Attention! A Lightweight 2D Hand Pose Estimation Approach
원문 초록
Vision based human pose estimation is an non-invasive technology for Human-Computer Interaction (HCI). Direct use of the hand as an input device provides an attractive interaction method, with no need for specialized sensing equipment, such as exoskeletons, gloves etc, but a camera. Traditionally, HCI is employed in various applications spreading in areas including manufacturing, surgery, entertainment industry and architecture, to mention a few. Deployment of vision based human pose estimation algorithms can give a breath of innovation to these applications. In this letter, we present a novel Convolutional Neural Network architecture, reinforced with a Self-Attention module that it can be deployed on an embedded system, due to its lightweight nature, with just 1.9 Million parameters. The source code and qualitative results are publicly available.
함께 살펴볼 논문
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Monocular 3D Hand Pose Estimation with Implicit Camera Alignment
Analyzing the Synthetic-to-Real Domain Gap in 3D Hand Pose Estimation
SiMHand: Mining Similar Hands for Large-Scale 3D Hand Pose Pre-training
Towards Dynamic 3D Reconstruction of Hand-Instrument Interaction in Ophthalmic Surgery
OccRobNet : Occlusion Robust Network for Accurate 3D Interacting Hand-Object Pose Estimation
Hand Pose Estimation in the Task of Egocentric Actions
토론
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