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Recent Submissions

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Ray Traced Stochastic Depth Map for Ambient Occlusion

(The Eurographics Association, 2024) Brüll, Felix; Kern, René; Grosch, Thorsten; Haines, Eric; Garces, Elena

Screen-space ambient occlusion is a popular technique for approximating global illumination in real-time rendering. However, it suffers from artifacts due to the lack of information from the depth buffer. A stochastic depth map [VSE21] can be used to retrieve most of the missing information, but it is not suitable for real-time rendering in large scenes. In this paper, we propose a new stochastic depth map acquisition method powered by hardware ray tracing, which shows better performance characteristics than the previous method. We present further improvements that increase the quality and performance of the stochastic depth map generation. Furthermore, the results are almost indistinguishable from a ground truth solution with all depth samples.

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Learning Self-Shadowing for Clothed Human Bodies

(The Eurographics Association, 2024) Einabadi, Farshad; Guillemaut, Jean-Yves; Hilton, Adrian; Haines, Eric; Garces, Elena

This paper proposes to learn self-shadowing on full-body, clothed human postures from monocular colour image input, by supervising a deep neural model. The proposed approach implicitly learns the articulated body shape in order to generate self-shadow maps without seeking to reconstruct explicitly or estimate parametric 3D body geometry. Furthermore, it is generalisable to different people without per-subject pre-training, and has fast inference timings. The proposed neural model is trained on self-shadow maps rendered from 3D scans of real people for various light directions. Inference of shadow maps for a given illumination is performed from only 2D image input. Quantitative and qualitative experiments demonstrate comparable results to the state of the art whilst being monocular and achieving a considerably faster inference time. We provide ablations of our methodology and further show how the inferred self-shadow maps can benefit monocular full-body human relighting.

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Real-Time Pixel-Perfect Hard Shadows with Leak Tracing

(The Eurographics Association, 2024) Kern, René; Brüll, Felix; Grosch, Thorsten; Haines, Eric; Garces, Elena

Accurate shadows greatly enhance the realism of a rendered image. Shadow mapping is the preferred solution for shadows in real-time applications. However, shadow maps suffer from discretization errors and self-shadowing artifacts, that need custom parameter tuning per scene. Filterable shadow maps such as variance or moment shadow maps solve both issues but introduce light leaking. With the advent of hardware ray tracing, it becomes more realistic to use shadow rays instead of a shadow map. However, distributing a shadow ray is often more expensive than evaluating a shadow map, especially if the ray hits alphatested geometry. We introduce leak tracing, where we use filterable shadow maps techniques on top of default shadow maps and eliminate the light leaks and aliased shadow edges with selective ray tracing. Our algorithm does not need any scene-dependent parameters. We achieve an average speedup ranging from 1.19 to 1.79, with a top speedup of 4.17, depending on the scene and eliminate major performance drops caused by alpha-tested geometry during ray tracing. Our solution is temporally stable and reaches similar quality as pure ray tracing.

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Precomputed Dynamic Appearance Synthesis and Rendering

(The Eurographics Association, 2024) Bai, Yaoyi; Hasan, Miloš; Yan, Ling-Qi; Haines, Eric; Garces, Elena

Interpolation between objects of varying dimensionality is a common task in computer graphics; however, high-quality dynamic natural interpolation for appearance remains scarce. In this paper, we propose a blending framework for general appearances that can be integrated into renderers without modifying the rendering pipeline. For natural interpolation calculations, we use the mathematical tool optimal transport (OT), known for its promising blending quality. Although recent advancements in OT theory have improved computational performance, integrating runtime OT calculations into the path tracing rendering pipeline compromises algorithm efficiency and increases storage requirements. To address this, we propose a novel solution that precomputes appearances into a proxy distribution and introduces a hierarchical query structure. This enables efficient online point or range data querying, allowing for the generation or retrieval of large data sets as needed. Additionally, the proxy and hierarchical query structure facilitate multi-way barycenter computation. With this efficient query structure and barycentric calculation, we demonstrate several applications of our method, including 2D and 3D interpolation, as well as isotropic BRDF interpolation.

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Computing Manifold Next-Event Estimation without Derivatives using the Nelder-Mead Method

(The Eurographics Association, 2024) Granizo-Hidalgo, Ana; Holzschuch, Nicolas; Haines, Eric; Garces, Elena

Specular surfaces, by focusing the light that is being reflected or refracted, cause bright spots in the scene, called caustics. These caustics are challenging to compute for global illumination algorithms. Manifold-based methods (Manifold Exploration, Manifold Next-Event Estimation, Specular Next Event Estimation) compute these caustics as the zeros of an objective function, using the Newton-Raphson method. They are efficient, but require computing the derivatives of the objective function, which in turn requires local surface derivatives around the reflection point, which can be challenging to implement. In this paper, we leverage the Nelder-Mead method to compute caustics using Manifold Next-Event Estimation without having to compute local derivatives. Our method only requires local evaluations of the objective function, making it an easy addition to any path-tracing algorithm.