Demo Data from EDBT 2026 / reviewers in the wild / expert
Daniel Grittner
dblp:317/0416
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2022
0000-0001-6645-541XORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 since 2021Graphics, 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.
| Artificial intelligence
1 paper |
3D vision · 100% | |
| 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 |
|---|---|---|---|---|
Computer vision › 3D vision › 3d scene modeling › scene representation
neural scene representation |
0.6 | 1 | 2022 | Intrinsic Neural Fields: Learning Functions on Manifolds · ECCV (2) 2022 |
Geometric modeling and processing
manifold learning |
0.2 | 1 | 2022 | Intrinsic Neural Fields: Learning Functions on Manifolds · ECCV (2) 2022 |
Methods — techniques the papers use, named apart from their topics
neural field · 1.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Intrinsic Neural Fields: Learning Functions on Manifolds
Lukas Koestler, Daniel Grittner, Michael Möller 0001, Daniel Cremers, Zorah Lähner |
ECCV (2) | 2 |