this paper, we propose a method to reconstruct a digital 3D model of a stolen/damaged statue using photogrammetric methods. This task is challenging because the number of available photos for a stolen statue is in general ...
    • PointCloudSlicer: Gesture-based Segmentation of Point Clouds 

      Gowtham, Hari Hara; Parakkat, Amal Dev; Cani, Marie-Paule (The Eurographics Association, 2023)
      Segmentation is a fundamental problem in point-cloud processing, addressing points classification into consistent regions, the criteria for consistency being based on the application. In this paper, we introduce a simple, ...
    • Towards L-System Captioning for Tree Reconstruction 

      Magnusson, Jannes S.; Hilsmann, Anna; Eisert, Peter (The Eurographics Association, 2023)
      This work proposes a novel concept for tree and plant reconstruction by directly inferring a Lindenmayer-System (L-System) word representation from image data in an image captioning approach. We train a model end-to-end ...
    • Out-of-the-loop Autotuning of Metropolis Light Transport with Reciprocal Probability Binning 

      Herveau, Killian; Otsu, Hisanari; Dachsbacher, Carsten (The Eurographics Association, 2023)
      The performance of Markov Chain Monte Carlo (MCMC) rendering methods depends heavily on the mutation strategies and their parameters. We treat the underlying mutation strategies as black-boxes and focus on their parameters. ...