发明公开
- 专利标题: SYSTEM AND METHOD FOR EYE-GAZE DIRECTION-BASED PRE-TRAINING OF NEURAL NETWORKS
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申请号: US18489338申请日: 2023-10-18
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公开(公告)号: US20240143074A1公开(公告)日: 2024-05-02
- 发明人: Ron M. Hecht , Omer Tsimhoni , Dan Levi , Shaul Oron , Andrea Forgacs , Ohad Rahamim , Gershon Celniker
- 申请人: GM GLOBAL TECHNOLOGY OPERATIONS LLC
- 申请人地址: US MI Detroit
- 专利权人: GM GLOBAL TECHNOLOGY OPERATIONS LLC
- 当前专利权人: GM GLOBAL TECHNOLOGY OPERATIONS LLC
- 当前专利权人地址: US MI Detroit
- 主分类号: G06F3/01
- IPC分类号: G06F3/01 ; G06T7/50 ; G06V10/74
摘要:
A method of training a disparity estimation network. The method includes obtaining an eye-gaze dataset having first images with at least one gaze direction associated with each of the first images. A gaze prediction neural network is trained based on the eye-gaze dataset to develop a model trained to provide a gaze prediction for an external image. A depth database is obtained that includes second images having depth information associated with each of the second images. A disparity estimation neural network for object detection is trained based on an output from the gaze prediction neural network and an output from the depth database.
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