Demo Data from SIGIR 2026 / reviewers in the wild / expert
André Lejeune
dblp:86/638
· DBLP profile ↗
2ranked-venue papers
2as first author
0since 2021 · last 1996
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2 · 2 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author
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 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computer vision › 3D vision
3d scene understanding |
0.0 | 1 | 1993 | Partitioning range images using curvature and scale · CVPR 1993 |
Computer vision › 3D vision › range sensing
range image segmentation |
0.0 | 1 | 1993 | Partitioning range images using curvature and scale · CVPR 1993 |
Geometric modeling and processing › shape decomposition
surface decomposition |
0.0 | 1 | 1993 | Partitioning range images using curvature and scale · CVPR 1993 |
Computer vision › 3D vision › 3d reconstruction
surface reconstruction |
0.0 | 1 | 1993 | Partitioning range images using curvature and scale · CVPR 1993 |
Methods — techniques the papers use, named apart from their topics
scale-space representation · 0.0curvature analysis · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1996 | Finding the Parts of Objects in Range Images
André Lejeune, Frank P. Ferrie |
Comput. Vis. Image Underst. | 1 |
| 1993 | Partitioning range images using curvature and scaleabstractA method is presented for partitioning a set of surface estimates obtained with a laser range finding system into subsets corresponding to parts of an object. The authors' strategy uses two complementary representations for surfaces, i.e., one which describes local structures in terms of differential properties (e.g., edges, lines, contours) and another which represents the surface as a collection of smooth patches at different scales. By enforcing a consistent interpretation between these two representations, it is possible to derive a partitioning algorithm that is both efficient and robust.> André Lejeune, Frank P. Ferrie |
CVPR | 1 |