Demo Data from EDBT 2026 / reviewers in the wild / expert
Song Zhang 0007
dblp:77/3067-7
· DBLP profile ↗
2ranked-venue papers
2as first author
2since 2021 · last 2025
0000-0002-6252-3291ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 2 · 2 first-author · 2 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 · 80% Computational photography and imaging · 20% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Rendering
antialiasing |
0.8 | 1 | 2024 | Area ReSTIR: Resampling for Real-Time Defocus and Antialiasing · ACM Trans. Graph. 2024 |
Rendering › lens and aperture model
defocus rendering |
0.8 | 1 | 2024 | Area ReSTIR: Resampling for Real-Time Defocus and Antialiasing · ACM Trans. Graph. 2024 |
Computational photography and imaging
depth of field |
0.8 | 1 | 2024 | Area ReSTIR: Resampling for Real-Time Defocus and Antialiasing · ACM Trans. Graph. 2024 |
Rendering
global illumination |
0.8 | 1 | 2024 | Area ReSTIR: Resampling for Real-Time Defocus and Antialiasing · ACM Trans. Graph. 2024 |
Rendering › sampling
subpixel sampling |
0.8 | 1 | 2024 | Area ReSTIR: Resampling for Real-Time Defocus and Antialiasing · ACM Trans. Graph. 2024 |
Methods — techniques the papers use, named apart from their topics
reservoir resampling · 0.8importance sampling · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Many-Light Rendering Using ReSTIR-Sampled Shadow MapsabstractAbstract We present a practical method targeting dynamic shadow maps for many light sources in real‐time rendering. We compute full‐resolution shadow maps for a subset of lights, which we select with spatiotemporal reservoir resampling (ReSTIR). Our selection strategy automatically regenerates shadow maps for lights with the strongest contributions to pixels in the current camera view. The remaining lights are handled using imperfect shadow maps, which provide low‐resolution shadow approximation. We significantly reduce the computation and storage compared to using all full‐resolution shadow maps and substantially improve shadow quality compared to handling all lights with imperfect shadow maps. Song Zhang 0007, Daqi Lin, Chris Wyman, Cem Yuksel |
Comput. Graph. Forum | 1 |
| 2024 | Area ReSTIR: Resampling for Real-Time Defocus and AntialiasingabstractRecent advancements in spatiotemporal reservoir resampling (ReSTIR) leverage sample reuse from neighbors to efficiently evaluate the path integral. Like rasterization, ReSTIR methods implicitly assume a pinhole camera and evaluate the light arriving at a pixel through a single predetermined subpixel location at a time (e.g., the pixel center). This prevents efficient path reuse in and near pixels with high-frequency details. We introduce Area ReSTIR , extending ReSTIR reservoirs to also integrate each pixel's 4D ray space, including 2D areas on the film and lens. We design novel subpixel-tracking temporal reuse and shift mappings that maximize resampling quality in such regions. This robustifies ReSTIR against high-frequency content, letting us importance sample subpixel and lens coordinates and efficiently render antialiasing and depth of field. Song Zhang 0007, Daqi Lin, Markus Kettunen 0001, Cem Yuksel, Chris Wyman |
ACM Trans. Graph. | 1 |