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Mar, 2017
基于特权信息的深度序列动作识别RNN的学习和优化
Learning and Refining of Privileged Information-based RNNs for Action Recognition from Depth Sequences
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Zhiyuan Shi, Tae-Kyun Kim
TL;DR
本文提出了一种基于特权信息(PI)的深度序列动作识别方法,通过多任务学习将PI作为辅助任务引入,提高了模型的鉴别能力和训练效果。
Abstract
Existing RNN-based approaches for
action recognition
from
depth sequences
require either skeleton joints or hand-crafted depth features as inputs. An end-to-end manner, mapping from raw depth maps to action class
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