no code implementations • 23 Mar 2023 • Trung Pham, Mehran Maghoumi, Wanli Jiang, Bala Siva Sashank Jujjavarapu, Mehdi Sajjadi Xin Liu, Hsuan-Chu Lin, Bor-Jeng Chen, Giang Truong, Chao Fang, Junghyun Kwon, Minwoo Park
The network is robust to sensor mounting variations (within some tolerances) and can be quickly customized for different vehicle types via efficient model fine-tuning thanks of its capability of taking calibration parameters as additional inputs during training and testing.
no code implementations • 21 Jun 2021 • Ariel Caputo, Andrea Giachetti, Simone Soso, Deborah Pintani, Andrea D'Eusanio, Stefano Pini, Guido Borghi, Alessandro Simoni, Roberto Vezzani, Rita Cucchiara, Andrea Ranieri, Franca Giannini, Katia Lupinetti, Marina Monti, Mehran Maghoumi, Joseph J. LaViola Jr, Minh-Quan Le, Hai-Dang Nguyen, Minh-Triet Tran
Gesture recognition is a fundamental tool to enable novel interaction paradigms in a variety of application scenarios like Mixed Reality environments, touchless public kiosks, entertainment systems, and more.
1 code implementation • 18 Nov 2020 • Mehran Maghoumi, Eugene M. Taranta II, Joseph J. LaViola Jr
We find that DeepNAG outperforms DeepGAN in accuracy, training time (up to 17x faster), and realism, thereby opening the door to a new line of research in generator network design and training for gesture synthesis.
1 code implementation • 30 Oct 2018 • Mehran Maghoumi, Joseph J. LaViola Jr
We propose DeepGRU, a novel end-to-end deep network model informed by recent developments in deep learning for gesture and action recognition, that is streamlined and device-agnostic.
Ranked #6 on Skeleton Based Action Recognition on SBU