1 code implementation • 28 May 2024 • Vida Adeli, Soroush Mehraban, Irene Ballester, Yasamin Zarghami, Andrea Sabo, Andrea Iaboni, Babak Taati
Lastly, we establish a benchmark for the analysis of skeleton-based motion encoder models in clinical settings.
1 code implementation • 25 Oct 2023 • Soroush Mehraban, Vida Adeli, Babak Taati
Our proposed GCNFormer module exploits the local relationship between adjacent joints, outputting a new representation that is complementary to the transformer output.
Ranked #1 on 3D Human Pose Estimation on MPI-INF-3DHP
1 code implementation • 22 Aug 2023 • Caroline Malin-Mayor, Vida Adeli, Andrea Sabo, Sergey Noritsyn, Carolina Gorodetsky, Alfonso Fasano, Andrea Iaboni, Babak Taati
In this work we train a deep neural network to map from a two dimensional pose sequence, extracted from a video of an individual walking down a hallway toward a wall-mounted camera, to a set of three-dimensional spatiotemporal gait features averaged over the walking sequence.
no code implementations • ICCV 2021 • Vida Adeli, Mahsa Ehsanpour, Ian Reid, Juan Carlos Niebles, Silvio Savarese, Ehsan Adeli, Hamid Rezatofighi
Joint forecasting of human trajectory and pose dynamics is a fundamental building block of various applications ranging from robotics and autonomous driving to surveillance systems.
no code implementations • 14 Jul 2020 • Vida Adeli, Ehsan Adeli, Ian Reid, Juan Carlos Niebles, Hamid Rezatofighi
In this paper, we propose a novel framework to tackle both tasks of human motion (or trajectory) and body skeleton pose forecasting in a unified end-to-end pipeline.