Demo Data from VLDB 2026 / reviewers in the wild / expert
F. Helt
dblp:64/1489
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1997
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Graphics, 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 |
Image and video processing · 100% | |
| Artificial intelligence
1 paper |
3D vision · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Image and video processing › image restoration
film restoration |
0.0 | 1 | 1997 | Deterioration detection for digital film restoration · CVPR 1997 |
Computer vision › 3D vision
motion estimation |
0.0 | 1 | 1997 | Deterioration detection for digital film restoration · CVPR 1997 |
Methods — techniques the papers use, named apart from their topics
spatio-temporal analysis · 0.0morphological detector · 0.0dynamic detector · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1997 | Deterioration detection for digital film restorationabstractThis paper presents a robust technique to detect local deteriorations of old cinematographic films. This method relies on spatio-temporal information and combines two different detectors: a morphological detector which uses spatial properties of deteriorations, and a dynamic detector based on motion estimation techniques. Our deterioration detector has been validated on several film sequences and turned out to be a powerful tool for digital film restoration. Olivier Buisson, Bernard Besserer, Samia Boukir, F. Helt |
CVPR | 4 |