- 专利标题: LEARNING METHOD AND LEARNING DEVICE FOR IMPROVING SEGMENTATION PERFORMANCE TO BE USED FOR DETECTING ROAD USER EVENTS USING DOUBLE EMBEDDING CONFIGURATION IN MULTI-CAMERA SYSTEM AND TESTING METHOD AND TESTING DEVICE USING THE SAME
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申请号: EP19207717.0申请日: 2019-11-07
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公开(公告)号: EP3686778A1公开(公告)日: 2020-07-29
- 发明人: Kim, Kye-Hyeon , Kim, Yongjoong , Kim, Insu , Kim, Hak-Kyoung , Nam, Woonhyun , Boo, SukHoon , Sung, Myungchul , Yeo, Donghun , Ryu, Wooju , Jang, Taewoong , Jeong, Kyungjoong , Je, Hongmo , Cho, Hojin
- 申请人: Stradvision, Inc.
- 申请人地址: No. 4427, Complex 4, 67, Cheongam-ro, Nam-gu Pohang-si, Gyeongsangbuk-do 37673 KR
- 专利权人: Stradvision, Inc.
- 当前专利权人: Stradvision, Inc.
- 当前专利权人地址: No. 4427, Complex 4, 67, Cheongam-ro, Nam-gu Pohang-si, Gyeongsangbuk-do 37673 KR
- 代理机构: V.O.
- 优先权: US201916257993 20190125
- 主分类号: G06K9/00
- IPC分类号: G06K9/00
摘要:
A learning method for improving segmentation performance to be used for detecting road user events including pedestrian events and vehicle events using double embedding configuration in a multi-camera system is provided. The learning method includes steps of: a learning device instructing similarity convolutional layer to generate similarity embedding feature by applying similarity convolution operations to a feature outputted from a neural network; instructing similarity loss layer to output a similarity loss by referring to a similarity between two points sampled from the similarity embedding feature, and its corresponding GT label image; instructing distance convolutional layer to generate distance embedding feature by applying distance convolution operations to the similarity embedding feature; instructing distance loss layer to output a distance loss for increasing inter-class differences among mean values of instance classes and decreasing intra-class variance values of the instance classes; backpropagating at least one of the similarity loss and the distance loss.
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