Our paper presenting a novel multi-scale approach for learning deep representations from RGB-D data has been accepted for publications on Robotics and Automation Letters:
L.Porzi, S.Rota, A.Peñate-Sánchez, E.Ricci, F.Moreno-Noguer, Learning Depth-aware Deep Representations for Robotic Perception, To appear in Robotics and Automation Letters (RA-L), 2017
Our paper presenting the SALSA dataset for analyzing free standing conversational groups from a camera network and sociometric badges has been published on PAMI:
X. Alameda-Pineda, J. Staiano, R. Subramanian, L. M. Batrinca, E. Ricci, B. Lepri, O. Lanz, N. Sebe. “SALSA: A Novel Dataset for Multimodal Group Behavior Analysis”. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2016.
I have two papers accepted at ACM MM 2016. Congrats to Dan and Lorenzo!
- D. Xu, X. Alameda-Pineda, J. Song, E. Ricci, and N. Sebe, “Academic Coupled Dictionary Learning for Sketch-based Image Retrieval,” in ACM International Conference on Multimedia, Amsterdam, The Netherlands, 2016.
- L.Porzi, S. Rota-Bulò, E.Ricci, “A Deeply-Supervised Deconvolutional Network for Horizon Line Detection”, in ACM International Conference on Multimedia, Amsterdam, The Netherlands, 2016.
I will be giving a tutorial at ACM Multimedia’2016: Emerging topics in learning from noisy and missing data. The tutorial will be given on October the 16th in collaboration with Dr. Xavier Alameda-Pineda, Dr. Timothy Hospedales, Prof. Xiaogang Wang and Prof. Nicu Sebe.