Abstract: An example device includes memory configured to store the point cloud data and one or more processors configured to determine a first point of the point cloud data to be a first node of a first prediction tree branch. The one or more processors are configured to determine that a first azimuth difference between the first point and a second point of the point cloud data does not meet a first azimuth threshold, and based on that determination, determine the second point to be a second node of the first prediction tree branch. The one or more processors are configured to determine that a second azimuth difference between a third point of the point cloud data and a fourth point of the point cloud data meets the first azimuth threshold and based on that determination, determine the fourth point to be a first node of a second prediction tree branch.

Abstract: An example method of decoding video data that includes receiving one or more syntax elements of the video data indicative of whether a first type of coding scheme or a second type of coding scheme is applied to residual values of a block of video data coded with transform skip, wherein the residual values are indicative of a difference between the block and a prediction block, and wherein, in transform skip, the residual values are not transformed from a sample domain to a frequency domain. The method includes determining a type of coding scheme to apply to the residual values based on the one or more syntax elements, determining the residual values based on the determined type of coding scheme, and reconstructing the block based on the determined residual values and the prediction block.

Abstract: A method of encoding point cloud data includes receiving, for a first encoding process, geometry data of the point cloud data of a source point cloud; encoding, in accordance with the first encoding process, the geometry data to generate encoded geometry data of a target point cloud and a geometry bitstream; decoding the encoded geometry data to generate reconstructed geometry data; performing an attribute recomputing process on attribute data of the point cloud data of the source point cloud based on the reconstructed geometry data to generate recomputed, reconstructed point cloud data of the target point cloud; and encoding, in accordance with a second encoding process, the recomputed, reconstructed point cloud data to generate an attribute bitstream.

Abstract: A device for video decoding can be configured to obtain, from a syntax structure in a bitstream comprising an encoded representation of the video data, a syntax element indicating whether 6-parameter affine prediction is enabled for blocks corresponding to the syntax structure, wherein the blocks corresponding to the syntax structure comprise a first block; based on the syntax element indicating that the 6-parameter affine prediction is enabled for the blocks corresponding to the syntax structure, use the 6-parameter affine prediction to generate a predictive block for the first block; and use the predictive block and residual data to reconstruct the first block.

Abstract: An example device for coding video data includes memory configured to store the video data and one or more processors communicatively coupled to the memory. The one or more processors are configured to reduce a bit length of one or more input variables for a linear regression operation to generate one or more reduced bit length input variables, the input variables including at least one of a) one or more delta coordinates, b) one or more delta motion vectors, or c) a value representing a number of subblocks. The one or more processors are configured to perform the linear regression operation and derive an affine motion model based on the performing the linear regression on the one or more reduced bit length input variables. The one or more processors are configured to code a current block of the video data based on the affine motion model.

Abstract: An example device for decoding video data includes a memory configured to store video data; and a processing system comprising one or more processors implemented in circuitry, the processing system being configured to: inverse transform a block of transform coefficients of a block of the video data using an inverse non-separable primary transform (NSPT), without using an inverse separable transform, to reconstruct a residual block of the block of the video data; and decode the block using the residual block.

Abstract: An example device for decoding video data includes: a memory configured to store video data; and a processing system comprising one or more processors implemented in circuitry, the processing system being configured to: determine whether motion information of a block of video data is for sub-blocks of the block larger than individual pixels of the block or for the individual pixels, the block being associated with data indicating that the block is to be predicted using affine motion compensation; in response to determining that the motion information of the block is for the sub-blocks, perform sub-block-based affine motion compensation to form a prediction block for the block; in response to determining that the motion information is for the individual pixels, perform pixel-based affine motion compensation to form the prediction block for the block; and decode the block using the prediction block.

Abstract: A method coding video data includes receiving a block of video data, wherein chroma samples of the block of video data are subsampled relative to luma samples of the block of video data (e.g., 4:2:0 or 4:2:2 video content). A video coder may determine a subsampling technique, from a plurality of subsampling techniques, for the luma samples of the block of video data for a cross-component prediction mode, and may code the block of video data using the subsampling technique and the cross-component prediction mode. A first subsampling technique of the plurality of subsampling techniques includes not applying subsampling to the luma samples of the block of video data, and a second subsampling technique of the plurality of subsampling techniques includes a combination of downsampling filters to be applied to the luma samples of the block.

Abstract: A video encoder may transform residual data by using a transform selected from a group of transforms. The transform is applied to the residual data to create a two-dimensional array of transform coefficients. A scanning mode is selected to scan the transform coefficients in the two-dimensional array into a one-dimensional array of transform coefficients. The combination of transform and scanning mode may be selected from a subset of combinations that is based on an intra-prediction mode. The scanning mode may also be selected based on the transform used to create the two-dimensional array. The transforms and/or scanning modes used may be signaled to a video decoder.

Abstract: A video coder may be configured to partition a coding block into subblocks, and generate initial subblock motion vectors for a plurality of the subblocks. The video coder may further refine the initial subblock motion vectors for the plurality of the subblocks using decoder side motion vector refinement to produce refined subblock motion vectors for the plurality of the subblocks, and perform a linear regression on the refined subblock motion vectors and coordinates of the plurality of the subblocks to derive an affine motion model. The video coder may then code the coding block using the derived affine motion model.

Abstract: This disclosure describes gradient-based prediction refinement. A video coder (e.g., video encoder or video decoder) determines one or more prediction blocks for inter-predicting a current block (e.g., based on one or more motion vectors for the current block). In gradient-based prediction refinement, the video coder modifies one or more samples of the prediction block based on various factors such as displacement in a horizontal direction, the horizontal gradient, a displacement in the vertical direction, and a vertical gradient. This disclosure provides for gradient-based prediction refinement where a precision level of the displacement (e.g., at least one of the horizontal or vertical displacement) is unified (e.g., the same) for different prediction modes.

Abstract: An example device for decoding video data includes a memory configured to store video data; and a processing system comprising one or more processors implemented in circuitry, the processing system being configured to: refine a first control point motion vector (CPMV) of a current block of the video data using a first decoder-side motion vector refinement (DMVR) process to form a first refined CPMV for the current block; refine a second CPMV of the current block of video data using a second DMVR process, independently of the first DMVR process, to form a second refined CPMV for the current block; form a prediction block for the current block using the first refined CPMV and the second refined CPMV; and decode the current block using the prediction block. In some examples, the CPMVs may each be decoded using a respective merge index and a respective motion vector difference (MVD).

Abstract: Encoding and decoding video data using an affine decoder side motion vector derivation (DMVR) mode includes receiving a block of video data to be decoded using the affine DMVR mode, and dividing the block into a plurality of subblocks. A video encoder and video decoder may determine a final offset for the affine DMVR mode using a first subset of the plurality of subblocks. The video encoder and decoder may code the block of video data using the final offset to generate a coded block of video data.

Abstract: A method for decoding point cloud data comprises, based on a comparison of a maximum difference value and a threshold, applying an inverse function to a set of one or more jointly coded values to recover (i) residual values for attribute values of a current point of point cloud data and (ii) a predictor index that indicates a predictor in a predictor list, wherein predictors in the predictor list are based on attribute values of one or more neighbor points; determining predicted attribute values based on the predictor index; and reconstructing the attribute values of the current point based on the residual values and the predicted attribute values.

Abstract: A device and method for coding video data is described. The device may generate filtered samples by performing, in a predicted samples domain, interpolation filtering and a second filtering from a group of one or more of: an adaptive filter, a domain transform filter, a scaler, or a local illumination compensation (LIC). The device may generate one or more of: residual data based on the filtered samples, or reconstructed samples based on the filtered samples; and code the video data based on one or more of the residual data or the reconstructed samples.

Abstract: A video decoder can be configured to determine a number of allowed non-zero coefficients for a block of video data based on a size of the block; obtain a set of dequantized coefficients for the block, wherein the set of dequantized coefficients comprises a first subset of dequantized coefficients that includes non-zero dequantized coefficients and a second subset of dequantized coefficients that includes all zero coefficients, wherein a number of coefficients in the first subset of dequantized coefficients is equal to the number of allowed non-zero coefficients for the block of video data; apply an inverse low-frequency non-separable transform (LFNST) to the first subset of dequantized coefficients to determine a first intermediate subset of coefficients; and apply an inverse separable transform to the first intermediate subset of coefficients and at least a portion of the second subset of coefficients to determine a block of reconstructed residual values.

Abstract: Systems, methods, and media are provided for loop filtering across raster scan slices. One example includes obtaining the video data comprising one or more pictures and a first block of a picture having a pixel subject to filtering. A second block is determined to be located in the first slice in a particular relation to the second block. A third block that includes pixels for filtering the pixel is determined to be in a second slice at a diagonal corner of the first block, with filtering across slice boundaries disabled. First one or more pixels of the second block are identified as available for performing loop filtering of the pixel and second one or more pixels of the third block identified as unavailable for performing the loop filtering of the pixel of the first block. The first one or more pixels and the second one or more pixels are padded.

Abstract: An example device for coding point cloud data includes a memory configured to store data representing points of a point cloud, and one or more processors implemented in circuitry and configured to: determine height values of points in a point cloud; classify the points into a set of ground points or a set of object points according to the height values; and code the ground points and the object points according to the classifications. The one or more processors may determine top and bottom thresholds and classify the ground and object points according to the top and bottom thresholds. The one or more processors may further code a data structure, such as a geometry parameter set (GPS), including data representing the top and bottom thresholds.

Abstract: An example method includes determining a color component of a unit of video data; determining, based at least on the color component, a context for context-adaptive binary arithmetic coding (CABAC) a syntax element that specifies a value of a low-frequency non-separable transform (LFNST) index for the unit of video data; CABAC decoding, based on the determined context and via a syntax structure for the unit of video data, the syntax element that specifies the value of the LFNST index for the unit of video data; and inverse-transforming, based on a transform indicated by the value of the LFNST index, transform coefficients of the unit of video data.

Abstract: A method of encoding video data includes determining an integer sample in a reference picture of the video data; determining, based on the integer sample, at least a first fractional sample and a second fractional sample, wherein the first fractional sample has a first fractional pel resolution, and the second fractional sample has a second fractional pel resolution different from the first fractional pel resolution; subsequent to determining both the first fractional sample and the second fractional sample, determining a first cost metric associated with the first fractional sample and a second cost metric associated with the second fractional sample; determining a reference block for a current block based on at least one of the first cost metric or the second cost metric; and encoding the current block based on the reference block.