PEAN: 3D Hand Pose Estimation Adversarial Network
文献类型：会议论文
| 作者 | Linhui Sun ; Yifan Zhang; Jian Cheng; Hanqing Lu
|
| 出版日期 | 2021-01 |
| 会议日期 | 2021-1 |
| 会议地点 | Milan, Italy |
| 英文摘要 | Despite recent emerging research attention, 3D hand pose estimation still suffers from the problems of predicting inaccurate or invalid poses which conflict with physical and kinematic constraints. To address these problems, we propose a novel 3D hand pose estimation adversarial network (PEAN) which can implicitly utilize such constraints to regularize the prediction in an adversarial learning framework. PEAN contains two parts: a 3D hierarchical estimation network (3DHNet) to predict hand pose, which decouples the task into multiple sub tasks with a hierarchical structure; a pose discrimination network (PDNet) to judge the reasonableness of the estimated 3D hand pose, which back-propagates the constraints to the estimation network. During the adversarial learning process, PDNet is expected to distinguish the estimated 3D hand pose and the ground truth, while 3DHNet is expected to estimate more valid pose to confuse PDNet. In this way, 3DHNet is capable of generating 3D poses with accurate positions and adaptively adjusting the invalid poses without additional prior knowledge. Experiments show that the proposed 3DHNet does a good job in predicting hand poses, and introducing PDNet to 3DHNet does further improve the accuracy and reasonableness of the predicted results. As a result, the proposed PEAN achieves the state-of-the-art performance on three public hand pose estimation datasets. |
| 源URL | [http://ir.ia.ac.cn/handle/173211/54538]  |
| 专题 | 自动化研究所_模式识别国家重点实验室_图像与视频分析团队 |
| 通讯作者 | Yifan Zhang |
| 作者单位 | 1.School of Artificial Intelligence, University of Chinese Academy of Sciences, 100049, Beijing, China 2.NLPR & AIRIA, Institute of Automation, Chinese Academy of Sciences |
| 推荐引用方式 GB/T 7714 | Linhui Sun,Yifan Zhang,Jian Cheng,et al. PEAN: 3D Hand Pose Estimation Adversarial Network[C]. 见:. Milan, Italy. 2021-1. |
入库方式： OAI收割
来源：自动化研究所
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