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Subject: Ray tracing × Has files: true ×

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    Selective Caching in Procedural Texture Graphs for Path Tracing
    (The Eurographics Association, 2025) Schüßler, Vincent; Hanika, Johannes; Sauvage, Basile; Dischler, Jean-Michel; Dachsbacher, Carsten; Wang, Beibei; Wilkie, Alexander
    Procedural texturing is crucial for adding details in large-scale rendering. Typically, procedural textures are represented as computational graphs that artists can edit. However, as scene and graph complexity grow, evaluating these graphs becomes increasingly expensive for the rendering system. Performance is greatly affected by the evaluation strategy: Precomputing textures into high resolution maps is straightforward but can be inefficient, while shade-on-hit architectures and tile-based caches improve efficiency by evaluating only necessary data. However, the ideal choice of strategy depends on the application context. We present a new method to dynamically select which texture graph nodes to cache within a rendering system that supports filtered texture graph evaluation and tile-based caching. Our method allows us to construct an optimized evaluation strategy for each scene. Cache-friendly nodes are identified using data-driven predictions based on statistics of requested texture footprints, gathered during a profiling phase. We develop a statistical model that fits profiling data and predicts how caching specific nodes affects evaluation efficiency and storage demands. Our approach can be directly integrated into a rendering system or used to analyze renderer data, helping practitioners to optimize performance in their workflows.
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    Radiative Backpropagation with Non-Static Geometry
    (The Eurographics Association, 2025) Worchel, Markus; Finnendahl, Ugo; Alexa, Marc; Wang, Beibei; Wilkie, Alexander
    Radiative backpropagation-based (RB) methods efficiently compute reverse-mode derivatives in physically-based differentiable rendering by simulating the propagation of differential radiance. A key assumption is that differential radiance is transported like normal radiance. We observe that this holds only when scene geometry is static and demonstrate that current implementations of radiative backpropagation produce biased gradients when scene parameters change geometry. In this work, we derive the differential transport equation without assuming static geometry. An immediate consequence is that the parameterization matters when the sampling process is not differentiated: only surface integrals allow a local formulation of the derivatives, i.e., one in which moving surfaces do not affect the entire path geometry. While considerable effort has been devoted to handling discontinuities resulting from moving geometry, we show that a biased interior derivative compromises even the simplest inverse rendering tasks, regardless of discontinuities. An implementation based on our derivation leads to systematic convergence to the reference solution in the same setting and provides unbiased RB interior derivatives for path-space differentiable rendering.
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    Less can be more: A Footprint-driven Heuristic to skip Wasted Connections and Merges in Bidirectional Rendering
    (The Eurographics Association, 2025) Yazici, Ömercan; Grittmann, Pascal; Slusallek, Philipp; Wang, Beibei; Wilkie, Alexander
    Bidirectional rendering algorithms can robustly render a wide range of scenes and light transport effects. Their robustness stems from the fact that they combine a huge number of sampling techniques: Paths traced from the camera are combined with paths traced from the lights by connecting or merging their vertices in all possible combinations. The flip side of this robustness is that efficiency suffers because most of these connections and merges are not useful - their samples will have a weight close to zero. Skipping these wasted computations is hence desirable. Prior work has attempted this via manual parameter tuning, by classifying materials as ''specular'', ''glossy'', or ''diffuse'', or via costly data-driven adaptation. We, instead, propose a simple footprint-driven heuristic to selectively enable only the most impactful bidirectional techniques. Our heuristic is based only on readily available PDF values, does not require manual tuning, supports arbitrarily complex material systems, and does not require precomputation.
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    Spatio-Temporal Dithering for Order-Independent Transparency on Ray Tracing Hardware
    (The Eurographics Association, 2025) Brüll, Felix; Kern, René; Grosch, Thorsten; Wang, Beibei; Wilkie, Alexander
    Efficient rendering of many transparent surfaces is a challenging problem in real-time ray tracing. We introduce an alternative approach to conventional order-independent transparency (OIT) techniques: our method interprets the alpha channel as coverage and uses state-of-the-art temporal anti-aliasing techniques to accumulate transparency over multiple frames. By efficiently utilizing ray tracing hardware and its early ray termination capabilities, our method reduces computational costs compared to conventional OIT methods. Furthermore, our approach shades only one fragment per pixel, significantly lowering the shading workload and improving frame rate stability. Despite relying on temporal accumulation, our technique performs well in dynamic scenes.
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    Convergence Estimation of Markov-Chain Monte Carlo Rendering
    (The Eurographics Association, 2025) Yu, Rui; Sun, Guangzhong; Zhao, Shuang; Dong, Yue; Wang, Beibei; Wilkie, Alexander
    We present a theoretical framework for estimating the convergence of Markov-Chain Monte Carlo (MCMC) rendering algorithms. Our theory considers both the variance and the correlation between samples, allowing for quantitative analyses of the convergence properties of MCMC estimators. With our theoretical framework, we devise a Monte Carlo (MC) algorithm capable of accurately estimating the expected MSE of an MCMC rendering algorithm. By adopting an efficient rejection sampling scheme, our MC-based MSE estimator yields a lower standard deviation compared to directly measuring the MSE by running the MCMC rendering algorithm multiple times. Moreover, we demonstrate that modifying the target distribution of the Markov chain by roughening the specular BRDF might lead to faster convergence on some scenarios. This finding suggests that our estimator can serve as a potential guide for selecting the target distribution.