1 code implementation • ICCV 2023 • Giacomo Zara, Alessandro Conti, Subhankar Roy, Stéphane Lathuilière, Paolo Rota, Elisa Ricci
Source-Free Video Unsupervised Domain Adaptation (SFVUDA) task consists in adapting an action recognition model, trained on a labelled source dataset, to an unlabelled target dataset, without accessing the actual source data.
1 code implementation • 9 May 2023 • Gk Tejus, Giacomo Zara, Paolo Rota, Andrea Fusiello, Elisa Ricci, Federica Arrigoni
In this paper we address the rotation synchronization problem, where the objective is to recover absolute rotations starting from pairwise ones, where the unknowns and the measures are represented as nodes and edges of a graph, respectively.
1 code implementation • CVPR 2023 • Giacomo Zara, Subhankar Roy, Paolo Rota, Elisa Ricci
Open-set Unsupervised Video Domain Adaptation (OUVDA) deals with the task of adapting an action recognition model from a labelled source domain to an unlabelled target domain that contains "target-private" categories, which are present in the target but absent in the source.
1 code implementation • 9 Jan 2023 • Giacomo Zara, Victor Guilherme Turrisi da Costa, Subhankar Roy, Paolo Rota, Elisa Ricci
In this work we address a more realistic scenario, called open-set video domain adaptation (OUVDA), where the target dataset contains "unknown" semantic categories that are not shared with the source.
1 code implementation • 26 Jul 2022 • Victor G. Turrisi da Costa, Giacomo Zara, Paolo Rota, Thiago Oliveira-Santos, Nicu Sebe, Vittorio Murino, Elisa Ricci
On the other hand, the performance of a model in action recognition is heavily affected by domain shift.