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Item A Multifragment Renderer for Material Aging Visualization(The Eurographics Association, 2018) Adamopoulos, Georgios; Moutafidou, Anastasia; Drosou, Anastasios; Tzovaras, Dimitrios; Fudos, Ioannis; Jain, Eakta and Kosinka, JirĂPeople involved in curatorial work and in preservation/conservation tasks need to understand exactly the nature of aging and to prevent it with minimal preservation work. In this scenario, it is of extreme importance to have tools to produce and visualize digital representations and models of visual surface appearance and material properties, to help the scientist understand how they evolve over time and under particular environmental conditions. We report on the development of a multifragment renderer for visualizing and combining the results of simulated aging of artwork objects. Several natural aging processes manifest themselves through change of color, fading, deformations or cracks. Furthermore, changes in the materials underneath the visible layers may be detected or simulated.Item Real-time Seamless Object Space Shading(The Eurographics Association, 2024) Li, Tianyu; Guo, Xiaoxin; Hu, Ruizhen; Charalambous, PanayiotisObject space shading remains a challenging problem in real-time rendering due to runtime overhead and object parameterization limitations. While the recently developed algorithm by Baker et al. [BJ22] enables high-performance real-time object space shading, it still suffers from seam artifacts. In this paper, we introduce an innovative object space shading system leveraging a virtualized per-halfedge texturing schema to obviate excessive shading and preclude texture seam artifacts. Moreover, we implement ReSTIR GI on our system (see Figure 1), removing the necessity of temporally reprojecting shading samples and improving the convergence of areas of disocclusion. Our system yields superior results in terms of both efficiency and visual fidelity.Item A Preliminary Analysis of Methods for Curvature Estimation on Surfaces With Local Reliefs(The Eurographics Association, 2019) Moscoso Thompson, Elia; Biasotti, Silvia; Cignoni, Paolo and Miguel, EderCurvature estimation is very popular in geometry processing for the analysis of local surface variations. Despite the large number of methods, no quantitative nor qualitative studies have been conducted for a comparative analysis of the different algorithms on surfaces with small geometric variations, such as chiselled or relief surfaces. In this work we compare eight curvature estimation methods that are commonly adopted by the computer graphics community on a number of triangle meshes derived from scans of surfaces with local reliefs.Item View Dependent Decompression for Web-based Massive Triangle Meshes Visualisation(The Eurographics Association, 2022) Cecchin, Alice; Du, Paul; Pastor, MickaĂ«l; Agouzoul, Asma; Sauvage, Basile; Hasic-Telalovic, JasminkaWe 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. These steps are repeated following a binary tree of operations, until a single compressed mesh remains. Decompressing the mesh involves progressively performing those steps in reverse, per node, and locally, by selecting the branch of the tree to explore. This method creates a compact and lossless representation of the model that allows its progressive and local reconstruction. Previously unprocessable meshes can be visualized on the web and mobile devices using this technique.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 Unsupervised Learning of Disentangled 3D Representation from a Single Image(The Eurographics Association, 2021) Lv, Junliang; Jiang, Haiyong; Xiao, Jun; Bittner, JirĂ and Waldner, ManuelaLearning 3D representation of a single image is challenging considering the ambiguity, occlusion, and perspective project of an object in an image. Previous works either seek image annotation or 3D supervision to learn meaningful factors of an object or employ a StyleGAN-like framework for image synthesis. While the first ones rely on tedious annotation and even dense geometry ground truth, the second solutions usually cannot guarantee consistency of shapes between different view images. In this paper, we combine the advantages of both frameworks and propose an image disentanglement method based on 3D representation. Results show our method facilitates unsupervised 3D representation learning while preserving consistency between images.Item A Survey on Reinforcement Learning Methods in Character Animation(The Eurographics Association and John Wiley & Sons Ltd., 2022) Kwiatkowski, Ariel; Alvarado, Eduardo; Kalogeiton, Vicky; Liu, C. Karen; PettrĂ©, Julien; Panne, Michiel van de; Cani, Marie-Paule; Meneveaux, Daniel; Patanè, GiuseppeReinforcement 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 actions based on their observation of the environment, and receive appropriate rewards which define the objective. This experience is then used to progressively improve the policy controlling the agent's behavior, typically represented by a neural network. This trained module can then be reused for similar problems, which makes this approach promising for the animation of autonomous, yet reactive characters in simulators, video games or virtual reality environments. This paper surveys the modern Deep Reinforcement Learning methods and discusses their possible applications in Character Animation, from skeletal control of a single, physically-based character to navigation controllers for individual agents and virtual crowds. It also describes the practical side of training DRL systems, comparing the different frameworks available to build such agents.Item Seamless Compressed Textures(The Eurographics Association, 2022) Maggiordomo, Andrea; Tarini, Marco; Sauvage, Basile; Hasic-Telalovic, JasminkaWe 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 artifacts in rendering; these can be prevented by careful, slight modifications a few texels around the seam. Unfortunately, GPU-based texture compression schemes are lossy and introduce their own slight modifications of texture values, nullifying that effort. The result is that texture compression may reintroduce the visual artefacts at seams. We modify a standard texture compression algorithm to make it aware of texture seams, resulting in compressed textures that still prevent the seam artefacts.Item Generative Landmarks(The Eurographics Association, 2021) Ferman, David; Bharaj, Gaurav; Bittner, JirĂ and Waldner, ManuelaWe propose a general purpose approach to detect landmarks with improved temporal consistency, and personalization. Most sparse landmark detection methods rely on laborious, manually labelled landmarks, where inconsistency in annotations over a temporal volume leads to sub-optimal landmark learning. Further, high-quality landmarks with personalization is often hard to achieve. We pose landmark detection as an image translation problem. We capture two sets of unpaired marked (with paint) and unmarked videos. We then use a generative adversarial network and cyclic consistency to predict deformations of landmark templates that simulate markers on unmarked images until these images are indistinguishable from ground-truth marked images. Our novel method does not rely on manually labelled priors, is temporally consistent, and image class agnostic - face, and hand landmarks detection examples are shown.Item Smooth Blended Subdivision Shading(The Eurographics Association, 2018) Bakker, Jelle; Barendrecht, Pieter J.; Kosinka, Jiri; Diamanti, Olga and Vaxman, AmirThe concept known as subdivision shading aims at improving the shading of subdivision surfaces. It is based on the subdivision of normal vectors associated with the control net of the surface. By either using the resulting subdivided normal field directly, or blending it with the normal field of the limit surface, renderings of higher visual smoothness can be obtained. In this work we propose a different and more versatile approach to blend the two normal fields, yielding not only better results, but also a proof that our blended normal field is C1.