4 papers
Paparazzo: Active Mapping of Moving 3D Objects
Davide Allegro, Shiyao Li, Stefano Ghidoni +1
Current 3D mapping pipelines generally assume static environments, which limits their ability to accurately capture and reconstruct moving objects. To address this limitation, we i…
MAGICIAN: Efficient Long-Term Planning with Imagined Gaussians for Active Mapping
Shiyao Li, Antoine Guédon, Shizhe Chen +1
Active mapping aims to determine how an agent should move to efficiently reconstruct unknown environments. Most existing approaches rely on greedy next-best-view prediction, result…
NextBestPath: Efficient 3D Mapping of Unseen Environments
Shiyao Li, Antoine Guédon, Clémentin Boittiaux +2
This work addresses the problem of active 3D mapping, where an agent must find an efficient trajectory to exhaustively reconstruct a new scene. Previous approaches mainly predict t…
GateAttentionPose: Enhancing Pose Estimation with Agent Attention and Improved Gated Convolutions
Liang Feng, Zhixuan Shen, Lihua Wen +2
This paper introduces GateAttentionPose, an innovative approach that enhances the UniRepLKNet architecture for pose estimation tasks. We present two key contributions: the Agent At…