José Arce — accepted AI-conference papers

2024

Syn-Mediverse: A Multimodal Synthetic Dataset for Intelligent Scene Understanding of Healthcare Facilities

Rohit Mohan, José Arce, Sassan Mokhtar, Daniele Cattaneo, Abhinav Valada

RA-L 2024

Safety and efficiency are paramount in healthcare facilities where the lives of patients are at stake. Despite the adoption of robots to assist medical staff in challenging tasks such as complex surgeries, human expertise is still indispensable. The next generation of autonomous healthcare robots hi

Cited by 9 Source ↗Scholar ↗

2023

PADLoC: LiDAR-Based Deep Loop Closure Detection and Registration Using Panoptic Attention

José Arce, Niclas Vödisch, Daniele Cattaneo, Wolfram Burgard, Abhinav Valada

RA-L 2023

A key component of graph-based SLAM systems is the ability to detect loop closures in a trajectory to reduce the drift accumulated over time from the odometry. Most LiDAR-based methods achieve this goal by using only the geometric information, disregarding the semantics of the scene. In this work, w

Cited by 40 Source ↗code ↗Scholar ↗