Papers

3

Total Citations

15

H-Index

3

About

Pedro Victor Vieira de Paiva is a robotics researcher dedicated to advancing human-robot interaction in unstructured, dynamic environments. His work centers on social perception, focusing on how robots can interpret human behavior using only lightweight, in-the-wild sensor data. In his highly cited 2020 paper, "Estimating Human Body Orientation using Skeletons and Extreme Gradient Boosting" (7 citations), he pioneered a method to infer body orientation from single-camera skeleton data—a critical cue for social path planning and approaching—without relying on expensive multi-sensory setups. That same year, he introduced ROSANA (5 citations), a mobile robot platform designed for social interaction, tackling the challenge of balancing high-level perception with limited onboard computational power. Most recently, in 2025, Paiva unveiled SkelETT—Skeleton-to-Emotion Transfer Transformer (3 citations), a novel architecture that recognizes human emotion purely from skeletal motion, bypassing traditional reliance on facial expressions or audio. By combining efficient machine learning with real-world deployability, Paiva’s contributions are shaping how socially interactive robots perceive and respond to people, making autonomous social navigation and affective computing more accessible and robust.

Research Focus

Key Achievements

3
H-Index
3
Papers
15
Total Citations
5
Avg Citations/Paper
🏆 Most Cited Paper
Estimating Human Body Orientation using Skeletons and Extreme Gradient Boosting
7 citations · 2020
📈 Most Prolific Year: 2020 (2 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: Centro de Tecnologia da Informação Renato Archer, Universidade Estadual de Campinas (UNICAMP)

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 17 days ago