2 code implementations • 11 Apr 2024 • Miruna-Alexandra Gafencu, Yordanka Velikova, Mahdi Saleh, Tamas Ungi, Nassir Navab, Thomas Wendler, Mohammad Farid Azampour
Purpose: Ultrasound (US) imaging, while advantageous for its radiation-free nature, is challenging to interpret due to only partially visible organs and a lack of complete 3D information.
no code implementations • 5 Feb 2024 • Mahdi Saleh, Michael Sommersperger, Nassir Navab, Federico Tombari
We also incorporate cross-attention mechanisms to capture the interplay between the objects.
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 • 1 Sep 2023 • Lennart Bastian, Vincent Bürgin, Ha Young Kim, Alexander Baumann, Benjamin Busam, Mahdi Saleh, Nassir Navab
We demonstrate that our multi-modal registration framework can localize images on the 3D surface topology of a patient-specific organ and the mean shape of an SSM.
1 code implementation • 15 Apr 2023 • Lennart Bastian, Alexander Baumann, Emily Hoppe, Vincent Bürgin, Ha Young Kim, Mahdi Saleh, Benjamin Busam, Nassir Navab
Statistical shape models (SSMs) are an established way to represent the anatomy of a population with various clinically relevant applications.
1 code implementation • CVPR 2023 • Hao Yu, Zheng Qin, Ji Hou, Mahdi Saleh, Dongsheng Li, Benjamin Busam, Slobodan Ilic
To this end, we introduce RoITr, a Rotation-Invariant Transformer to cope with the pose variations in the point cloud matching task.
1 code implementation • 27 Sep 2022 • Hao Yu, Ji Hou, Zheng Qin, Mahdi Saleh, Ivan Shugurov, Kai Wang, Benjamin Busam, Slobodan Ilic
More specifically, 3D structures of the whole frame are first represented by our global PPF signatures, from which structural descriptors are learned to help geometric descriptors sense the 3D world beyond local regions.
no code implementations • 31 Jul 2022 • Mahdi Saleh, Yige Wang, Nassir Navab, Benjamin Busam, Federico Tombari
The proposed hierarchical model achieves state-of-the-art shape classification in mean accuracy and yields results on par with the previous segmentation methods while requiring significantly fewer computations.
1 code implementation • CVPR 2022 • Yongzhi Su, Mahdi Saleh, Torben Fetzer, Jason Rambach, Nassir Navab, Benjamin Busam, Didier Stricker, Federico Tombari
Dense methods also improved pose estimation in the presence of occlusion.
no code implementations • CVPR 2022 • Mahdi Saleh, Shun-Cheng Wu, Luca Cosmo, Nassir Navab, Benjamin Busam, Federico Tombari
Shape matching has been a long-studied problem for the computer graphics and vision community.
1 code implementation • NeurIPS 2021 • Hao Yu, Fu Li, Mahdi Saleh, Benjamin Busam, Slobodan Ilic
We study the problem of extracting correspondences between a pair of point clouds for registration.
1 code implementation • NeurIPS 2021 • Hao Yu, Fu Li, Mahdi Saleh, Benjamin Busam, Slobodan Ilic
We study the problem of extracting correspondences between a pair of point clouds for registration.
1 code implementation • 18 Oct 2020 • Mahdi Saleh, Shervin Dehghani, Benjamin Busam, Nassir Navab, Federico Tombari
3D Point clouds are a rich source of information that enjoy growing popularity in the vision community.
1 code implementation • 7 Apr 2020 • Stefan Denner, Ashkan Khakzar, Moiz Sajid, Mahdi Saleh, Ziga Spiclin, Seong Tae Kim, Nassir Navab
Our results show that spatio-temporal information in longitudinal data is a beneficial cue for improving segmentation.