资源分类
》 资源 》论文》Cascaded Hand Pose Regression

Cascaded Hand Pose Regression

2019-12-17 | |  68 |   47 |   0

Abstract

We extends the previous 2D cascaded object pose regression work [9] in two aspects so that it works better for 3D articulated objects. Our fifirst contribution is 3D poseindexed features that generalize the previous 2D parameterized features and achieve better invariance to 3D transformations. Our second contribution is a principled hierarchical regression that is adapted to the articulated object structure. It is therefore more accurate and faster. Comprehensive experiments verify the state-of-the-art accuracy and effificiency of the proposed approach on the challenging 3D hand pose estimation problem, on a public dataset and our new dataset.

上一篇：Sparse Depth Super Resolution

下一篇：Real-time Visual Analysis of Microvascular Blood Flow for Critical Care

用户评价
全部评价

热门资源

  • Stratified Strate...

    In this paper we introduce Stratified Strategy ...

  • The Variational S...

    Unlike traditional images which do not offer in...

  • Learning to Predi...

    Much of model-based reinforcement learning invo...

  • Learning to learn...

    The move from hand-designed features to learned...

  • A Mathematical Mo...

    Direct democracy, where each voter casts one vo...