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公开(公告)号：US20200242479A1
公开(公告)日：2020-07-30
申请号：US16731085
申请日：2019-12-31
申请人： STRADVISION, INC.
发明人： Kye-Hyeon KIM , Yongjoong KIM , Hak-Kyoung KIM , Woonhyun NAM , SukHoon BOO , Myungchul SUNG , Dongsoo SHIN , Donghun YEO , Wooju RYU , Myeong-Chun LEE , Hyungsoo LEE , Taewoong JANG , Kyungjoong JEONG , Hongmo JE , Hojin CHO
摘要： A learning method for transforming a virtual video on a virtual world to a more real-looking video is provided. And the method includes steps of: (a) a learning device instructing a generating CNN to apply a convolutional operation to an N-th virtual training image, N-th meta data and (N-K)-th reference information to generate an N-th feature map; (b) the learning device instructing the generating CNN to apply a deconvolutional operation to the N-th feature map to generate an N-th transformed image; (c) the learning device instructing a discriminating CNN to apply a discriminating CNN operation to the N-th transformed image to generate a category score vector; (d) the learning device instructing the generating CNN to generate a generating CNN loss by referring to the category score vector and its corresponding GT, and to perform backpropagation by referring to the generating CNN loss to learn parameters of the generating CNN.
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公开(公告)号：US20200250402A1
公开(公告)日：2020-08-06
申请号：US16721961
申请日：2019-12-20
申请人： STRADVISION, INC.
发明人： Kye-Hyeon KIM , Yongjoong KIM , Hak-Kyoung KIM , Woonhyun NAM , SukHoon BOO , Myungchul SUNG , Dongsoo SHIN , Donghun YEO , Wooju RYU , Myeong-Chun LEE , Hyungsoo LEE , Taewoong JANG , Kyungjoong JEONG , Hongmo JE , Hojin CHO
摘要： A method for face recognition by using a multiple patch combination based on a deep neural network is provided. The method includes steps of: a face-recognizing device, (a) if a face image with a 1-st size is acquired, inputting the face image into a feature extraction network, to allow the feature extraction network to generate a feature map by applying convolution operation to the face image with the 1-st size, and to generate multiple features by applying sliding-pooling operation to the feature map, wherein the feature extraction network has been learned to extract a feature using a face image for training having a 2-nd size and wherein the 2-nd size is smaller than the 1-st size; and (b) inputting the multiple features into a learned neural aggregation network, to allow the neural aggregation network to aggregate the multiple features and to output an optimal feature for the face recognition.
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公开(公告)号：US20200250514A1
公开(公告)日：2020-08-06
申请号：US16724302
申请日：2019-12-22
申请人： STRADVISION, INC.
发明人： Kye-Hyeon KIM , Yongjoong KIM , Hak-Kyoung KIM , Woonhyun NAM , SukHoon BOO , Myungchul SUNG , Dongsoo SHIN , Donghun YEO , Wooju RYU , Myeong-Chun LEE , Hyungsoo LEE , Taewoong JANG , Kyungjoong JEONG , Hongmo JE , Hojin CHO
摘要： A learning method for generating integrated object detection information by integrating first object detection information and second object detection information is provided. And the method includes steps of: (a) a learning device instructing a concatenating network to generate one or more pair feature vectors; (b) the learning device instructing a determining network to apply FC operations to the pair feature vectors, to thereby generate (i) determination vectors and (ii) box regression vectors; (c) the learning device instructing a loss unit to generate an integrated loss by referring to the determination vectors, the box regression vectors and their corresponding GTs, and performing backpropagation processes by using the integrated loss, to thereby learn at least part of parameters included in the DNN.
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公开(公告)号：US20200241526A1
公开(公告)日：2020-07-30
申请号：US16731089
申请日：2019-12-31
申请人： STRADVISION, INC.
发明人： Kye-Hyeon KIM , Yongjoong KIM , Hak-Kyoung KIM , Woonhyun NAM , SukHoon BOO , Myungchul SUNG , Dongsoo SHIN , Donghun YEO , Wooju RYU , Myeong-Chun LEE , Hyungsoo LEE , Taewoong JANG , Kyungjoong JEONG , Hongmo JE , Hojin CHO
摘要： A method for remotely controlling at least one autonomous vehicle is provided. The method includes steps of: an autonomous driving control device, (a) on condition that the autonomous driving control device detects driving environment by referring to sensor information and allows the autonomous vehicle to travel on an autonomous driving mode or a manual driving mode, determining whether the autonomous driving control device fails to establish a driving plan by using the driving environment and whether the autonomous driving control device fails to change to the manual driving mode by using the driving environment; and (b) if the autonomous driving control device fails to establish the driving plan or fails to change to the manual driving mode, selecting a remote control mode and transmitting request information to a remote control service providing server, to allow a remote driver to control the autonomous vehicle by using a specific remote vehicle.
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5.发明申请公开(公告)号：US20210357763A1
公开(公告)日：2021-11-18
申请号：US17135396
申请日：2020-12-28
申请人： Stradvision, Inc.
发明人： Hongmo JE , Dongkyu YU , Bongnam KANG , Yongjoong KIM
摘要： A method for predicting behavior using explainable self-focused attention is provided. The method includes steps of: a behavior prediction device, (a) inputting test images and the sensing information acquired from a moving subject into a metadata recognition module to apply learning operation to output metadata, and inputting the metadata into a feature encoding module to output features; (b) inputting the test images, the metadata, and the features into an explaining module to generate explanation information on affecting factors affecting behavior predictions, inputting the test images and the metadata into a self-focused attention module to output attention maps, and inputting the features and the attention maps into a behavior prediction module to generate the behavior predictions; and (c) allowing an outputting module to output behavior results and allowing a visualization module to visualize and output the affecting factors by referring to the explanation information and the behavior results.
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公开(公告)号：US20200241544A1
公开(公告)日：2020-07-30
申请号：US16731083
申请日：2019-12-31
申请人： STRADVISION, INC.
发明人： Kye-Hyeon KIM , Yongjoong KIM , Hak-Kyoung KIM , Woonhyun NAM , SukHoon BOO , Myungchul SUNG , Dongsoo SHIN , Donghun YEO , Wooju RYU , Myeong-Chun LEE , Hyungsoo LEE , Taewoong JANG , Kyungjoong JEONG , Hongmo JE , Hojin CHO
摘要： A learning method for performing a seamless parameter switch by using a location-specific algorithm selection for an optimized autonomous driving is provided. And the method includes steps of: (a) a learning device instructing a K-th convolutional layer to apply a convolution operation to K-th training images, to thereby generate K-th feature maps; (b) the learning device instructing a K-th output layer to apply a K-th output operation to the K-th feature maps, to thereby generate K-th estimated autonomous driving source information; (c) the learning device instructing a K-th loss layer to generate a K-th loss by using the K-th estimated autonomous driving source information and its corresponding GT, and then to perform backpropagation by using the K-th loss, to thereby learn K-th parameters of the K-th CNN; and (d) the learning device storing the K-th CNN in a database after tagging K-th location information to the K-th CNN.
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