no code implementations • ICCV 2023 • Zhiying Leng, Shun-Cheng Wu, Mahdi Saleh, Antonio Montanaro, Hao Yu, Yin Wang, Nassir Navab, Xiaohui Liang, Federico Tombari
In this work, we propose the first precise hand-object reconstruction method in hyperbolic space, namely Dynamic Hyperbolic Attention Network (DHANet), which leverages intrinsic properties of hyperbolic space to learn representative features.
1 code implementation • 21 Sep 2022 • Antonio Montanaro, Diego Valsesia, Enrico Magli
In this paper, we propose to embed the features of a point cloud classifier into the hyperbolic space and explicitly regularize the space to account for the part-whole hierarchy.
Ranked #9 on 3D Point Cloud Classification on ModelNet40
no code implementations • 1 Jul 2022 • Antonio Montanaro, Diego Valsesia, Enrico Magli
Inverse problems consist in reconstructing signals from incomplete sets of measurements and their performance is highly dependent on the quality of the prior knowledge encoded via regularization.
no code implementations • 20 Aug 2021 • Antonio Montanaro, Diego Valsesia, Giulia Fracastoro, Enrico Magli
Semi-supervised learning techniques are gaining popularity due to their capability of building models that are effective, even when scarce amounts of labeled data are available.