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EDBT 2026 Demo / reviewers in the wild / expert

Qian Wang 0053

dblp:75/5723-53 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2023
0000-0001-6471-6284ORCID · conflict

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 · 75% Robot manipulation · 25%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computer vision › 3D vision › object pose estimation
6DOF pose tracking		 0.712023
FC-TrackNet: Fast Convergence Net for 6D Pose Tracking in Synthetic Domains · AAAI 2023
Robotics › Robot manipulation
grasping		 0.712023
FC-TrackNet: Fast Convergence Net for 6D Pose Tracking in Synthetic Domains · AAAI 2023
Computer vision › 3D vision
object pose estimation		 0.712023
FC-TrackNet: Fast Convergence Net for 6D Pose Tracking in Synthetic Domains · AAAI 2023
Computer vision › 3D vision › pose estimation
pose tracking		 0.712023
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
YearPublicationVenuePosition
2023 FC-TrackNet: Fast Convergence Net for 6D Pose Tracking in Synthetic Domains
abstract
In 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
 AAAI2