Abstract: Disclosed herein are a method and apparatus for video decoding and a method and apparatus for video encoding. A prediction block for a target block is generated by predicting the target block using a prediction network, and a reconstructed block for the target block is generated based on the prediction block and a reconstructed residual block. The prediction network includes an intra-prediction network and an inter-prediction network and uses a spatial reference block and/or a temporal reference block when it performs prediction. For learning in the prediction network, a loss function is defined, and learning in the prediction network is performed based on the loss function.

Abstract: Disclosed is an eyeball movement analysis system. The eyeball movement analysis system includes an image capturing unit configured to acquire a first image of an eyeball at a reference location and acquire a second image of the eyeball at a moved location, and an eyeball movement analyzing unit configured to calculate a rotational angle of the eyeball and a translational distance of the eyeball in a process of moving the eyeball from the reference location to the moved location through comparison of the first image and the second image.

Abstract: Disclosed herein are a method, an apparatus and a storage medium for performing encoding/decoding on an image using a subpicture. A picture may be partitioned into various units such as subpictures and slices, and various syntax elements and structures may be used to specify the units. In an embodiment, there is a method for configuring a reference picture list for motion compensation in the case where the location of a reference subpicture to be referred to for motion compensation is different from the location of a target subpicture. Further, in an embodiment, there is provided a method for providing the configuration of a reference picture list and an override on the number of activated reference indexes.

Abstract: Disclosed herein are a method, an apparatus and a storage medium for image encoding/decoding. For efficient image compression, efficient syntax is required. Pieces of information required for image decoding may be structurally or semantically associated with each other. Based on this association, whether signaling of one piece of information is to be performed may be determined based on another piece of information. Further, based on this association, the signaling order or priority of multiple pieces of information may be determined. Depending on this determination, based on the number of subpictures present in a picture in high-level syntax, the number of slices present in the picture may be selectively signaled.

Abstract: The present invention relates to a medical use of a compound, of Chemical Formula 1, for treating, alleviating or preventing non-alcoholic steatohepatitis (NASH) and/or hepatic fibrosis.

Abstract: Disclosed herein are a method, apparatus and storage medium for image encoding/decoding using a reference picture. A picture is divided into multiple sub-pictures. The sub-pictures of the picture share a reference picture list. In order to determine sub-pictures that share the reference picture list, specific information is signaled from an encoding apparatus to a decoding apparatus. For each sub-picture that does not share a reference picture list for an additional sub-picture, a reference picture list for the sub-picture is separately configured.

Abstract: An inter-prediction method and apparatus uses a reference frame generated based on deep learning. In the inter-prediction method and apparatus, a reference frame is selected, and a virtual reference frame is generated based on the selected reference frame. A reference picture list is configured to include the generated virtual reference frame, and inter prediction for a target block is performed based on the virtual reference frame. The virtual reference frame may be generated based on a deep-learning network architecture, and may be generated based on video interpolation and/or video extrapolation that use the selected reference frame.

Abstract: Disclosed herein are a video decoding method and apparatus and a video encoding method and apparatus. A transformed block is generated by performing a first transformation that uses a prediction block for a target block. A reconstructed block for the target block is generated by performing a second transformation that uses the transformed block. The prediction block may be a block present in a reference image, or a reconstructed block present in a target image. The first transformation and the second transformation may be respectively performed by neural networks. Since each transformation is automatically performed by the corresponding neural network, information required for a transformation may be excluded from a bitstream.

Abstract: An apparatus comprising one or more processors, a communication circuit, and a memory for storing instructions, which when executed, performs a method of recognizing a user utterance. The method comprises: receiving first data associated with a user utterance, performing, a first determination to determine whether the user utterance includes the first data and a specified word, performing a second determination to determine whether the first data includes the specified word, transmitting the first data to an external server, receiving a text generated from the first data by the external server, performing a third determination to determine whether the received text matches the specified word, and determining whether to activate the voice-based input system based on the third determination.

Abstract: Disclosed herein are a method and apparatus for video decoding and a method and apparatus for video encoding. A prediction block for a target block is generated by predicting the target block using a prediction network, and a reconstructed block for the target block is generated based on the prediction block and a reconstructed residual block. The prediction network includes an intra-prediction network and an inter-prediction network and uses a spatial reference block and/or a temporal reference block when it performs prediction. For learning in the prediction network, a loss function is defined, and learning in the prediction network is performed based on the loss function.

Abstract: Disclosed is an eyeball movement analysis system. The eyeball movement analysis system includes an image capturing unit configured to acquire a first image of an eyeball at a reference location and acquire a second image of the eyeball at a moved location, and an eyeball movement analyzing unit configured to calculate a rotational angle of the eyeball and a translational distance of the eyeball in a process of moving the eyeball from the reference location to the moved location through comparison of the first image and the second image.

Abstract: A vehicle temperature control system includes: an air conditioning unit configured to cool and heat an interior of a vehicle; a first thermoelectric module mounted in a steering wheel of the vehicle and configured to be selectively heated or cooled; a second thermoelectric module mounted in a seat of the vehicle and configured to be selectively heated or cooled; and an integrated control unit configured to integrally control the air conditioning unit, the first thermoelectric module, and the second thermoelectric module, thereby obtaining an advantageous effect of improving temperature control efficiency and energy efficiency.

Abstract: Disclosed herein are a method and apparatus for compressing learning parameters for training of a deep-learning model and transmitting the compressed parameters in a distributed processing environment. Multiple electronic devices in the distributed processing system perform training of a neural network. By performing training, parameters are updated. The electronic device may share the updated parameter thereof with additional electronic devices. In order to efficiently share the parameter, the residual of the parameter is provided to the additional electronic devices. When the residual of the parameter is provided, the additional electronic devices update the parameter using the residual of the parameter.

Abstract: Disclosed herein are a video decoding method and apparatus and a video encoding method and apparatus. A virtual frame is generated by a video generation network including a generation encoder and a generation decoder. The virtual frame is used as a reference frame in inter prediction for a target. Further, a video generation network for inter prediction may be selected from among multiple video generation networks, and inter prediction that uses the selected video generation network may be performed.

Abstract: A method and apparatus for image compression using a latent variable are provided. The multiple components of the latent variable may be sorted in order of importance. Through sorting, when the feature information of only some of the multiple components is used, the quality of a reconstructed image may be improved. In order to generate a latent variable, the components of which are sorted in order of importance, learning may be performed in various manners. Also, less important information may be eliminated from the latent variable, and processing, such as quantization, may be applied to the latent variable. Through elimination and processing, the amount of data for the latent variable may be reduced.

Abstract: Disclosed herein are a video decoding method and apparatus and a video encoding method and apparatus. In quantization and dequantization, multiple quantization methods and multiple dequantization methods may be used. The multiple quantization methods include a variable-rate step quantization method and a fixed-rate step quantization method. The variable-rate step quantization method may be a quantization method in which an increment in a quantization step depending on an increase in a value of a quantization parameter by 1 is not fixed. The fixed-rate step quantization method may be a quantization method in which the increment in the quantization step depending on the increase of the value of the quantization parameter by 1 is fixed.

Abstract: The present invention relates to a method and apparatus for performing encoding and decoding using a variably-sized quantization coefficient group, in quantization coefficient group encoding and decoding of video compression technology.

Abstract: The present invention relates to a method and apparatus for performing encoding and decoding using a variably-sized quantization coefficient group, in quantization coefficient group encoding and decoding of video compression technology.

Abstract: Disclosed herein are a method and apparatus for measuring video quality based on a perceptually sensitive region. The quality of video may be measured based on a perceptually sensitive region and a change in the perceptually sensitive region. The perceptually sensitive region includes a spatial perceptually sensitive region, a temporal perceptually sensitive region, and a spatio-temporal perceptually sensitive region. Perceptual weights are applied to a detected perceptually sensitive region and a change in the detected perceptually sensitive region. Distortion is calculated based on the perceptually sensitive region and the change in the perceptually sensitive region, and a result of quality measurement for a video is generated based on the calculated distortion.

Abstract: Disclosed herein are a video decoding method and apparatus and a video encoding method and apparatus. In image encoding, encoding using multiple quantization parameters is performed on a transform coefficient. Two quantized coefficients are generated through encoding that uses two quantization parameters. Based on the two quantized coefficients, a quantized coefficient difference is generated. Information about the quantized coefficient difference is transmitted from an encoding apparatus to a decoding apparatus through binary encoding. The information about the quantized coefficient difference may be selectively transmitted. By means of the information about the quantized coefficient difference, a high-quality video may be provided.