Demo Data from EDBT 2026 / reviewers in the wild / expert
Shiyuan Gu
dblp:04/7642
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2013
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1
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 |
Geometric modeling and processing · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Geometric modeling and processing › parameterization
volumetric mapping |
0.2 | 1 | 2013 | Biharmonic Volumetric Mapping Using Fundamental Solutions · IEEE Trans. Vis. Comput. Graph. 2013 |
Geometric modeling and processing
shape decomposition |
0.0 | 1 | 2013 | Biharmonic Volumetric Mapping Using Fundamental Solutions · IEEE Trans. Vis. Comput. Graph. 2013 |
Methods — techniques the papers use, named apart from their topics
fundamental solutions · 0.2biharmonic model · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2013 | Biharmonic Volumetric Mapping Using Fundamental SolutionsabstractWe propose a biharmonic model for cross-object volumetric mapping. This new computational model aims to facilitate the mapping of solid models with complicated geometry or heterogeneous inner structures. In order to solve cross-shape mapping between such models through divide and conquer, solid models can be decomposed into subparts upon which mappings is computed individually. The biharmonic volumetric mapping can be performed in each subregion separately. Unlike the widely used harmonic mapping which only allows C0 continuity along the segmentation boundary interfaces, this biharmonic model can provide C1 smoothness. We demonstrate the efficacy of our mapping framework on various geometric models with complex geometry (which are decomposed into subparts with simpler and solvable geometry) or heterogeneous interior structures (whose different material layers can be segmented and processed separately). Huanhuan Xu, Wuyi Yu, Shiyuan Gu, Xin Li 0003 |
IEEE Trans. Vis. Comput. Graph. | 3 |