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Yiti Jiang

dblp:346/8992 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2023
0000-0002-9208-9895ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Rendering · 100%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Computational science and engineering · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Rendering
global illumination
0.712023
A Practical Walk-on-Boundary Method for Boundary Value Problems · ACM Trans. Graph. 2023
Rendering
light transport
0.712023
A Practical Walk-on-Boundary Method for Boundary Value Problems · ACM Trans. Graph. 2023
Rendering
monte carlo integration
0.712023
A Practical Walk-on-Boundary Method for Boundary Value Problems · ACM Trans. Graph. 2023
Computational science and engineering › partial differential equations
boundary value problems
0.212023
A Practical Walk-on-Boundary Method for Boundary Value Problems · ACM Trans. Graph. 2023

Methods — techniques the papers use, named apart from their topics

virtual point lights · 1.3multiple importance sampling · 1.3markov chain monte carlo · 1.3boundary integral formulation · 1.3bidirectional estimators · 0.7bidirectional estimator · 0.7
YearPublicationVenuePosition
2023 A Practical Walk-on-Boundary Method for Boundary Value Problems
abstract
We introduce the walk-on-boundary (WoB) method for solving boundary value problems to computer graphics. WoB is a grid-free Monte Carlo solver for certain classes of second order partial differential equations. A similar Monte Carlo solver, the walk-on-spheres (WoS) method, has been recently popularized in computer graphics due to its advantages over traditional spatial discretization-based alternatives. We show that WoB's intrinsic properties yield further advantages beyond those of WoS. Unlike WoS, WoB naturally supports various boundary conditions (Dirichlet, Neumann, Robin, and mixed) for both interior and exterior domains. WoB builds upon boundary integral formulations, and it is mathematically more similar to light transport simulation in rendering than the random walk formulation of WoS. This similarity between WoB and rendering allows us to implement WoB on top of Monte Carlo ray tracing, and to incorporate advanced rendering techniques (e.g., bidirectional estimators with multiple importance sampling, the virtual point lights method, and Markov chain Monte Carlo) into WoB. WoB does not suffer from the intrinsic bias of WoS near the boundary and can estimate solutions precisely on the boundary. Our numerical results highlight the advantages of WoB over WoS as an attractive alternative to solve boundary value problems based on Monte Carlo.
Ryusuke Sugimoto, Terry Chen, Yiti Jiang, Christopher Batty, Toshiya Hachisuka
ACM Trans. Graph.3