Abstract: A method and an apparatus are disclosed for video coding using an improved in-loop filter. The video coding method and the apparatus generate a residual frame from a reconstructed frame using a deep learning model. The video coding method and the apparatus improve performance of an in-loop filter by approximating an original residual frame by applying the generated residual frame to a linear model.

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 method and an apparatus are disclosed for video coding for refining predicted signals of intra prediction based on deep learning. The video coding method and the apparatus generate a refined intra predicted signal to improve video coding efficiency and video quality. The video coding method and the apparatus adaptively input a prediction block according to intra prediction of a current block, block information related to the current block, and neighboring reconstructed reference samples into a deep learning network.

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: In a method of predicting a position of an object at a future time point for a vehicle, video image information at a current time point and at a plurality of time points before the current time point acquired through a camera of the vehicle may be extracted as semantic segmentation image. A mask image imaging an attribute and position information of an object present in each of the video images may be extracted. A position distribution of the object may be predicted by deriving a plurality of hypotheses for a position of the object at a future time point through deep learning by receiving video images at the current time point and the time points before the current time point, a plurality of semantic segmentation images, a plurality of mask images, and ego-motion information of the vehicle, and calculating the plurality of hypotheses as a Gaussian mixture probability distribution.

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 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 VCM coding apparatus and a VCM coding method, related to a deep learning-based feature map coding apparatus in a multitasking system for machine vision, are provided for performing default procedures of generating and compressing a common feature map related to multiple tasks implied by an original video. The VCM coding apparatus and the VCM coding method can further generate and compress a task-specific feature map whenever needed for higher performance than obtainable with the common feature map to ensure relatively acceptable performance for both machine vision and human vision.

Abstract: A method and an apparatus for video coding using a deep learning-based in-loop filter for inter-prediction are disclosed. The video coding method and the apparatus utilize a deep learning-based in-loop filter for inter-prediction of a predictive frame (P-frame) and a bipredictive frame (B-frame) in order to mitigate various levels of image distortion according to a QP (quantization parameter) value present in the P-frame and the B-frame.

Abstract: An apparatus and method for coding machine vision data using a reduction of feature map are disclosed. To reduce the size of a feature map extracted by a machine task-specialized deep learning model, a Video Coding for Machines (VCM) coding apparatus and a method are provided. The VCM coding apparatus and the method utilize a sparsification method that reduces redundancy in terms of space and channels of the feature map, and the VCM coding apparatus and the method also utilize a feature map decomposition method based on tensor decomposition.

Abstract: A video coding method and an apparatus for refining predicted signals in intra prediction are disclosed. The video coding method and apparatus generate refined prediction signals approximating original video signals from predicted signals of intra prediction using a variable and fixed coefficient-based deep learning model to reduce the amount of data for residual signals, which are to be encoded.

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: A frame packing method in an MPEG immersive video format is provided. A frame packing method in association with an immersive-video encoding and decoding method efficiently arranges, on a single screen, texture information and depth information of a basic view and an additional view to increase the coding efficiency.

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 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 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: 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.