Invention Application
- Patent Title: DEPTH DETECTION METHOD, METHOD FOR TRAINING DEPTH ESTIMATION BRANCH NETWORK, ELECTRONIC DEVICE, AND STORAGE MEDIUM
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Application No.: US17813870Application Date: 2022-07-20
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Publication No.: US20220351398A1Publication Date: 2022-11-03
- Inventor: Zhikang Zou , Xiaoqing Ye , Hao Sun
- Applicant: Beijing Baidu Netcom Science Technology Co., LTD.
- Applicant Address: CN Beijing
- Assignee: Beijing Baidu Netcom Science Technology Co., LTD.
- Current Assignee: Beijing Baidu Netcom Science Technology Co., LTD.
- Current Assignee Address: CN Beijing
- Priority: CN202111155117.3 20210929
- Main IPC: G06T7/50
- IPC: G06T7/50 ; G06T7/73

Abstract:
A depth detection method, a method for training a depth estimation branch network, an electronic device, and a storage medium are provided, which relate to the field of artificial intelligence, particularly to the technical fields of computer vision and deep learning, and may be applied to intelligent robot and automatic driving scenarios. The specific implementation includes: extracting a high-level semantic feature in an image to be detected, wherein the high-level semantic feature is used to represent a target object in the image to be detected; inputting the high-level semantic feature into a pre-trained depth estimation branch network, to obtain distribution probabilities of the target object in respective sub-intervals of a depth prediction interval; and determining a depth value of the target object according to the distribution probabilities of the target object in the respective sub-intervals and depth values represented by the respective sub-intervals.
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