Yufei Zhu
Befattning: Doktorand Organisation: Institutionen för naturvetenskap och teknikE-post: eXVmZWkuemh1O29ydS5zZQ==
Telefon: 019 303458
Rum: T1227
Forskningsprojekt
Pågående projekt
Forskargrupper
Publikationer
Artiklar i tidskrifter |
Konferensbidrag |
Artiklar i tidskrifter
- Schreiter, T. , Almeida, T. R. d. , Zhu, Y. , Gutiérrez Maestro, E. , Morillo-Mendez, L. , Rudenko, A. , Palmieri, L. , Kucner, T. P. & et al. (2024). THÖR-MAGNI: A large-scale indoor motion capture recording of human movement and robot interaction. The international journal of robotics research. [BibTeX]
- Almeida, T. R. d. , Zhu, Y. , Rudenko, A. , Kucner, T. P. , Stork, J. A. , Magnusson, M. & Lilienthal, A. J. (2024). Trajectory Prediction for Heterogeneous Agents: A Performance Analysis on Small and Imbalanced Datasets. IEEE Robotics and Automation Letters, 9 (7), 6576-6583. [BibTeX]
Konferensbidrag
- Zhu, Y. , Rudenko, A. , Kucner, T. , Palmieri, L. , Arras, K. , Lilienthal, A. & Magnusson, M. (2023). CLiFF-LHMP: Using Spatial Dynamics Patterns for Long-Term Human Motion Prediction. I: 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 01-05 October 2023, Detroit, MI, USA. Konferensbidrag vid 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2023), Detroit, MI, USA, October 1-5, 2023. (ss. 3795-3802). IEEE. [BibTeX]
- Almeida, T. , Rudenko, A. , Schreiter, T. , Zhu, Y. , Gutiérrez Maestro, E. , Morillo-Mendez, L. , Kucner, T. P. , Martinez Mozos, O. & et al. (2023). THÖR-Magni: Comparative Analysis of Deep Learning Models for Role-Conditioned Human Motion Prediction. I: 2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW). Konferensbidrag vid IEEE/CVF International Conference on Computer Vision (ICCV) Workshops, Paris, France, October 2-6, 2023. (ss. 2192-2201). IEEE. [BibTeX]
- Schreiter, T. , Almeida, T. R. d. , Zhu, Y. , Gutiérrez Maestro, E. , Morillo-Mendez, L. , Rudenko, A. , Kucner, T. P. , Martinez Mozos, O. & et al. (2022). The Magni Human Motion Dataset: Accurate, Complex, Multi-Modal, Natural, Semantically-Rich and Contextualized. Konferensbidrag vid 31st IEEE International Conference on Robot & Human Interactive Communication, Naples, Italy, August 29 - September 2, 2022. [BibTeX]