8 citations · 10 across the 3 of their papers we have counts for
5 papers
THOR-Net: End-to-end Graformer-based Realistic Two Hands and Object Reconstruction with Self-supervision
Ahmed Tawfik Aboukhadra, Jameel Malik, Ahmed Elhayek +2
Realistic reconstruction of two hands interacting with objects is a new and challenging problem that is essential for building personalized Virtual and Augmented Reality environmen…
HandVoxNet: Deep Voxel-Based Network for 3D Hand Shape and Pose Estimation from a Single Depth Map
Jameel Malik, Ibrahim Abdelaziz, Ahmed Elhayek +5
3D hand shape and pose estimation from a single depth map is a new and challenging computer vision problem with many applications. The state-of-the-art methods directly regress 3D…
Structure from Articulated Motion: Accurate and Stable Monocular 3D Reconstruction without Training Data
Onorina Kovalenko, Vladislav Golyanik, Jameel Malik +2
Recovery of articulated 3D structure from 2D observations is a challenging computer vision problem with many applications. Current learning-based approaches achieve state-of-the-ar…
DeepHPS: End-to-end Estimation of 3D Hand Pose and Shape by Learning from Synthetic Depth
Jameel Malik, Ahmed Elhayek, Fabrizio Nunnari +4
Articulated hand pose and shape estimation is an important problem for vision-based applications such as augmented reality and animation. In contrast to the existing methods which…
Simultaneous Hand Pose and Skeleton Bone-Lengths Estimation from a Single Depth Image
Jameel Malik, Ahmed Elhayek, Didier Stricker
Articulated hand pose estimation is a challenging task for human-computer interaction. The state-of-the-art hand pose estimation algorithms work only with one or a few subjects for…