Demo Data from EDBT 2026 / reviewers in the wild / expert
Shuangbing Song
dblp:276/7465
· DBLP profile ↗
2ranked-venue papers
2as first author
1since 2021 · last 2023
0000-0002-1031-6151ORCID · corroborated
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 · 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 |
Visual content generation and editing · 67% Image and video processing · 33% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Visual content generation and editing
image editing |
0.7 | 1 | 2023 | Guided Linear Upsampling · ACM Trans. Graph. 2023 |
Image and video processing › image resampling › image rescaling
image upsampling |
0.7 | 1 | 2023 | Guided Linear Upsampling · ACM Trans. Graph. 2023 |
Visual content generation and editing › image editing
interactive image editing |
0.7 | 1 | 2023 | Guided Linear Upsampling · ACM Trans. Graph. 2023 |
Methods — techniques the papers use, named apart from their topics
linear interpolation · 0.7joint optimization · 0.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Guided Linear UpsamplingabstractGuided upsampling is an effective approach for accelerating high-resolution image processing. In this paper, we propose a simple yet effective guided upsampling method. Each pixel in the high-resolution image is represented as a linear interpolation of two low-resolution pixels, whose indices and weights are optimized to minimize the upsampling error. The downsampling can be jointly optimized in order to prevent missing small isolated regions. Our method can be derived from the color line model and local color transformations. Compared to previous methods, our method can better preserve detail effects while suppressing artifacts such as bleeding and blurring. It is efficient, easy to implement, and free of sensitive parameters. We evaluate the proposed method with a wide range of image operators, and show its advantages through quantitative and qualitative analysis. We demonstrate the advantages of our method for both interactive image editing and real-time high-resolution video processing. In particular, for interactive editing, the joint optimization can be precomputed, thus allowing for instant feedback without hardware acceleration. Shuangbing Song, Fan Zhong 0001, Tianju Wang, Xueying Qin, Changhe Tu |
ACM Trans. Graph. | 1 |
| 2020 | Illumination Harmonization with Gray Mean Scale
Shuangbing Song, Fan Zhong 0001, Xueying Qin, Changhe Tu |
CGI | 1 |