Qualcomm Incorporated

Shumaker & Sieffert, P.a.

Bappaditya Ray

Marta Karczewicz

Geert Van Der Auwera

Adarsh Krishnan Ramasubramonian

Louis Joseph Kerofsky

Luong Pham Van

Vadim Seregin

Han Huang

Muhammed Zeyd Coban

Yao-Jen Chang

Keming Cao

Wei-Jung Chien

Dmytro Rusanovskyy

Hilmi Enes Egilmez

Chun-Chi Chen

Hongtao Wang

Yu Han

A method of encoding or decoding video data includes determining a block vector for a current block of a current picture, the block vector identifying a fractional-pel position between reference samples in the current picture and having a fractional-pel resolution that is less than integer-pel resolution; generating a prediction block from reference samples in the current picture based on the fractional-pel position; and encoding or decoding the current block based on the prediction block.

Fractional-pel block vector for video coding

A device for decoding a bitstream that includes point cloud data can be configured to determine, based on syntax signaled in the bitstream, that in-tree quantization is enabled for a node; determine, for the node based on the syntax signaled in the bitstream, that an angular mode is activated for the node; in response to in-tree quantization being enabled for the node, determine for the node a quantized value representing a coordinate position relative to an origin position; scale the quantized value without clipping to determine a scaled value representing the coordinate position relative to the origin position; and determine a context for context decoding a plane position syntax element for the angular mode based on the scaled value representing the coordinate position relative to the origin position.

Angular mode and in-tree quantization in geometry point cloud compression

A method of encoding a point cloud includes determining, by one or more processors, a quantity of lasers used to capture light detection and ranging (LIDAR) data that represents the point cloud; and encoding, by the one or more processors, a laser index for a current node of the point cloud, wherein encoding the laser index comprises: obtaining a predicted laser index value of the current node; determining a residual laser index value for the current node, wherein determining the residual laser index value comprises constraining a sum of the residual laser index value and the predicted laser index value to be less than or equal to the determined quantity of lasers minus one; and encoding, in a bitstream, one or more syntax elements that represent the residual laser index value.

Clipping laser indices in predictive geometry coding for point cloud compression

A method of encoding or decoding video data includes constructing a list of chroma intra-prediction modes for a chroma block of a current block of the video data, wherein constructing includes adding intra-prediction modes of a first group to the list of chroma intra-prediction modes, the first group comprising two or more intra-prediction modes derived from intra-prediction modes of two or more co-located luma blocks of the current block that are co-located with the chroma block; determining an intra-prediction mode for the chroma block from the list of chroma intra-prediction modes; and encoding or decoding the chroma block based on the intra-prediction mode.

Intra chroma mode list construction for video coding

A video coder may adaptively determine whether to apply an inter-MTS (multiple transform set) mode to video data. The video coder may adaptively determine one or more of a maximum block size or a minimum block size for applying an inter-MTS mode. The video decoder may determine whether the inter-MTS mode is enabled for a block of video data based on a size of the block compared to one or more of the minimum block size or the maximum block size. and code the block using the inter-MTS mode based on the inter-MTS mode being enabled. Coding the block using the inter-MTS mode includes applying one or more transforms of a plurality of transforms to transform coefficients associated with the block of video data.

Flexible activation of multiple transform selection for inter-coding in video coding

A method of encoding point cloud data includes determining an amount by which a laser turns for determining points in a point cloud represented by the point cloud data, generating a syntax element indicative of the amount by which the laser turns, wherein a value of the syntax element is a defined value less than the amount by which the laser turns, and signaling the syntax element.

High level syntax refinements for geometry point cloud compression (G-PCC)

A method of encoding point cloud data comprises storing, in a buffer, a maximum coordinate of a pair of coordinates of an applicable node, wherein the applicable node is a most-recently encoded node with a same position as a current node along an applicable axis and the pair of coordinates are for axes different from the applicable axis; determining a context for a planar mode plane position of the current node, wherein determining the context for the planar mode plane position comprises determining, based on the maximum coordinate of the pair of coordinates of the applicable node, a distance value representing a distance between the current node and the applicable node; determining an increment value that indicates whether the distance value is greater than a threshold; and determining the context index based on the increment value; and entropy encoding the planar mode plane position using the determined context.

GPCC planar mode and buffer simplification

A method comprises obtaining a first laser angle; obtaining a second laser angle; obtaining a laser angle difference for a third laser angle; determining a predicted value based on the first laser angle and the second laser angle; and determining the third laser angle based on the predicted value and the laser angle difference for the third laser angle.

Coding of laser angles for angular and azimuthal modes in geometry-based point cloud compression

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.

Residual coding for geometry point cloud compression

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.

Performance improvement of geometry point cloud compression (GPCC) planar mode using inter prediction

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.

Hybrid-tree coding for inter and intra prediction for geometry coding

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.

Inter prediction coding for geometry point cloud compression

A device for encoding point cloud data, the device comprising: a memory to store the point cloud data; and one or more processors coupled to the memory and implemented in circuitry, the one or more processors configured to: determine a horizontal plane position of a node, wherein the horizontal plane position indicates a position of a single plane that is perpendicular to a first axis of a coordinate system, wherein the first axis is a horizontal axis; determine, from a plurality of contexts consisting of 8 contexts, a context for the horizontal plane position of the node; and perform arithmetic encoding on a syntax element indicating the horizontal plane position using the determined context.

Planar and azimuthal mode in geometric point cloud compression

A device to code a point cloud data that 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; code a data structure including data that represents a top threshold and a bottom threshold; classify points having height values between the top threshold and the bottom threshold into the set of ground points; classify points having height values above the top threshold or below the bottom threshold into the set of object points. The one or more processors code the ground points and the object points according to the classifications. The one or more processors code a geometry data unit header that includes data that overrides or refines the data of the data structure for the at least one of the top threshold or the bottom threshold.

Global motion estimation using road and ground object labels for geometry-based point cloud compression

Techniques are described for decoding video data. A video decoder may determine chroma blocks in a chroma quantization group (QG) of the video data, determine a quantization parameter predictor that is the same for each of the chroma blocks of the chroma QG, determine an offset value that is the same for two or more of the chroma blocks of the chroma QG, determine a quantization parameter value for each of the two or more of the chroma blocks in the chroma QG based on the quantization parameter predictor and the offset value inverse quantize coefficients of one or more residual blocks for the chroma blocks based on the determined quantization parameter value, generate the one or more residual blocks based on the inverse quantized coefficients, and reconstruct the chroma blocks based on the one or more residual blocks.

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San Diego, CA, United States of America

Bappaditya Ray