EG 2024 - Tutorials

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Browsing EG 2024 - Tutorials by Title

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    Design and development of VR games for Cultural Heritage using Immersive Storytelling
    (The Eurographics Association, 2024) Rizvic, Selma; Mijatovic, Bojan; Mania, Katerina; Artusi, Alessandro
    In this tutorial we introduce the whole process of creating, designing and developing a serious VR game for cultural heritage using the concept of immersive storytelling. The use of serious games in education is allowing us to offer a different approach to learning. However, designing an application with gameplay parts as well as educational components in specific area such as cultural heritage can be challenging and different to many other methodologies in the creation of similar applications. The goal of the tutorial is to show different aspects of serious game creation and usage of our immersive storytelling methodology called hyper storytelling to help with the educational elements of the game. We will go through the creation of a story for the game; the creation of scenarios for the educational gameplay part; the filming of actors on green screen and filming of 360 videos; compositing of VR videos with actors and ambisonic sound; the creation of photogrammetry items; combining educational parts with gameplay and creating connection between them; application development and finalization of the product. At the end, we will showcase our example of the game.
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    Diffusion Models for Visual Content Generation
    (The Eurographics Association, 2024) Mitra, Niloy; Mania, Katerina; Artusi, Alessandro
    Diffusion models are now the state-of-the-art for producing images. These models have been trained on vast datasets and are increasingly repurposed for various image processing and conditional image generation tasks. We expect these models to be widely used in Computer Graphics and related research areas. Image generation has evolved into a rich promise of new possibilities, and in this tutorial, we will guide you through the intricacies of understanding and using diffusion models. This tutorial is targeted towards graphics researchers with an interest in image/video synthesis and manipulation. Attending the tutorial will enable participants to build a working knowledge of the core formulation, understand how to get started in this area, and study practical use cases to explore this new tool. Our goal is to get more researchers with expertise in computer graphics to start exploring the open challenges in this topic and explore innovative use cases in CG contexts in image synthesis and other media formats. From understanding the underlying principles to hands-on implementation, you'll gain practical skills that bridge theory and application. Throughout the tutorial, we'll explore techniques for generating lifelike textures, manipulating details, and achieving remarkable visual effects. By the end, you'll have a solid foundation in utilizing diffusion models for image generation, ready to embark on your creative projects. Join us as we navigate the fascinating intersection of computer graphics and diffusion models, where pixels become canvases and algorithms transform into brushes.
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    EUROGRAPHICS 2024: Tutorials Frontmatter
    (Eurographics Association, 2024) Mania, Katerina; Artusi, Alessandro; Mania, Katerina; Artusi, Alessandro
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    Next Generation 3D Face Models
    (The Eurographics Association, 2024) Chandran, Prashanth; Yang, Lingchen; Mania, Katerina; Artusi, Alessandro
    Having a compact, expressive and artist friendly way to represent and manipulate human faces has been of prime interest to the visual effects community for the past several decades as face models play a very important role in many face capture workflows. In this short course, we go over the evolution of 3D face models used to model and animate facial identity and expression in the computer graphics community, and discuss how the recent emergence of deep face models is transforming this landscape by enabling new artistic choices. In this first installment, the course will take the audience through the evolution of face models, starting with simple blendshape models introduced in the 1980s; that continue to be extremely popular today, to recent deep shape models that utilize neural networks to represent and manipulate face shapes in an artist friendly fashion. As the course is meant to be beginner friendly, the course will commence with a quick introduction to non-neural parametric shape models starting with linear blendshape and morphable models. We will then switch focus to deep shape models, particularly those that offer intuitive control to artists. We will discuss multiple variants of such deep face models that i) allow semantic control, ii) are agnostic to the underlying topology of the manipulated shape, iii) provide the ability to explicitly model a sequence of 3D shapes or animations, and iv) allow for the simulation of physical effects. Applications that will be discussed include face shape synthesis, identity and expression interpolation, rig generation, performance retargeting, animation synthesis and more.
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    Predictive Modeling of Material Appearance: From the Drawing Board to Interdisciplinary Applications
    (The Eurographics Association, 2024) Baranoski, Gladimir V. G.; Mania, Katerina; Artusi, Alessandro
    This tutorial addresses one of the fundamental and timely topics of computer graphics research, namely the predictive modeling of material appearance. Although this topic is deeply rooted in traditional areas like rendering and natural phenomena simulation, this tutorial is not limited to cover contents connected to these areas. It also closely looks into the scientific methodology employed in the development of predictive models of light and matter interactions. Given the widespread use of this methodology to find modeling solutions for problems within and outside computer graphics, its discussion from a ''behind the scenes'' perspective aims to underscore practical and far-reaching aspects of interdisciplinary research that are often overlooked in related publications. More specifically, this tutorial unveils constraints and pitfalls found in each of the key stages of the model development process, namely data collection, design and evaluation, and brings forward alternatives to tackle them effectively. Furthermore, besides being a central component of realistic image synthesis frameworks, predictive material appearance models have a scope of applications that can be extended far beyond the generation of believable images. For instance, they can be employed to accelerate the hypothesis generation and validation cycles of research across a wide range of fields, from biology and medicine to photonics and remote sensing, among others. These models can also be used to generate comprehensive in silico (computational) datasets to support the translation of knowledge advances in those fields to real-world applications (e.g., the noninvasive screening of medical conditions and the remote detection of environmental hazards). In fact, a number of them are already being used in physical and life sciences, notably to support investigations seeking to strengthen the current understanding about material appearance changes prompted by mechanisms which cannot be fully studied using standard ''wet'' experimental procedures. Accordingly, such interdisciplinary research initiatives are also discussed in this tutorial through selected case studies involving the use of predictive material appearance models to elucidate challenging scientific questions.