Abstract: An example device for decoding video data includes a memory configured to store video data; and one or more processors implemented in circuitry and configured to: determine a number of multiple transform selection (MTS) candidates for a current block of video data, the number being greater than zero and different than four, the MTS candidates being MTS candidates other than a DCT2 candidate; determine one of the MTS candidates of the number of MTS candidates for the current block; inverse transform a transform block for the current block using the determined one of the MTS candidates to produce a residual block; and decode the current block using the residual block.

Abstract: A video decoder may be configured to construct motion vector candidates using possible sign values, respective magnitudes of motion vector difference components, and a motion vector predictor for a block of video data, wherein the possible sign values include a positive sign value and a negative sign value, sort the motion vector candidates based on a cost for each of the motion vector candidates to create a sorted list, determine a respective motion vector difference sign for each motion vector difference coordinate based on a motion vector sign predictor index and the sorted list, and decode the block of video data using the respective magnitudes of motion vector difference coordinates and the respective motion vector difference sign for each motion vector difference component.

Abstract: A method of decoding point cloud data comprises obtaining a bitstream that includes an arithmetically encoded syntax element indicating a vertical point position offset within a node of a tree that represents 3-dimensional positions of points in a point cloud represented by the point cloud data; and decoding the vertical point position offset, wherein decoding the vertical point position offset comprises: determining a laser index of a laser candidate in a set of laser candidates, wherein the determined laser index indicates a laser beam that intersects the node; determining a context index based on whether the laser beam is above a first distance threshold, between the first distance threshold and a second distance threshold, between the second distance threshold and a third distance threshold, or below the third distance threshold; and arithmetically decoding a bin of the vertical point position offset using a context indicated by the determined context index.

Abstract: In some examples, a method of decoding a point cloud includes decoding an initial QP value from an attribute parameter set. The method also includes determining a first QP value for a first component of an attribute of point cloud data from the initial QP value. The method further includes determining a QP offset value for a second component of the attribute of the point cloud data and determining a second QP value for the second component of the attribute from the first QP value and from the QP offset value. The method includes decoding the point cloud data based on the first QP value and further based on the second QP value.

Abstract: In some examples, a method of decoding a point cloud includes determining a first slice QP value for a first component of an attribute in a slice of point cloud data. The method also includes decoding a first delta QP value for the first component of the attribute for a region in the slice and determining a first region QP value for the first component of the attribute in the region from the first slice QP value and from the first delta QP value. The method further includes decoding a second delta QP value for the second component of the attribute for the region and determining a second region QP value for the second component of the attribute in the region from the second delta QP value. The method includes decoding the point cloud data based on the first and second region QP values.

Abstract: An example device for processing a point cloud includes: a memory configured to store at least a portion of the point cloud; and one or more processors implemented in circuitry and configured to: obtain planar information of a reference block of the point cloud; determine, based on the planar information of the reference block, a context; context-adaptive code, based on the context, a syntax element that indicates whether a current node is coded using a planar mode; code, based on the current node being coded using the planar mode, the current node using the planar mode.

Abstract: A method of decoding video data includes determining an intra prediction mode from a plurality of intra prediction modes for a current block of the video data, determining a low frequency non-separable transform (LFNST) kernel from a plurality of LFNST kernels for the current block based on the determined intra prediction mode, wherein at least one LFNST kernel of the plurality of LFNST kernels is associated with at least two different intra prediction modes of the plurality of intra prediction modes, applying an inverse of the determined LFNST kernel to coefficient values generated from a transform unit (TU) of the current block to generate intermediate values, applying an inverse primary transform on the intermediate values to generate residual data, and reconstructing the current block based on the residual data.

Abstract: An example device for decoding video data includes a memory configured to store video data; and one or more processors implemented in circuitry and configured to: determine a size of a current block of video data; determine an intra-prediction mode for the current block of video data; determine a mode group including the determined intra-prediction mode, the mode group being one of a plurality of mode groups, each including respective sets of intra-prediction modes; determine a set of available multiple transform selection (MTS) schemes for the current block according to the size and the intra-prediction mode for the current block; determine an MTS scheme from the set of available MTS schemes according to the determined mode group; apply transforms of the MTS scheme to a transform block of the current block to produce a residual block for the current block; and decode the current block using the residual block.

Abstract: A method of decoding point cloud data comprises obtaining a bitstream that is encoded to comply with one or more constraints and decoding the bitstream, wherein decoding the bitstream comprises: determining a residual value of a first component of an attribute of a point; generating a predicted value of a second component of the attribute of the point; and reconstructing the second component as a sum of the predicted value of the second component and a multiplication product of a scale factor for the second component and the residual value of the first component, wherein the constraints include a constraint that limits the first component of the attribute of the point, the residual value of the first component of the attribute of the point, the second component of the attribute, and the residual value of the second component of the attribute of the point to one or more predefined bitdepths.

Abstract: A video decoder can be configured to receive, for a first chroma component of a block of the video data, information for first residual samples that correspond to a difference between a first chroma block of the first chroma component and a first prediction block of the first chroma component; determine intermediate reconstructed samples based on the first residual samples; receive, for a second chroma component of the block of video data, information for second residual samples that correspond to a difference between a second chroma block of the second chroma component and the intermediate reconstructed samples; reconstruct the first chroma block based on the first residual samples and the first prediction block; reconstruct the second chroma block based on the second residual samples and the intermediate reconstructed samples; and output decoded video data comprising the reconstructed first chroma block and the reconstructed second chroma block.

Abstract: A video decoder can be configured to determine that a new scaling list for a set of scaling lists is to be predicted from a reference scaling list, wherein the new scaling list corresponds to a new scaling matrix; receive a syntax element that identifies an ID number corresponding to a scaling list of the set of scaling lists that is to be used as the reference scaling list; determine that the set of scaling lists does not include a scaling list with the ID number; and in response to determining that the set of scaling lists does not include the scaling list with the ID number, determine the new scaling matrix based on a set of default values.

Abstract: A video coder determines whether a coding mode of a first block of the video data is in a set of applicable coding modes. The set of applicable coding modes includes at least one of a block-based delta pulse code modulation mode, a transform skip mode, or a palette mode. The video coder determines whether a coding mode of a second block of the video data is in the set of applicable coding modes, wherein the second block is adjacent to the first block. The video coder determines that a deblocking filter is disabled for a color component of at least one of the first block or the second block based on at least one of: the coding mode of the first block being in the set of applicable coding modes or the coding mode of the second block being in the set of applicable coding modes.

Abstract: Techniques are disclosed for coding point cloud data using a scene model. An example device for coding point cloud data includes a memory configured to store the point cloud data and one or more processors implemented in circuitry and communicatively coupled to the memory. The one or more processors are configured to determine or obtain a scene model corresponding with a first frame of the point cloud data, wherein the scene model represents objects within a scene, the objects corresponding with at least a portion of the first frame of the point cloud data. The one or more processors are also configured to code a current frame of the point cloud data based on the scene model.

Abstract: A device for decoding a bitstream that includes point cloud data is configured to determine an octree that defines an octree-based splitting of a space containing the point cloud, wherein a leaf node of the octree contains one or more points of the point cloud; and directly decode positions of each of the one or more points in the leaf node, wherein to directly decode the positions of each of the one or more points in the leaf node, the one or more processors are further configured to: generate a prediction of the one or more points; and determine the one or more points based on the prediction.

Abstract: An example of processing a point cloud includes responsive to determining to predict a current point in the point cloud using predictive geometry coding, selecting, from a set of prediction modes, a prediction mode for the current point, wherein the set of prediction modes includes at least an intra prediction mode and an inter prediction mode; and responsive to selecting the inter prediction mode for the current point, predicting the current point of the point cloud using inter prediction.

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 device for coding a point cloud includes a memory configured to store the point cloud and one or more processors communicatively coupled to the memory. The one or more processors are configured to determine a value of a numerator syntax element, the value of the numerator syntax element being indicative of a numerator of a scale factor of the point cloud. The one or more processors are configured to determine a value of a denominator syntax element, the value of the denominator syntax element being indicative of a denominator of the scale factor of the point cloud. The one or more processors are configured to process the point cloud at least in part based on the scale factor of the point cloud.

Abstract: A method and device for encoding an image divided into blocks. The image contains two separate zones. The method implements the following: only in the event where the current block pertains to one of the zones of the image: encoding the current block using a prediction, the current block being predicted using a previously encoded and then decoded block located in the other zone of the image, the blocks of the other zone having been previously encoded and then decoded, and encoding information indicating the application of the prediction; and for any decoded block pertaining to the other zone of the image, storing the decoded block data.

Abstract: A method and device for encoding an image divided into blocks. The image contains two separate zones. The method implements the following: only in the event where the current block pertains to one of the zones of the image: encoding the current block using a prediction, the current block being predicted using a previously encoded and then decoded block located in the other zone of the image, the blocks of the other zone having been previously encoded and then decoded, and encoding information indicating the application of the prediction; and for any decoded block pertaining to the other zone of the image, storing the decoded block data.

Abstract: This disclosure describes video encoding and video decoding techniques for encoding and decoding video data in a chroma intra prediction mode. The techniques may improve the encoding and decoding process by simplifying aspects of the encoding and decoding process and by reducing a number of binarization tables used for the encoding and decoding. Moreover, reducing the number binarization tables may, in turn, reduce the amount of memory needed in an encoder device or decoder device to perform the video encoding or decoding process.