Demo Data from VLDB 2026 / reviewers in the wild / expert
Guilherme G. Haetinger
dblp:279/9585 · also Guilherme Gomes Haetinger
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2025
0009-0008-7293-292XORCID · 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 |
Visual content generation and editing · 100% |
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 › style transfer › 3d content stylization
3d scene stylization |
0.9 | 1 | 2025 | Shaping Strands with Neural Style Transfer · ACM Trans. Graph. 2025 |
Visual content generation and editing › style transfer
neural style transfer |
0.9 | 1 | 2025 | Shaping Strands with Neural Style Transfer · ACM Trans. Graph. 2025 |
Visual content generation and editing
style transfer |
0.9 | 1 | 2025 | Shaping Strands with Neural Style Transfer · ACM Trans. Graph. 2025 |
Methods — techniques the papers use, named apart from their topics
neural style transfer · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Shaping Strands with Neural Style TransferabstractThe intricate geometric complexity of knots, tangles, dreads and clumps require sophisticated grooming systems that allow artists to both realistically model and artistically control fur and hair systems. Recent volumetric and 3D neural style transfer techniques provided a new paradigm of art directability, allowing artists to modify assets drastically with the use of single style images. However, these previous 3D neural stylization approaches were limited to volumes and meshes. In this paper we propose the first stylization pipeline to support hair and fur. Through a carefully tailored fur/hair representation, our approach allows complex, 3D consistent and temporally coherent grooms that are stylized using style images. Beyzanur Coban, Pascal Chang, Guilherme G. Haetinger, Jingwei Tang, Vinicius C. Azevedo |
ACM Trans. Graph. | 3 |