Mirco Planamente

Politecnico di Torino, Italian Institute of Technology

Papers

Total Citations

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About

Mirco Planamente is a computer vision and robotics researcher whose work sits at the intersection of human-robot cooperation, egocentric action recognition, and multimodal object recognition. His research addresses one of the most pressing challenges in modern robotics: enabling machines to understand and anticipate human behavior in real-world, uncontrolled environments. Planamente has made notable contributions to egocentric vision, developing deep learning frameworks that allow robots to interpret first-person human activities — a capability essential for safe and effective human-robot collaboration. His work on unsupervised domain adaptation tackles the practical challenge of deploying action recognition models "in the wild," bridging the gap between controlled training conditions and unpredictable real-world settings. Earlier in his career, Planamente explored RGB-D object recognition, leveraging the rich spatial information provided by depth cameras through recurrent convolutional fusion architectures to enhance robotic perception. Though still building his citation profile — with his most recognized works accumulating citations in the range of three to five — his research agenda is timely and forward-looking, addressing fundamental problems that will shape the next generation of intelligent, human-aware robotic systems.