Article
Computer Science, Software Engineering
Zander Majercik, Thomas Muller, Alexander Keller, Derek Nowrouzezahrai, Morgan McGuire
Summary: This study enhances sample efficiency for transport contributions terminating on diffuse scattering events by combining screen-space reservoir resampling and sparse world-space probes, resulting in clear improvements over purely path tracing and probe-based baselines in rendering global illumination interactively in complex scenes.
COMPUTER GRAPHICS FORUM
(2022)
Article
Computer Science, Software Engineering
Cheng Zhang, Zihan Yu, Shuang Zhao
Summary: This paper introduces a physics-based differentiable rendering technique that utilizes differential path integrals for estimating arbitrary scene parameters. The method efficiently handles challenging geometric discontinuities and light transport phenomena, such as volumetric caustics.
ACM TRANSACTIONS ON GRAPHICS
(2021)
Article
Computer Science, Software Engineering
Shinyoung Yi, Donggun Kim, Kiseok Choi, Adrian Jarabo, Diego Gutierrez, Min H. Kim
Summary: Recent differentiable rendering techniques have become important tools for solving inverse problems in graphics and vision. However, existing models assume infinite speed of light, which may not be suitable for ultrafast imaging applications. This paper introduces a novel differentiable transient rendering framework that takes into account the finite speed of light, and successfully applies it in challenging scenarios such as optimizing indices of refraction and non-line-of-sight tracking.
ACM TRANSACTIONS ON GRAPHICS
(2021)
Article
Thermodynamics
Peter Stewart Cumber
Summary: This paper explores the application of various variants of the Monte-Carlo method and quasi-Monte-Carlo method in evaluating three view factor configurations. The study finds that for two configurations, the numerical integration-based methods are more accurate than the ray tracing-based methods. However, for the configuration with a common edge, ray tracing performs better than numerical integration. A hybrid method that combines ray tracing and numerical integration is proposed for this configuration. The hybrid quasi-Monte-Carlo method is demonstrated to be the most efficient approach for evaluating the view factor integral.
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
(2022)
Article
Computer Science, Software Engineering
Arnau Colom, Ricardo Marques, Luis Paulo Santos
Summary: This study proposes a VPL-based ray tracing approach that achieves interactive rendering by clustering and computing visibility on the GPU.
COMPUTERS & GRAPHICS-UK
(2022)
Article
Computer Science, Software Engineering
Hanggao Xin, Shaokun Zheng, Kun Xu, Ling-Qi Yan
Summary: This paper presents a novel method to generate single-bounce indirect illumination for dynamic scenes at interactive framerates. The method uses a lightweight neural network to predict screen-space indirect illumination, and achieves high quality and good temporal coherence through bilateral convolution layers and simplified input information.
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
(2022)
Article
Computer Science, Software Engineering
Yuankang Chen, Yifan Lu, Xiaohua Zhang, Nine Xie
Summary: In this paper, a lightweight cascaded network is proposed to denoise 1-spp Monte Carlo images through pixel and kernel prediction methods. Experimental results show that the approach achieves state-of-the-art denoising qualities for 1-spp images at an interactive frame speed.
Article
Computer Science, Software Engineering
Jaroslav Kravec, Martin Kacerik, Jiri Bittner
Summary: Novel view synthesis is improved by using a new representation called potentially visible layered image (PVLI) that encodes the depth implicitly and allows for cheap run-time reconstruction. PVLI also enables reconstruction of pixel and layer connectivities, which is important for filtering and post-processing of rendered images. The method supports real-time ray tracing for temporal and spatial upsampling of ray-traced illumination, as well as network streaming and thin client utilization for latency hiding and upsampling.
Article
Computer Science, Interdisciplinary Applications
Cheng Shao, Takuma Hori, Junichiro Shiomi
Summary: P-TRANS is a software that simulates phonon transport in arbitrary nanostructures using the Monte Carlo ray-tracing method. It achieves high performance by utilizing parallelization and can handle calculations on normal PCs within seconds. The software is useful for exploring various nanostructures and is applicable in structural optimization and high-throughput screening.
COMPUTER PHYSICS COMMUNICATIONS
(2022)
Article
Computer Science, Software Engineering
Jozef Kobrtek, Tomas Milet, Michal Toth, Adam Herout
Summary: This paper compares state-of-the-art precise shadowing techniques for an omnidirectional point light, with ray tracing being the fastest method and stencil shadow volumes faster than some newer methods. Omnidirectional frustum-traced shadows are the second fastest algorithm tested.
COMPUTER GRAPHICS FORUM
(2022)
Article
Computer Science, Information Systems
Wonjun Lee, Piljoong Jeong, Hajin Choi, Jinwoo Kim, Bochang Moon
Summary: The research proposes a technique for estimating scene illumination through online learning to achieve visual consistency between virtual and real objects, capable of providing high-quality global illumination results in augmented reality.
Article
Materials Science, Multidisciplinary
Bruno R. de Abreu, Fabio Cinti, Tommaso Macri
Summary: This paper investigates the search for spontaneous pattern formation in equilibrium phases with genuine quantum properties. The effect of quantum fluctuations and exchange interactions on the phases of an ensemble of bosonic particles is studied. Extensive simulations reveal a rich phase diagram with supersolid stripes, kagome, and triangular crystals in the low-density regime, as well as patterns with 12-fold rotational symmetry in the high-density limit. The quantum phases are characterized by computing the superfluid density and the bond-orientational order parameter. Differences between the findings of this study and classical equilibrium phases for the same parameter regimes are highlighted.
Article
Computer Science, Software Engineering
Jie Guo, Zijing Zong, Yadong Song, Xihao Fu, Chengzhi Tao, Yanwen Guo, Ling-Qi Yan
Summary: This paper proposes a new method for probe-based global illumination (GI) rendering that can generate a wide range of GI effects, including glossy reflection with multiple bounces, in complex scenes. The method utilizes a gradient-based search algorithm and a neural image reconstruction method to achieve fast and high-quality GI rendering, while employing temporal reprojection and a temporal loss to improve temporal stability for animation sequences.
ACM TRANSACTIONS ON GRAPHICS
(2022)
Review
Computer Science, Software Engineering
Yuchi Huo, Sung-eui Yoon
Summary: Monte Carlo integration is commonly used in realistic image synthesis, but balancing bias and variance may result in noise. Recent focus has been on denoising MC rendering with deep learning, showing promising results in real-world applications.
COMPUTATIONAL VISUAL MEDIA
(2021)
Article
Computer Science, Software Engineering
Xi Deng, Milos Hasan, Nathan Carr, Zexiang Xu, Steve Marschner
Summary: The proposed method iteratively refines radiance estimates by processing a fixed collection of paths in a path graph, improving image quality. The operations of aggregation and propagation gradually refine radiance values. The method can be easily integrated into any standard path tracer and neural final image denoiser, leading to realistic rendering results.
ACM TRANSACTIONS ON GRAPHICS
(2021)
Article
Computer Science, Software Engineering
Jan Novak, Iliyan Georgiev, Johannes Hanika, Wojciech Jarosz
COMPUTER GRAPHICS FORUM
(2018)
Article
Computer Science, Software Engineering
Carlos Urena, Iliyan Georgiev
COMPUTER GRAPHICS FORUM
(2018)
Article
Computer Science, Software Engineering
Bailey Miller, Iliyan Georgiev, Wojciech Jarosz
ACM TRANSACTIONS ON GRAPHICS
(2019)
Article
Computer Science, Software Engineering
Pascal Grittmann, Iliyan Georgiev, Philipp Slusallek, Jaroslav Krivanek
ACM TRANSACTIONS ON GRAPHICS
(2019)
Article
Computer Science, Software Engineering
Iliyan Georgiev, Zackary Misso, Toshiya Hachisuka, Derek Nowrouzezahrai, Jaroslav Krivanek, Wojciech Jarosz
ACM TRANSACTIONS ON GRAPHICS
(2019)
Article
Computer Science, Software Engineering
Rex West, Iliyan Georgiev, Adrien Gruson, Toshiya Hachisuka
ACM TRANSACTIONS ON GRAPHICS
(2020)
Article
Computer Science, Software Engineering
Tizian Zeltner, Iliyan Georgiev, Wenzel Jakob
ACM TRANSACTIONS ON GRAPHICS
(2020)
Article
Computer Science, Software Engineering
Tizian Zeltner, Sebastien Speierer, Iliyan Georgiev, Wenzel Jakob
Summary: Physically based differentiable rendering algorithms have advanced in computing derivatives with respect to millions of parameters, but their fundamental properties are still poorly understood and further research is needed. Current algorithms mechanically differentiate a given primal algorithm, limiting potential improvements.
ACM TRANSACTIONS ON GRAPHICS
(2021)
Article
Computer Science, Software Engineering
Pascal Grittmann, Oemercan Yazici, Iliyan Georgiev, Philipp Slusallek
Summary: Multiple importance sampling (MIS) is a crucial tool in light-transport simulation, allowing robust Monte Carlo integration through the combination of samples from different techniques. However, the efficiency of complex combined estimators is not always superior to simpler algorithms, leading to the proposal of a general method to improve MIS efficiency.
ACM TRANSACTIONS ON GRAPHICS
(2022)
Article
Computer Science, Software Engineering
Vassillen Chizhov, Iliyan Georgiev, Karol Myszkowski, Gurprit Singh
Summary: This paper proposes a perception-oriented framework to optimize rendering errors by distributing the error as visually pleasing blue noise in image space. It leverages models based on human perception to improve image fidelity and shows substantial improvements over prior state of the art.
ACM TRANSACTIONS ON GRAPHICS
(2022)
Article
Computer Science, Software Engineering
Zackary Misso, Benedikt Bitterli, Iliyan Georgiev, Wojciech Jarosz
Summary: We introduce a general framework for transforming biased estimators into unbiased and consistent estimators in the same field. We demonstrate how this framework can be applied to rendering and improve existing unbiased estimation strategies. We provide examples of novel unbiased forms of transmittance estimation, photon mapping, and finite differences that are developed using this framework.
ACM TRANSACTIONS ON GRAPHICS
(2022)
Article
Computer Science, Software Engineering
Ege Ciklabakkal, Adrien Gruson, Iliyan Georgiev, Derek Nowrouzezahrai, Toshiya Hachisuka
Summary: Resampling is the process of selecting samples from a set of candidates to achieve a distribution that is approximately proportional to a desired target. Recent research has explored its application to Monte Carlo integration, resulting in powerful and practical importance sampling methods. Existing resampling methods have the limitation of not being able to generate stratified samples. We propose two complementary techniques to efficiently achieve stratified resampling.
COMPUTER GRAPHICS FORUM
(2022)
Article
Computer Science, Software Engineering
Corentin Salauen, Iliyan Georgiev, Hans-Peter Seidel, Gurprit Singh
Summary: This paper proposes a multi-class point optimization formulation based on continuous Wasserstein barycenters, which is designed to handle a large number of optimization objectives and comes with a practical optimization scheme. The effectiveness of the framework is demonstrated on various sampling applications such as stippling, object placement, and Monte-Carlo integration. A multi-class error bound for perceptual rendering error is derived, which can be minimized using the proposed optimization. Source code is provided at the given link.
ACM TRANSACTIONS ON GRAPHICS
(2022)
Article
Computer Science, Software Engineering
Pascal Grittmann, Iliyan Georgiev, Philipp Slusallek
Summary: Combining diverse sampling techniques through multiple importance sampling is crucial for robustness in modern Monte Carlo light transport simulation. The proposal of a correlation-aware heuristic, based on known path densities required for MIS, can achieve significantly lower error compared to the balance heuristic, without incurring additional computational and memory overhead.
COMPUTER GRAPHICS FORUM
(2021)
Proceedings Paper
Computer Science, Theory & Methods
Shinji Ogaki, Iliyan Georgiev
SA'18: SIGGRAPH ASIA 2018 TECHNICAL BRIEFS
(2018)