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        "title": "Single-Exemplar Lighting Style Transfer via Emissive Texture Synthesis and Optimization",
        "date": "2025",
        "abstract": "Lighting is a key component in how scenes are perceived. However, many interior lighting situations are currently either handcrafted by expert designers, or simply consist of basic regular arrangements of luminaires, such as to reach uniform lighting at a predefined brightness. Our method aims to bring more interesting lighting configurations to various scenes in a semi-automatic manner designed for fast prototyping by non-expert users. Starting from a single photograph of a lighting configuration, we allow users to quickly copy and adapt a lighting style to any 3D scene. Combining image analysis, texture synthesis, and light parameter optimization, we produce a lighting design for the target 3D scene matching the input image. We validate via a user study that our results successfully transfer the desired lighting style more accurately and realistically than state-of-the-art generic style transfer methods. Furthermore, we investigate the behaviour of our method under potential altern ative choices in an ablation study.",
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        "date_from": "2025-02-26",
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        "title": "View-Independent Adjoint Light Tracing for Lighting Design Optimization",
        "date": "2024-05-22",
        "abstract": "Differentiable rendering methods promise the ability to optimize various parameters of three-dimensional (3D) scenes to achieve a desired result. However, lighting design has so far received little attention in this field. In this article, we introduce a method that enables continuous optimization of the arrangement of luminaires in a 3D scene via differentiable light tracing. Our experiments show two major issues when attempting to apply existing methods from differentiable path tracing to this problem: First, many rendering methods produce images, which restricts the ability of a designer to define lighting objectives to image space. Second, most previous methods are designed for scene geometry or material optimization and have not been extensively tested for the case of optimizing light sources. Currently available differentiable ray-tracing methods do not provide satisfactory performance, even on fairly basic test cases in our experience. In this article, we propose, to the best of our knowledge, a novel adjoint light tracing method that overcomes these challenges and enables gradient-based lighting design optimization in a view-independent (camera-free) way. Thus, we allow the user to paint illumination targets directly onto the 3D scene or use existing baked illumination data (e.g., light maps). Using modern ray-tracing hardware, we achieve interactive performance. We find light tracing advantageous over path tracing in this setting, as it naturally handles irregular geometry, resulting in less noise and improved optimization convergence. We compare our adjoint gradients to state-of-the-art image-based differentiable rendering methods. We also demonstrate that our gradient data works with various common optimization algorithms, providing good convergence behaviour. Qualitative comparisons with real-world scenes underline the practical applicability of our method.",
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        "doi": "10.1145/3662180",
        "event": "SIGGRAPH 2024",
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        "journal": "ACM Transactions on Graphics",
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        "publisher": "ASSOC COMPUTING MACHINERY",
        "volume": "43",
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            "Lighting design",
            "optimization",
            "ray tracing"
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