Papers
2
Total Citations
9
H-Index
2
About
Guido Borghi is a researcher advancing the frontier of human-robot collaboration through innovative computer vision and pose estimation techniques. His primary research areas center on 3D pose estimation from depth data, with a specific focus on enabling safe and efficient interactions between humans and robots in shared workspaces. Borghi’s major contribution is the development of the Semi-Perspective Decoupled Heatmaps (SPDH) approach, a novel framework that accurately estimates 3D robot poses from single depth images. This method is notable for being non-invasive and light-invariant, making it highly practical for real-world industrial settings where lighting conditions vary. His work directly addresses critical applications such as detecting unsafe proximity between workers and machinery, and analyzing mutual interactions for ergonomic and social studies. With his most-cited paper accumulating 7 citations and a follow-up work, D-SPDH, tackling the challenging Sim2Real domain gap, Borghi is establishing a strong foundation for next-generation collaborative robotics. His research is essential reading for anyone interested in the intersection of 3D vision, human factors, and safe automation.
Research Focus
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Top Papers
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