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公开(公告)号：US11461639B2
公开(公告)日：2022-10-04
申请号：US16336995
申请日：2018-08-16
摘要： A training method of a neural network for implementing image style transfer, an image processing method and an image processing device are disclosed. The training method includes: acquiring a first training input image and a second training input image; performing a style transfer process on the first training input image by the neural network to obtain a training output image; based on the first training input image, the second training input image and the training output image, calculating a loss value of parameters of the neural network through a loss function; and modifying the parameters of the neural network according to the loss value, where the loss function satisfies a predetermined condition, obtaining a trained neural network, where the loss function doesn't satisfy the predetermined condition, continuing to repeatedly perform above training process, the loss function including a weight-bias-ratio loss function.
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公开(公告)号：US20210334642A1
公开(公告)日：2021-10-28
申请号：US16604410
申请日：2019-04-23
发明人： Pablo Navarrete Michelini , Dan Zhu , Hanwen Liu
摘要： The present disclosure generally relates to the field of deep learning technologies. An apparatus for generating a plurality of correlation images may include a feature extracting unit configured to receive a training image and extracting at least one or more of feature from the training image to generate a first feature image based on the training image; a normalizer configured to normalize the first feature image and generate a second feature image; and a shift correlating unit configured to perform a plurality of translational shifts on the second feature image to generate a plurality of shifted images, correlate each of the plurality of shifted images with the second feature image to generate the plurality of correlation images.
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公开(公告)号：US20210097645A1
公开(公告)日：2021-04-01
申请号：US16465294
申请日：2018-12-17
发明人： Pablo Navarrete Michelini , Dan Zhu , Hanwen Liu
摘要： The present disclosure relates to an image processing method. The image processing method may include upscaling a feature image of an input image by an upscaling convolutional network to obtain a upscaled feature image; downscaling the upscaled feature image by a downscaling convolutional network to obtain a downscaled feature image; determining a residual image between the downscaled feature image and the feature image of the input image; upscaling the residual image between the downscaled feature image and the feature image of the input image to obtain an upscaled residual image; correcting the upscaled feature image using the upscaled residual image to obtain a corrected upscaled feature image; and generating a first super-resolution image based on the input image using the corrected upscaled feature image.
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公开(公告)号：US10547888B2
公开(公告)日：2020-01-28
申请号：US15306212
申请日：2016-01-20
IPC分类号： H04N21/2662 , H04N21/2343 , H04N19/184 , H04N19/44 , H04L29/06 , H04N21/4402
摘要： According to embodiments of the present disclosure, a method for processing an adaptive media service at an encoder includes a first acquisition step of acquiring a first data stream including first image encoding data obtained by encoding a first image sequence, a second acquisition step of acquiring at least one second data stream, each second data steam including second image encoding data obtained by encoding a second image sequence and a target optimization parameter corresponding to the second image encoding data, a first selection step of selecting one data stream from a first data stream set in accordance with a condition of the receiver, the first data stream set at least including the first data stream and the at least one second data stream, and a first transmission step of transmitting the selected data stream to the receiver.
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5.发明授权公开(公告)号：US10515435B2
公开(公告)日：2019-12-24
申请号：US15821095
申请日：2017-11-22
发明人： Pablo Navarrete Michelini , Hanwen Liu , Xiaoyu Li
摘要： The disclosure discloses an apparatus for upscaling an image, a method for training the same, and a method for upscaling an image, where a convolutional neural network circuit obtains feature images of the image, a multiplexer upscales the image by integrating every n*n feature images of an input signal into a feature image with a resolution which is n times the resolution of a feature image of the image, where n is an integer greater than 1.
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公开(公告)号：US10311547B2
公开(公告)日：2019-06-04
申请号：US15741781
申请日：2017-06-23
摘要： An image upscaling system includes at least two convolutional neural network modules and at least one synthesizer. The convolutional neural network module and the synthesizer are alternately connected to one another. The first convolutional neural network module receive an input image and the corresponding supplemental image, generate a first number of the feature images, and output them to the next synthesizer connected thereto. Other convolutional neural network modules each may receive the output image from the previous synthesizer and the corresponding supplemental image, generate a second number of feature images, and output them to the next synthesizer connected thereto, or output them from the image upscaling system. The synthesizer may synthesize every n*n feature images in the received feature image into one feature image and output the resultant third number of feature images to the next convolutional neural network module connected thereto or output them from the image upscaling system.
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公开(公告)号：US20190139191A1
公开(公告)日：2019-05-09
申请号：US15921961
申请日：2018-03-15
摘要： The embodiments of the present disclosure provide an image processing method, and a processing device. The image processing method comprises: acquiring a first image including N components, where N is a positive integer greater than or equal to 1; and performing image conversion processing on the first image using a generative neural network, to output a first output image, wherein the generative neural network is trained using a Laplace transform function.
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公开(公告)号：US10230902B2
公开(公告)日：2019-03-12
申请号：US15560094
申请日：2017-03-22
发明人： Han Yan , Pablo Navarrete Michelini
摘要： The present disclosure provides a method and device for correcting video flicker. The method comprises: performing statistics on grayscale values of a previous frame of video image to obtain a histogram of the grayscale values of the previous frame of video image; determining correction weights for correcting grayscale values of a next frame of video image according to the histogram; and correcting the grayscale values of the next frame of video image according to the correction weights.
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公开(公告)号：US10019642B1
公开(公告)日：2018-07-10
申请号：US15518404
申请日：2016-03-02
摘要： An image upsampling system, a training method thereof and an image upsampling method are provided, the feature images of an image are obtained by using the convolutional network, upsampling processing is performed on the images with the muxer layer to synthesize every n×n feature images in the input signal into a feature image with the resolution amplified by n×n times, in the upsampling procedure with the muxer layer, information of respective feature images in the input signal is recorded in the generated feature image(s) without loss; and thus, every time when the image passes through a muxer layer with an upsampling multiple of n, the image resolution can be increased by n×n times.
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公开(公告)号：US20230115094A1
公开(公告)日：2023-04-13
申请号：US17047935
申请日：2019-12-19
发明人： Dan Zhu , Hanwen Liu , Pablo Navarrete Michelini
IPC分类号： G06T13/40 , G06T11/60 , G06T7/194 , G06T7/70 , G06F3/0482 , G06F3/04845 , G06F3/04883
摘要： A computer-implemented method is provided. The computer-implemented method includes rendering a dynamic effect to one or more objects in an image. The method includes setting boundary points surrounding a foreground object to define a boundary area in which a dynamic movement is to be realized; setting a movement line to define a dynamic movement direction along which the dynamic movement is to be realized, wherein setting the movement line includes detecting a continuous touch over different positions on the touch control display panel; setting a stationary area to define an area in which the dynamic movement is prohibited, wherein setting the stationary area includes detecting a first touch area corresponding to the stationary area on the touch control display panel; and generating an animation of the foreground object in the boundary area moving along the dynamic movement direction, thereby realizing the dynamic effect in the image.
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