Demo Data from EDBT 2026 / reviewers in the wild / expert
Zhiyang Jin
dblp:261/6783
· DBLP profile ↗
2ranked-venue papers
1as first author
1since 2021 · last 2023
—ORCID · conflict
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 2 · 1 first-author · 1 since 2021Artificial intelligence and machine learning · 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 · 75% Robot manipulation · 25% |
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 › object pose estimation
6DOF pose tracking |
0.7 | 1 | 2023 | FC-TrackNet: Fast Convergence Net for 6D Pose Tracking in Synthetic Domains · AAAI 2023 |
Robotics › Robot manipulation
grasping |
0.7 | 1 | 2023 | FC-TrackNet: Fast Convergence Net for 6D Pose Tracking in Synthetic Domains · AAAI 2023 |
Computer vision › 3D vision
object pose estimation |
0.7 | 1 | 2023 | FC-TrackNet: Fast Convergence Net for 6D Pose Tracking in Synthetic Domains · AAAI 2023 |
Computer vision › 3D vision › pose estimation
pose tracking |
0.7 | 1 | 2023 | FC-TrackNet: Fast Convergence Net for 6D Pose Tracking in Synthetic Domains · AAAI 2023 |
Methods — techniques the papers use, named apart from their topics
synthetic data · 0.7deep learning · 0.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | FC-TrackNet: Fast Convergence Net for 6D Pose Tracking in Synthetic DomainsabstractIn this work, we propose a fast convergence track net, or FC-TrackNet, based on a synthetic data-driven approach to maintaining long-term 6D pose tracking. Comparison experiments are performed on two different datasets, The results demonstrate that our approach can achieve a consistent tracking frequency of 90.9 Hz as well as higher accuracy than the state-of-the art approaches. Di Jia, Qian Wang 0053, Peng Cai 0005, Zhiyang Jin |
AAAI | 5 |
| 2020 | Feature extraction optimization of JPEG steganalysis based on residual images
Zhiyang Jin, Guorui Feng, Yanli Ren, Xinpeng Zhang 0001 |
Signal Process. | 1 |