Abstract: A method and apparatus for intra-prediction coding of video data are provided. The apparatus includes a decoder that is configured to decode, from a bitstream, a syntax element indicating an intra-prediction type of a current block of the video data, and an intra-predictor that is configured to generate a prediction block for the current block by selectively performing matrix based intra-prediction or regular intra-prediction based on the intra-prediction type of the current block indicated by the syntax element.

Abstract: A method and apparatus for intra-prediction coding of video data are provided. The apparatus includes a decoder that is configured to decode, from a bitstream, a syntax element indicating an intra-prediction type of a current block of the video data, and an intra-predictor that is configured to generate a prediction block for the current block by selectively performing matrix based intra-prediction or regular intra-prediction based on the intra-prediction type of the current block indicated by the syntax element.

Abstract: A video decoding apparatus is provided for decoding pictures using inter-prediction. The video decoding apparatus includes a predictor that generates affine prediction samples for respective subblocks in a target block in a current picture to be decoded by performing affine motion prediction on a subblock-by-subblock basis using control point motion vectors which respectively correspond to corners of the target block. The predictor also modifies sample values of the affine prediction samples by executing a first coding tool, the first coding tool compensating for motion according to sample positions in each of the subblocks using the control point motion vectors.

Abstract: A coding tool is provided to improve the compression performance of inter prediction and is used at the encoder/decoder side to adjust the correction of a motion vector based on a high level syntax. In addition, a method is provided for simply performing an integer sample search step of searching for an integer offset and a fractional sample refinement step of searching for a sub-pixel offset in relation to motion vector refinement among coding tools.

Abstract: An apparatus for decoding video data includes a decoder configured to decode, from a bitstream, a syntax element indicating an intra-prediction type of a current block of the video data, and an intra-predictor configured to generate a prediction block for the current block by selectively performing matrix based intra-prediction (MIP) or regular intra-prediction based on the intra-prediction type of the current block indicated by the syntax element.

Abstract: A method and device for controlling coding tools are provided. The video decoding method includes decoding, from a high level of a bitstream, an enable flag indicating whether one or more coding tools are enabled. The coding tools includes a first coding tool that encodes sample values using luma component mapping based on a piecewise linear model. The method includes acquiring a value of an application flag depending on a value of the enable flag, by setting the application flag indicating whether to apply the coding tools to a predetermined value, or by decoding the application flag from a low level of the bitstream, the application flag including a first application flag indicating whether to apply the first coding tool. The coding tools are operated when the value of the application flag is a value indicating that the coding tools are applied.

Abstract: A method and device for controlling coding tools are provided. The video decoding method includes decoding, from a high level of a bitstream, an enable flag indicating whether one or more coding tools are enabled. The coding tools includes a first coding tool that encodes sample values using luma component mapping based on a piecewise linear model. The method includes acquiring a value of an application flag depending on a value of the enable flag, by setting the application flag indicating whether to apply the coding tools to a predetermined value, or by decoding the application flag from a low level of the bitstream, the application flag including a first application flag indicating whether to apply the first coding tool. The coding tools are operated when the value of the application flag is a value indicating that the coding tools are applied.

Abstract: A video codec uses a block-based deep learning model. The video codec, when processing video blocks by using a deep learning model, generates a super block by stacking or packing the respective ones of YUV video blocks and inputs the generated super block to the deep learning model.

Abstract: A coding tool is provided to improve the compression performance of inter prediction and is used at the encoder/decoder side to adjust the correction of a motion vector based on a high level syntax. In addition, a method is provided for simply performing an integer sample search step of searching for an integer offset and a fractional sample refinement step of searching for a sub-pixel offset in relation to motion vector refinement among coding tools.

Abstract: A video encoding or decoding apparatus and method perform existing inter prediction on a current block to generate a motion vector and predicted samples. The video encoding or decoding apparatus and method generate enhanced predicted samples for the current block using a deep learning-based video prediction network (VPN) on the basis of the motion vector, the reference samples, the predicted samples, and the like to improve encoding efficiency.

Abstract: A video encoding method and a video decoding method is provided for generating improved picture quality for a current frame and improving encoding efficiency. The video encoding method and the video decoding method further include an in-loop filter that detects a reference region from a current frame and a reference frame using a deep learning-based detection model and then combines the detected reference region with the current frame.

Abstract: An inter prediction method allows a variable coefficient deep learning model to adaptively learn characteristics of a video; transmits a variable coefficient deep learning model parameter generated from the learning from an image encoding device to an image decoding device; and refers to a virtual reference frame generated by the variable coefficient deep learning model.

Abstract: An image acquisition apparatus includes: a multispectral image sensor configured to acquire images in at least four channels based on a second wavelength band of about 10 nm to about 1,000 nm; and a processor configured to estimate illumination information of the images by inputting the images of at least four channels to a deep learning network trained in advance, and convert colors of the acquired images using the estimated illumination information.

Abstract: Image decoding of decoding a sequence of coded pictures on a block-by-block basis is provided. The image decoding incudes decoding a first high-level syntax element from a bitstream to determine, at a sequence level, whether affine motion prediction is allowed. A second high-level syntax element is extracted for each of at least one coding tool from the bitstream depending on the first high-level syntax element. At a picture level, the method determines whether each of the at least one coding tool is allowed. The coding tool includes sample-by-sample adjustment of affine motion prediction samples.

Abstract: An apparatus for decoding video data includes a decoder configured to decode, from a bitstream, a syntax element indicating an intra-prediction type of a current block of the video data, and an intra-predictor configured to generate a prediction block for the current block by selectively performing matrix based intra-prediction (MIP) or regular intra-prediction based on the intra-prediction type of the current block indicated by the syntax element.

Abstract: Image decoding of decoding a sequence of coded pictures on a block-by-block basis is provided. The image decoding incudes decoding a first high-level syntax element from a bitstream to determine, at a sequence level, whether affine motion prediction is allowed. A second high-level syntax element is extracted for each of at least one coding tool from the bitstream depending on the first high-level syntax element. At a picture level, the method determines whether each of the at least one coding tool is allowed. The coding tool includes sample-by-sample adjustment of affine motion prediction samples.

Abstract: Image decoding of decoding a sequence of coded pictures on a block-by-block basis is provided. The image decoding incudes decoding a first high-level syntax element from a bitstream to determine, at a sequence level, whether affine motion prediction is allowed. A second high-level syntax element is extracted for each of at least one coding tool from the bitstream depending on the first high-level syntax element. At a picture level, the method determines whether each of the at least one coding tool is allowed. The coding tool includes sample-by-sample adjustment of affine motion prediction samples.

Abstract: A coding tool is provided to improve the compression performance of inter prediction and is used at the encoder/decoder side to adjust the correction of a motion vector based on a high level syntax. In addition, a method is provided for simply performing an integer sample search step of searching for an integer offset and a fractional sample refinement step of searching for a sub-pixel offset in relation to motion vector refinement among coding tools.

Abstract: Disclosed is a method for video encoding and decoding using adaptive color transform on a residual signal. In particular, the maximum memory size required for adaptive color transform is limited by: controlling whether to allow color space conversion on a sequence level according to a syntax element indicating the maximum conversion size allowed for a sequence of pictures; or controlling whether to apply color space conversion on a block level according to the size of a coding block.

Abstract: A method of building an ad-hoc network of a wireless relay node and an ad-hoc network system are disclosed. The method includes verifying state information representing a relative distance and angle to a neighboring node capable of receiving data when each of relay nodes transmits the data, determining an action representing a change over time of each relay node, determining, based on an amount of change in a network throughput determined according to the state information and an amount of energy consumption according to the action, a reward corresponding to the action, and building a network including a source node, a destination node, and a plurality of relay nodes by generating, based on a reward of each of the relay nodes, a policy that allows a cumulative reward to be maximized.