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        "title": "Sampling-Distribution-Based Evaluation for Monte Carlo Rendering",
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        "abstract": "In this paper, we investigate the application of per-pixel difference metrics for evaluating Monte Carlo (MC) rendering techniques. In particular, we propose to take the sampling distribution of the mean (SDM) into account for this purpose. We establish the theoretical background and analyze other per-pixel difference metrics, such as the absolute deviation (AD) and the mean squared error (MSE) in relation to the SDM. Based on insights from this analysis, we propose a new, alternative, and particularly easy-to-use approach, which builds on the SDM and facilitates meaningful comparisons of MC rendering techniques on a per-pixel basis. In order to demonstrate the usefulness of our approach, we compare it to commonly used metrics based on a variety of images computed with different rendering techniques. Our evaluation reveals limitations of commonly used metrics, in particular regarding the detection of differences between renderings that might be difficult to detect otherwise—this circ umstance is particularly apparent in comparison to the MSE calculated for each pixel. Our results indicate the potential of SDM-based approaches to reveal differences between MC renderers that might be caused by conceptual or implementation-related issues. Thus, we understand our approach as a way to facilitate the development and evaluation of rendering techniques.",
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        "booktitle": "Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications",
        "date_from": "2023-02-19",
        "date_to": "2023-02-21",
        "doi": "10.5220/0011886300003417",
        "event": "18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (GRAPP)",
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                "abstract": "The rendering of 3D models and scenes has been a major, long-standing challenge in computer graphics that can be divided into two major subfields. <em>Real-time rendering</em> refers to the real-time synthesis of images on commodity graphics hardware to facilitate interaction for visualizations or computer games. The field of <em>physically based rendering</em> focuses on algorithms that accurately simulate the physics of light for use in the movie industry, architectural visualizations, etc. Compared to real-time rendering methods, these algorithms generally require a considerable amount of time (i.e., hours up to days) to generate acceptable results.\n\nIn the context of real-time rendering, our work revolves around the development of algorithms to achieve higher visual quality. Furthermore, we work on techniques to accelerate physically based rendering algorithms to make them viable for interactive rendering. Another aspect of our research work revolves around tools that facilitate the work of content creators.",
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                "id": "Rendering",
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                "short_abstract": "In this area, we concentrate on algorithms that synthesize images to depict 3D models or scenes, often by simulating or approximating the physics of light.",
                "abstract": "The rendering of 3D models and scenes has been a major, long-standing challenge in computer graphics that can be divided into two major subfields. <em>Real-time rendering</em> refers to the real-time synthesis of images on commodity graphics hardware to facilitate interaction for visualizations or computer games. The field of <em>physically based rendering</em> focuses on algorithms that accurately simulate the physics of light for use in the movie industry, architectural visualizations, etc. Compared to real-time rendering methods, these algorithms generally require a considerable amount of time (i.e., hours up to days) to generate acceptable results.\n\nIn the context of real-time rendering, our work revolves around the development of algorithms to achieve higher visual quality. Furthermore, we work on techniques to accelerate physically based rendering algorithms to make them viable for interactive rendering. Another aspect of our research work revolves around tools that facilitate the work of content creators.",
                "website": "https://www.cg.tuwien.ac.at/research/area/Rendering",
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                "abstract": "The synthesis of photorealistic images has always been a major challenge in the field of computer graphics and is of great relevance for many applications such as motion picture production, computer games and architectural lighting simulations. Despite our detailed knowledge behind the physical processes of light transport, accurate and efficient simulation is still a challenge and subject to a vast amount of research work. This is due to the fact that light transport is extremely intricate: a single photon, emitted from a particular light source, can interact many times with various materials until it finally reaches the human eye.\n\nCurrent state-of-the-art methods in the field of photorealistic rendering rely on Monte Carlo integration of the incident radiance. As opposed to traditional physical applications, where the solution emerges as the result of one Monte Carlo process, photorealistic rendering is, by principle, different: a separate Monte Carlo process is run for every pixel, resulting in visually unpleasant images. We show that in order to completely eliminate the noise, one either has to resort to rendering an enormous amount of samples per pixel (up to the order of hundreds of thousands) or use noise filtering, where we show that as of now, all methods have their inherent drawbacks.\n\nHowever, our experiments and experience have led us to two key insights that will open up the road towards noise-free photorealistic rendering:\n\nOur first key insight is that the most difficult light-transport phenomena usually exist on a low-dimensional manifold that can be specifically sampled exhaustively, resulting in images that are completely noise-free with respect to these difficult light-transport situations.\n\nOur second key insight is that noise filtering is a viable way to mitigate noise for simple light transport effects, such as low-frequency illumination on diffuse surfaces. \n\nConsequently, the goal of this project is to develop a fundamentally new method that it combines the approaches of (1) exhaustively sampling special path-space manifolds and (2) applying noise filtering to the remaining space. To this end, we will provide a mathematical model to quantify the effectiveness of modern noise-filtering methods.\n\nMore concretely, the project will make the following contributions to photorealistic rendering:\n\n(1) An analysis and visualization of the space of light paths to build a better understanding how most state-of-the-art algorithms can be improved to perform better in challenging light-transport situations.\n(2) A new class of algorithms that are capable of rendering the most difficult light-transport situations effectively in a fundamentally new way that guarantees that these phenomena always appear completely smooth and converged.\n\n(3) A new way of combining noise-filtering techniques with photorealistic rendering algorithms, where each technique is used for the subclass of light paths where it is the most useful.\n",
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        "title": "Gaussian Material Synthesis",
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        "abstract": "We present a learning-based system for rapid mass-scale material synthesis that is useful for novice and expert users alike. The user preferences are learned via Gaussian Process Regression and can be easily sampled for new recommendations. Typically, each recommendation takes 40-60 seconds to render with global illumination, which makes this process impracticable for real-world workflows. Our neural network eliminates this bottleneck by providing high-quality image predictions in real time, after which it is possible to pick the desired materials from a gallery and assign them to a scene in an intuitive manner. Workflow timings against Disney’s “principled” shader reveal that our system scales well with the number of sought materials, thus empowering even novice users to generate hundreds of high-quality material models without any expertise in material modeling. Similarly, expert users experience a significant decrease in the total modeling time when populating a scene with materials. Furthermore, our proposed solution also offers controllable recommendations and a novel latent space variant generation step to enable the real-time fine-tuning of materials without requiring any domain expertise.",
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        "doi": "10.1145/3197517.3201307",
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        "journal": "ACM Transactions on Graphics (SIGGRAPH 2018)",
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                "abstract": "Creating photorealistic images has always been an essential goal in computer graphics. The image generation process builds on a complex mathematical construct, the so-called rendering equation. This equation defines how light interacts with surfaces in a virtual scene, and involves complex surface description models that describe important effects like reflections, glossy surface interactions, and indirect illumination. Solving this equation can be achieved by investing a large amount of time and computational resources, but intelligent methods have been found that greatly speed up the calculations up to an interactive or even real-time frame rates. Both interactive as well as any non-interactive applications such as computer games, visual effects, architectural lighting simulation, urban and automotive design, disaster simulation and many other applications that depend on an accurate light simulation, profit from efficient ways to calculate light transport.\nThese methods can be categorized by being a part of the mathematical field of functional analysis where a large body of research exists because it forms the basis for scientific fields such as quantum mechanics, chaos and ergodic theory, vision and signal processing besides countless specialized applications in areas like structural mechanics, simulation and other engineering problems. Applications of Fourier or Laplace transformations, Spherical Harmonics or Wavelets, just to name a few important approaches, are ubiquitous.\nHowever, despite the considerable amount of research work devoted to finding methods to calculate and analyze the complex light transport in a virtual scene, they remain challenging issues and many inherent properties of light transport are largely unknown.\nOver the course of the last 10 years, a more general form of wavelets, named anisotropic wavelets that introduce directionality to the basis definitions have been proposed. In particular, curvelets and contourlets have already proven to be powerful tools in astrophysics, seismology, fluid dynamics and vision due to their unique properties optimized for natural signals.\nYet, anisotropic wavelets have not been considered for light transport, though they have several advantages over standard wavelets such as a higher sparsity or near-optimal representation. Therefore, the main goal of this project is to develop methods based on anisotropic wavelets that calculate all aspects of light transport more efficiently, delivering a higher image quality with fewer resources, including an adaptation to all principal domains used in computer graphics.  Due to their properties, anisotropic wavelets also form an excellent foundation to perform a fundamental multi-scale and multi-directional analysis of light transport which leads to a better understanding and deeper into the process of light transport in virtual scenes.\n",
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            {
                "id": "Mofa",
                "workgroup_id": "rend",
                "drupal_id": 4209,
                "drupal_path": "/research/projects/Mofa",
                "name": "Modern Functional Analysis in Computer Graphics",
                "name_de": null,
                "short_title": "Mofa",
                "website": null,
                "status": "active",
                "short_abstract": "The projects develops new mathematical foundations for global-illumination algorithms.",
                "abstract": "Creating photorealistic images has always been an essential goal in computer graphics. The image generation process builds on a complex mathematical construct, the so-called rendering equation. This equation defines how light interacts with surfaces in a virtual scene, and involves complex surface description models that describe important effects like reflections, glossy surface interactions, and indirect illumination. Solving this equation can be achieved by investing a large amount of time and computational resources, but intelligent methods have been found that greatly speed up the calculations up to an interactive or even real-time frame rates. Both interactive as well as any non-interactive applications such as computer games, visual effects, architectural lighting simulation, urban and automotive design, disaster simulation and many other applications that depend on an accurate light simulation, profit from efficient ways to calculate light transport.\nThese methods can be categorized by being a part of the mathematical field of functional analysis where a large body of research exists because it forms the basis for scientific fields such as quantum mechanics, chaos and ergodic theory, vision and signal processing besides countless specialized applications in areas like structural mechanics, simulation and other engineering problems. Applications of Fourier or Laplace transformations, Spherical Harmonics or Wavelets, just to name a few important approaches, are ubiquitous.\nHowever, despite the considerable amount of research work devoted to finding methods to calculate and analyze the complex light transport in a virtual scene, they remain challenging issues and many inherent properties of light transport are largely unknown.\nOver the course of the last 10 years, a more general form of wavelets, named anisotropic wavelets that introduce directionality to the basis definitions have been proposed. In particular, curvelets and contourlets have already proven to be powerful tools in astrophysics, seismology, fluid dynamics and vision due to their unique properties optimized for natural signals.\nYet, anisotropic wavelets have not been considered for light transport, though they have several advantages over standard wavelets such as a higher sparsity or near-optimal representation. Therefore, the main goal of this project is to develop methods based on anisotropic wavelets that calculate all aspects of light transport more efficiently, delivering a higher image quality with fewer resources, including an adaptation to all principal domains used in computer graphics.  Due to their properties, anisotropic wavelets also form an excellent foundation to perform a fundamental multi-scale and multi-directional analysis of light transport which leads to a better understanding and deeper into the process of light transport in virtual scenes.\n",
                "start_date": "2012-10-01",
                "end_date": "2016-05-31",
                "leader_id": 193,
                "logo": null,
                "funding_organisations": [
                    {
                        "id": "fwf",
                        "contract_number": "P23700-N23",
                        "comment": null
                    }
                ],
                "research_areas": [
                    "Rendering"
                ],
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                "url": "https://www.cg.tuwien.ac.at/research/projects/Mofa",
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        "url": "https://www.cg.tuwien.ac.at/research/publications/2014/zsolnai-ist-invited-2014/",
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