Demo Data from SIGIR 2026 / reviewers in the wild / expert
Jiang Yu Zhen
dblp:182/4663
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 1991
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 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 |
Motion planning and robot control · 67% Robot manipulation · 33% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Motion planning and robot control › robot control › sensor-based control
active camera control |
0.0 | 1 | 1991 | Active camera controlling for manipulation · CVPR 1991 |
Robotics › Robot manipulation › robot vision
vision-based manipulation |
0.0 | 1 | 1991 | Active camera controlling for manipulation · CVPR 1991 |
Robotics › Motion planning and robot control › robot control › sensor-based control
visual servoing |
0.0 | 1 | 1991 | Active camera controlling for manipulation · CVPR 1991 |
Methods — techniques the papers use, named apart from their topics
task-driven image processing · 0.0active vision · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1991 | Active camera controlling for manipulationabstractA method for object manipulation using an active camera is introduced. By actively moving the camera to proper positions with desired viewing angle from objects of interest, it is possible to acquire data to realize the robust visual feedback control of a robot. This approach avoids complicated 3-D modeling, and the image processing carried out is driven by tasks. Active camera control for robot guidance and image understanding is addressed.> Jiang Yu Zhen, Fumio Kishino, Qian Chen 0001, Saburo Tsuji |
CVPR | 1 |