Recent Advances in 3D Object and Hand Pose Estimation

2020/06/10 by Vincent Lepetit, Lepetit, Vincent
Computer Science · Engineering · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Hand Gesture Recognition Systems #Human Pose and Action Recognition #Robot Manipulation and Learning

paper · pdf · doi:10.48550/arxiv.2006.05927

openalex publication_date 2020/06/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

3D object and hand pose estimation have huge potentials for Augmented Reality, to enable tangible interfaces, natural interfaces, and blurring the boundaries between the real and virtual worlds. In this chapter, we present the recent developments for 3D object and hand pose estimation using cameras, and discuss their abilities and limitations and the possible future development of the field.

Citations

• Generalized Procrustes Analysis
• Long Short-Term Memory
• ImageNet Large Scale Visual Recognition Challenge
• Multilayer feedforward networks are universal approximators
• Distinctive Image Features from Scale-Invariant Keypoints
• ShapeNet: An Information-Rich 3D Model Repository
• Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired Data

Related

• Measuring Generalisation to Unseen Viewpoints, Articulations, Shapes and Objects for 3D Hand Pose Estimation under Hand-Object Interaction
• Vision-based Pose Estimation for Augmented Reality : A Comparison Study
• Articulated Hand Pose Estimation Review
• Efficient Annotation and Learning for 3D Hand Pose Estimation: A Survey
• Semi-supervised 3D Hand-Object Pose Estimation via Pose Dictionary Learning