Publications

Nicora, E., Goyal, G., Noceti, N., Vignolo, A., Sciutti, A., & Odone, F. (2020). The MoCA dataset, kinematic and multi-view visual streams of fine-grained cooking actions. Scientific Data, 7(1), 1-15.

Goyal, G., Noceti, N., & Odone, F. (2021). Single View Learning in Action Recognition. In 25th IEEE International Conference on Pattern Recognition (ICPR) (pp. 3690-3697).

Marsella, A., Goyal, G., & Odone, F. (2021). Adversarial feature refinement for cross-view action recognition. In Proceedings of the 36th Annual ACM Symposium on Applied Computing (pp. 1046-1054).

Vignolo, A., Noceti, N., Sciutti, A., Odone, F., & Sandini, G. (2021). Learning dictionaries of kinematic primitives for action classification. In 25th IEEE International Conference on Pattern Recognition (ICPR) (pp. 5965-5972).

Nair, V., Hemeren, P., Vignolo, A., Noceti, N., Nicora, E., Sciutti, A., ... & Sandini, G. (2020). Action similarity judgment based on kinematic primitives. In Joint IEEE 10th International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob) (pp. 1-8).

Nicora, E., Goyal, G., Noceti, N., & Odone, F. (2019). The effects of data sources: A baseline evaluation of the moca dataset. In International Conference on Image Analysis and Processing (pp. 544-555). Springer.

Rea, F., Vignolo, A., Sciutti, A., & Noceti, N. (2019). Human motion understanding for selecting action timing in collaborative human-robot interaction. Frontiers in Robotics and AI, 6, 58.

Malafronte, D., Goyal, G., Vignolo, A., Odone, F., & Noceti, N. (2017). Investigating the use of space-time primitives to understand human movements. In International Conference on Image Analysis and Processing (pp. 40-50). Springer.