Samsung Electronics Co., Ltd.

Youngo Park

Kwangpyo Choi

Jongseok Lee

Jaehwan Kim

Yumi Sohn

Myungjin Eom

Minseok Choi

Quockhanh Dinh

Sunyoung Jeon

Pilkyu Park

Chaeeun Lee

Sungchan Kim

Heechul Yang

Sangwook Baek

Dongkyu Kim

Sangwon Lee

Jungmin Lee

Yongsup Park

Kyonghwan Jin

Sangmi Lee

Gihyeon Bae

Taekeun Kang

An artificial intelligence (AI) decoding apparatus includes a memory storing one or more instructions; and a processor configured to execute the one or more instructions to obtain image data generated through first encoding on a first image; obtain a second image corresponding to the first image by performing first decoding on the image data; perform pre-processing of changing a resolution of the second image, according to a pre-determined output resolution; and obtain a fourth image having the pre-determined output resolution by applying AI up-scaling based on an up-scaling deep neural network (DNN) to a third image obtained as a result of the pre-processing.

Apparatus and method for performing artificial intelligence encoding and artificial intelligence decoding on image by using pre-processing

Provided is an electronic device configured to participate in video conference by using artificial intelligence (AI), the electronic device including a display and a processor configured to execute one or more instructions. The processor configured to obtain, from a server, image data generated by first encoding first image related to another electronic device participating in video conference, and AI data related to AI downscaling from original image to first image, obtain second image corresponding to first image by performing first decoding on image data, determine whether to perform AI upscaling on second image, based on importance of the other electronic device, based on determining to perform AI upscaling, obtain third image by performing AI upscaling on second image through an upscaling deep neural network and provide third image to display, and based on determining not to perform AI upscaling, provide second image to display.

Method and apparatus for artificial intelligence downscaling and upscaling during video conference

Provided is an electronic apparatus configured to provide an image based on artificial intelligence (AI), the electronic apparatus including a processor configured to execute one or more instructions stored in the electronic apparatus to obtain a first image by AI-downscaling an original image by a downscaling neural network, obtain first image data by encoding the first image, based on a display apparatus not supporting an AI upscaling function, obtain a second image by decoding the first image data, obtain a third image by AI-upscaling the second image by an upscaling neural network, and provide, to the display apparatus, second image data obtained by encoding the third image.

Image providing method and apparatus using artificial intelligence, and display method and apparatus using artificial intelligence

An electronic apparatus includes: a display; and a processor configured to: obtain a first image, identify an application used to obtain the first image, select neural network setting information corresponding to the identified application from among a plurality of pieces of neural network setting information, obtain a second image by artificial intelligence (AI)-upscaling the first image by using an upscaling neural network to which the selected neural network setting information is applied, and output the obtained second image via the display.

Electronic apparatus and method for reproducing image based on artificial intelligence according to application

An image processing apparatus for performing image quality processing on an image includes: a memory configured to store one or more instructions; and a processor configured to execute the one or more instructions stored in the memory to: obtain a first image by downscaling an input image by using a downscale network; extract first feature information corresponding to the first image by using a feature extraction network; obtain a second image by performing image quality processing on the first image based on the first feature information, by using an image quality processing network; and obtain an output image by upscaling the second image, extracting second feature information corresponding to the input image, and performing image quality processing on the upscaled second image based on the second feature information, by using an upscale network.

Image processing apparatus and operating method thereof

Methods and apparatuses for image encoding and image decoding are provided. The image decoding method includes: obtaining deep neural network (DNN) update permission information indicating whether one or more pieces of DNN setting information are updated; based on the DNN update permission information indicating that the one or more pieces of the DNN setting information are updated, obtaining DNN update information necessary for determining one or more pieces of the DNN setting information that are updated; determining the one or more pieces of the updated DNN setting information according to the DNN update information; and obtaining a third image by performing artificial intelligence (AI) up-scaling on a second image according to the one or more pieces of the updated DNN setting information.

Image encoding method and apparatus and image decoding method and apparatus using deep neural networks

A method includes obtaining, by a second processor of the electronic device, from a first processor of the electronic device, a control signal for obtaining image data, loading any one learning model of at least one learning model into a memory, obtaining, by using the camera module, raw image data of the object, from light reflected from the object, the raw image data being configured to have a specified color array consisting of a plurality of colors with respect to a plurality of pixels, obtaining, by using the loaded any one learning model, a color data set with respect to the plurality of pixels from the obtained raw image data, the color data set including a plurality of pieces of color data classified according to the plurality of colors, and obtaining the noise-reduced image data of the object by using the obtained color data set.

Method of generating noise-reduced image data and electronic device for performing the same

Provided is a method of adaptively performing artificial intelligence (AI) downscaling on an image during a video telephone call of a user terminal. The method includes obtaining, from an opposite user terminal, AI upscaling support information of the opposite user terminal that is a target of a video telephone call, determining whether the user terminal is to perform AI downscaling on an original image, based on the AI upscaling support information, based on determining that the user terminal is to perform AI downscaling on the original image, obtaining a first image by AI downscaling the original image using a downscaling deep neural network (DNN), generating image data by performing first encoding on the first image, and transmitting AI data including information related to the AI downscaling and the image data.

Method and apparatus for adaptive artificial intelligence downscaling for upscaling during video telephone call

An apparatus for performing artificial intelligence (AI) encoding on an image includes: a memory storing one or more instructions; and a processor configured to execute the one or more instructions stored in the memory to: determine a resolution of an original image; when the resolution of the original image is higher than a predetermined value, obtain a first image by performing AI downscaling on the original image via a downscaling deep neural network (DNN); when the resolution of the original image is lower than or equal to the predetermined value, obtain a first image by performing AI one-to-one preprocessing on the original image via a one-to-one preprocessing DNN for upscaling; generate image data by performing first encoding on the first image; and transmit the image data and AI data including information related to the AI downscaling or information related to the AI one-to-one preprocessing.

Method and apparatus for performing artificial intelligence encoding and artificial intelligence decoding

An artificial intelligence (AI) decoding method including obtaining image data generated from performing first encoding on a first image and AI data related to AI down-scaling of at least one original image related to the first image; obtaining a second image corresponding to the first image by performing first decoding on the image data; obtaining, based on the AI data, deep neural network (DNN) setting information for performing AI up-scaling of the second image; and generating a third image by performing the AI up-scaling on the second image via an up-scaling DNN operating according to the obtained DNN setting information. The DNN setting information is DNN information updated for performing the AI up-scaling of at least one second image via joint training of the up-scaling DNN and a down-scaling DNN used for the AI down-scaling.

Apparatus and method for performing artificial intelligence (AI) encoding and AI decoding on image

Provided is a decoding apparatus including: a communication interface configured to receive AI encoding data generated as a result of artificial intelligence (AI) down-scaling and first encoding of an original image; a processor configured to divide the AI encoding data into image data and AI data; and an input/output (I/O) device, wherein the processor is further configured to: obtain a second image by performing first decoding on a first image obtained by performing AI down-scaling on the original image, based on the image data; and control the I/O device to transmit the second image and the AI data to an external apparatus. In some embodiments, the external apparatus performs an AI upscaling of the second image using the AI data, and displays the resulting third image.

Decoding apparatus and operating method of the same, and artificial intelligence (AI) up-scaling apparatus and operating method of the same

A terminal for receiving streaming data may receive information of a plurality of different quality versions of an image content; request, based on the information, a server for a version of the image content from among the plurality of different quality versions of the image content; when the requested version of the image content and artificial intelligence (AI) data corresponding to the requested version of the image content are received, determines whether to perform AI upscaling on the received version of the image content, based on the AI data; and based on a result of the determining whether to perform AI upscaling, performs AI upscaling on the received version of the image content through a upscaling deep neural network (DNN) that is trained jointly with a downscaling DNN of the server.

Method and apparatus for streaming data

An image processing apparatus for performing image quality processing on an image includes a feature extraction network and an image quality processing network including one or more modulation blocks, wherein each of the one or more modulation blocks includes a convolution layer, a modulation layer, and an activation layer for processing the image.

Image processing apparatus and method of operating the same

An artificial intelligence (AI) decoding apparatus includes a memory storing one or more instructions, and a processor configured to execute the stored one or more instructions, to obtain image data corresponding to a first image that is encoded, obtain a second image corresponding to the first image by decoding the obtained image data, determine whether to perform AI up-scaling of the obtained second image, based on the AI up-scaling of the obtained second image being determined to be performed, obtain a third image by performing the AI up-scaling of the obtained second image through an up-scaling deep neural network (DNN), and output the obtained third image, and based on the AI up-scaling of the obtained second image being determined to be not performed, output the obtained second image.

Apparatuses and methods for performing artificial intelligence encoding and artificial intelligence decoding on image

Provided is an artificial intelligence (AI) decoding apparatus includes: a memory storing one or more instructions; and a processor configured to execute the one or more instructions stored in the memory, the processor is configured to: obtain AI data related to AI down-scaling an original image to a first image; obtain image data corresponding to an encoding result on the first image; obtain a second image corresponding to the first image by performing a decoding on the image data; obtain deep neural network (DNN) setting information among a plurality of DNN setting information from the AI data; and obtain, by an up-scaling DNN, a third image by performing the AI up-scaling on the second image, the up-scaling DNN being configured with the obtained DNN setting information, wherein the plurality of DNN setting information comprises a parameter used in the up-scaling DNN, the parameter being obtained through joint training of the up-scaling DNN and a down-scaling DNN, and wherein the down-scaling DNN is used to obtain the first image from the original image.

Growing community of inventors

Suwon-si, South Korea

Youngo Park