1 code implementation • 4 Apr 2023 • Alec Diaz-Arias, Dmitriy Shin
In this paper we propose \textbf{\textit{ConvFormer}}, a novel convolutional transformer that leverages a new \textbf{\textit{dynamic multi-headed convolutional self-attention}} mechanism for monocular 3D human pose estimation.
Ranked #16 on 3D Human Pose Estimation on HumanEva-I
no code implementations • 3 Mar 2021 • Alec Diaz-Arias, Mitchell Messmore, Dmitriy Shin, Stephen Baek
Furthermore, our system can be combined with an off-the-shelf 2d pose detector and a depth map predictor to perform 3d pose estimation in the wild.