Fabio Poiesi
Papers
5
Total Citations
193
H-Index
3
About
Fabio Poiesi is a leading researcher at the intersection of computer vision, robotics, and human-computer interaction (HCI). His work primarily focuses on enabling intelligent systems to perceive, understand, and interact with dynamic environments. A key contribution is his comprehensive 2022 survey on deep learning for intelligent HCI (150 citations), which explores how gesture and speech recognition are revolutionizing virtual reality interfaces. Poiesi has also made significant strides in autonomous robotics, developing a distributed vision-based consensus model for aerial-robot teams to collaboratively track targets without external control. His recent work addresses critical challenges in visual SLAM through multimodal fusion with Fourier attention, improving performance in noisy and dark environments. Poiesi’s impact extends to applied domains, with surveys on video anomaly detection in dynamic scenes with moving cameras and machine vision for food industry automation, both published in 2023-2024. His research consistently bridges theoretical advances with practical deployment, making him a notable figure in the advancement of intelligent, vision-driven robotic systems for real-world applications.
Research Focus
Key Achievements
Top Papers
- 1Deep Learning for Intelligent Human–Computer Interaction150 citations · 2022
- 2Survey on video anomaly detection in dynamic scenes with moving cameras19 citations · 2023
- 3
- 4A distributed vision-based consensus model for aerial-robotic teams3 citations · 2018
- 5Multimodal Fusion SLAM With Fourier Attention2 citations · 2024