A Prototype-Based Generalized Zero-Shot Learning Framework for Hand Gesture Recognition
文献类型：会议论文
| 作者 | Jinting Wu1,2 ; Yujia Zhang2; Xiaoguang Zhao2
|
| 出版日期 | 2021-01 |
| 会议日期 | 2021-1 |
| 会议地点 | Online |
| 英文摘要 | Hand gesture recognition plays a signifificant role in human-computer interaction for understanding various human gestures and their intent. However, most prior works can only recognize gestures of limited labeled classes and fail to adapt to new categories. The task of Generalized Zero-Shot Learning (GZSL) for hand gesture recognition aims to address the above issue by leveraging semantic representations and detecting both seen and unseen class samples. In this paper, we propose an end-to-end prototype-based GZSL framework for hand gesture recognition which consists of two branches. The fifirst branch is a prototype-based detector that learns gesture representations and determines whether an input sample belongs to a seen or unseen category. The second branch is a zero-shot label predictor which takes the features of unseen classes as input and outputs predictions through a learned mapping mechanism between the feature and the semantic space. We further establish a hand gesture dataset that specififically targets this GZSL task, and comprehensive experiments on this dataset demonstrate the effectiveness of our proposed approach on recognizing both seen and unseen gestures. |
| 源URL | [http://ir.ia.ac.cn/handle/173211/49703]  |
| 专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_先进机器人控制团队 |
| 作者单位 | 1.University of Chinese Academy of Sciences 2.Institute of Automation, Chinese Academy of Sciences |
| 推荐引用方式 GB/T 7714 | Jinting Wu,Yujia Zhang,Xiaoguang Zhao. A Prototype-Based Generalized Zero-Shot Learning Framework for Hand Gesture Recognition[C]. 见:. Online. 2021-1. |
入库方式： OAI收割
来源：自动化研究所
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