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: 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: A device comprises one or more processors configured to: obtain a value for a first laser, the value for the first laser indicating a number of probes in an azimuth direction of the first laser; decode a syntax element for a second laser, wherein the syntax element for the second laser indicates a difference between the value for the first laser and a value for the second laser, the value for the second laser indicating a number of probes in the azimuth direction of the second laser; determine the value for the second laser indicating the number of probes in the azimuth direction of the second laser based on the first value and the indication of the difference between the value for the first laser and the value for the second laser; and decode a point based on the number of probes in the azimuth direction of the second laser.

Abstract: An example method of decoding a point cloud includes selecting, from a plurality of predefined prediction modes, a prediction mode for performing predictive geometry coding of a position of a current node of the point cloud, wherein the plurality of prediction modes includes at least: a zero prediction mode, and a delta prediction mode; responsive to selecting the zero prediction mode: determining a radius, an azimuth, and a laser index of a parent node of the current node; inferring an azimuth and a laser index of a predicted position of the current node as the azimuth and the laser index of the parent node; inferring a radius of the predicted position to be a minimum radius value, wherein the minimum radius value is different than the radius of the parent node; and determining, based on the predicted position of the current node, the position of the current node.

Abstract: A G-PCC encoder and G-PCC decoder may quantize and scale, respectively, a position of a child node. The G-PCC encoder may control the precision of the quantization and scaling using a quantization parameter (QP) value and a parameter value k, wherein the parameter value k specifies a number of QP points per doubling of a scaling step size to be used at the G-PCC decoder.

Abstract: A method of encoding point cloud data includes signaling at least one of: a first syntax element indicating that planar mode is disabled for a current node when angular mode is enabled; or a second syntax element indicating that angular mode is enabled for the current node; bypassing signaling of values for a planar mode for the current node in a condition where the first syntax element indicates that the planar mode is disabled for the current node when the angular mode is enabled, or in a condition where the second syntax element indicates that the angular mode is enabled for the current node; and encoding the current node in a mode other than the planar mode.

Abstract: A point cloud encoder and decoder are configured to code point cloud data using predictive geometry coding and a vertical predictor. A vertical predictor is a previously coded point in the point cloud having a different laser ID compared to the currently coded point. The point cloud encoder and decoder may be configured to determine a pivot laser ID, determine a vertical predictor for a current point of the point cloud data, wherein the vertical predictor is based on a second point having a second laser ID different than the pivot laser ID, and code the current point using the vertical predictor and predictive geometry decoding.

Abstract: A point cloud encoder and point cloud decoder are configured to convert Cartesian coordinates of a point of point cloud data to spherical coordinates. The spherical coordinates include a radius, an azimuth value, and a laser ID. The point cloud encoder and point cloud decoder may perform the conversion for the azimuth value using a fixed-point implementation using a variable shift value based on a number of bits used for coding azimuth.

Abstract: An example method of encoding a point cloud includes obtaining a value of a secondary residual for geometry coding a current predictive tree node of the point cloud; and encoding the value of the secondary residual, wherein encoding the value comprises: encoding, using a first set of context-adaptive binary arithmetic coding (CABAC) contexts, prefix bins of a syntax element having a value that specifies an absolute value of the value of the secondary residual minus 2; and encoding, using a second set of CABAC contexts that is different than the first set of contexts, suffix bins of the syntax element.

Abstract: Point clouds may be coded using a plurality of laser angles. In one example, a video coder may be configured to code a plurality of syntax elements that indicate respective values of a plurality of laser angles in a sorted order according to a constraint.

Abstract: A G-PCC coder is configured to receive the point cloud data, determine a final quantization parameter (QP) value for the point cloud data as a function of a node QP offset multiplied by a geometry QP multiplier, and code the point cloud data using the final QP value to create an coded point cloud.

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: A method of decoding point cloud data comprises obtaining a bitstream that includes an arithmetically encoded syntax element indicating a vertical plane position of a planar mode of a node; and decoding the vertical plane position of the planar mode in the node, wherein decoding the vertical plane position of the planar mode 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 the vertical plane position of the planar mode using a context indicated by the determined context index.

Abstract: A device for coding video data includes a processor configured to generate an inter-prediction block and an intra-prediction block for a current block of video data; for each sample of a prediction block to be generated: determine a first weight for the sample according to a position of the sample in the prediction block; determine a second weight for the sample according to the position of the sample in the prediction block; apply the first weight to a sample at the position in the inter-prediction block to generate a weighted inter-prediction sample; apply the second weight to a sample at the position in the intra-prediction block to generate a weighted intra-prediction sample; and calculate a value for the sample at the position in the prediction block using the weighted inter-prediction sample and the weighted intra-prediction sample; and code the current block using the prediction block.

Abstract: An example device for decoding point cloud data includes memory configured to store the point cloud data and one or more processors implemented in circuitry and coupled to the memory. The one or more processors are configured to determine dimensions of a region box and determine dimensions of a slice bounding box. The one or more processors are also configured to decode a slice of the point cloud data associated with the slice bounding box. The dimensions of the region box are constrained to not exceed the dimensions of the slice bounding box.

Abstract: An example device for decoding point cloud data includes a memory configured to store point cloud data; and one or more processors implemented in circuitry and configured to: determine a number of times to upscale a downscaled encoded representation of a point cloud geometry; decode the downscaled encoded representation of the point cloud geometry; upscale the downscaled representation of the point cloud geometry the number of times to form an upscaled representation of the point cloud geometry; and reproduce a point cloud using the upscaled representation of the point cloud geometry.

Abstract: A video coder may be configured to code video data by performing splitting of a coding unit (CU) of video data using intra sub-partition (ISP) to form a set of prediction blocks. The video coder may group a plurality of the prediction blocks from the set of prediction blocks into a first prediction block group (PBG). The video coder may reconstruct samples of prediction blocks included in the first PBG independently of samples of other prediction blocks included in the first PBG.

Abstract: A video encoder maintains a first reference picture list; maintains a second reference picture list; determines that a picture is an instantaneous decoding refresh (IDR) picture; determines that reference picture list syntax elements are present in a slice header for the IDR picture; and in response to determining that the picture is the IDR picture and that the reference picture list syntax elements are present in the slice header for the IDR picture, updates the first reference picture list and the second reference picture list such that no picture in the first reference picture list and no picture in the second reference picture list precedes, in output order or decoding order, any preceding instant random access point (IRAP) picture in decoding order.

Abstract: A method of decoding a point cloud comprises: reconstructing a position of a point of the point cloud; determining a quantized attribute value for the point; deriving a quantization parameter (QP) bit depth offset for the point; deriving a QP range for the point based on the QP bit depth offset for the point; determining a quantization step size for the point based on the QP range for the point; and inverse quantizing the quantized attribute value for the point based on the quantization step size for the point.

Abstract: A device for encoding a point cloud comprises a memory configured to store point cloud data for the point cloud; and one or more processors configured to: determine a residual value associated with a current point of the point cloud, the residual value associated with the current point being a radius residual or an azimuth residual; determine a context for entropy encoding the residual value based on whether the current point is coded with intra prediction or inter prediction; and entropy encode the residual value using the determined context.