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REINFORCEMENT LEARNING-BASED LABEL-FREE SIX-DIMENSIONAL ITEM ATTITUDE PREDICTION METHOD AND DEVICE

机译:基于加强学习的无标签六维物品姿态预测方法和装置

摘要

A reinforcement learning-based label-free six-dimensional item attitude prediction method and device. The method comprises: obtaining a target image (14) for prediction, the target image (14) being a two-dimensional image (201) comprising a target object; performing, according to the target image (14), attitude prediction using a pre-trained attitude prediction model (12), so as to obtain a prediction result (16), the attitude prediction model (12) being a model (202) obtained by performing reinforcement learning according to a sample image; and determining, according to the prediction result (16), a three-dimensional position and a three dimensional direction (203) of the target object. The attitude prediction model (12) is trained by introducing reinforcement learning, and attitude prediction is performed according to the target image (14) by using the pretrained attitude prediction model (12), so that the problem of six-dimensional item attitude estimation based on a two-dimensional image can be solved when there is no real attitude labelling, and the prediction effect of label-free six-dimensional item attitude prediction is ensured.
机译:基于加强学习的无标签的六维物品姿态预测方法和装置。该方法包括:获得用于预测的目标图像(14),目标图像(14)是包括目标对象的二维图像(201);根据目标图像(14),使用预先训练的姿态预测模型(12)进行姿态预测,以获得预测结果(16),姿态预测模型(12)是获得的模型(202)通过根据样本图像进行强化学习;根据预测结果(16),根据目标对象的三维位置和三维方向(203)来确定。姿态预测模型(12)通过引入增强学习训练,并且通过使用预制姿态预测模型(12)来执行根据目标图像(14)来执行姿态预测,从而基于六维物品姿态估计的问题在没有真正的姿态标记时可以解决在二维图像上,并且确保了无标签的六维物品姿态预测的预测效果。

著录项

  • 公开/公告号WO2021184530A1

    专利类型

  • 公开/公告日2021-09-23

    原文格式PDF

  • 申请/专利权人 TSINGHUA UNIVERSITY;

    申请/专利号WO2020CN91342

  • 发明设计人 JI XIANGYANG;SHAO JIANZHUN;

    申请日2020-05-20

  • 分类号G06T7/73;

  • 国家 CN

  • 入库时间 2022-08-24 21:14:53

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