Abstract: A device for decoding video data can be configured to determine a prediction block for a current block of the video data; determine a residual block for the current block of the video data; process residual data of the residual block to determine processed residual data; store the processed residual data; add the prediction block to the residual block to determine a reconstructed block; and perform adaptive loop filtering (ALF) on the reconstructed block, based on the processed residual data.

Abstract: An example device for decoding video data includes a processing system configured to determine an initial block vector predictor (BVP) for a current block of video data; determine a set of valid block vector difference (BVD) values using a template size, the valid BVD values being BVD values that, when added to the BVP, refer to a region of a picture that is entirely within a search area of the picture, the region including a reference block and a template, the template having the template size and being used to perform template matching decoder-side block vector derivation; select one of the valid BVD values as a final BVD; add the final BVD to the BVP to form a block vector (BV); generate a prediction block using the BV; and decode the current block using the prediction block.

Abstract: Devices and techniques are disclosed for coding video data. An example device includes one or more memories configured to store the video data and one or more processors coupled to the one or more memories. The one or more processors are configured to determine to code a first block of the video data using intra block copy merge mode with block vector differences (IBC-MBVD). The one or more processors are configured to process a syntax element indicative of whether to use IBC-MBVD with fractional-pel offsets or to use IBC-MBVD with integer-pel offsets. The one or more processors are configured to code the first block based on a determination of whether to use IBC-MBVD with fractional-pel offsets or IBC-MBVD with integer-pel offsets.

Abstract: Methods and devices for decoding including a processor configured to determine which picture is a collocated picture, and determine a location of an associated block of the video data in the collocated picture that corresponds to the current block of video data in the current coding picture, based on using previously decoded blocks in the current coding picture to find an initial motion vector between the associated block in the collocated picture and the current block in the current coding picture, where the associated block of the video data includes at least one first derived motion vector. The processor configured to determine at least one second derived motion vector associated with the current block in the current coding picture, when the initial motion vector points to the collocated picture, based on the at least on first derived motion vector associated with the associated block in the collocated picture.

Abstract: A video encoder may be configured to encode multiple adaptive loop filter sets in an adaptation parameter set associated with the video data. A video decoder may receive the multiple adaptive loop filter sets in the adaptation parameter set associated with video data, determine one or more adaptive loop filters from the multiple adaptive loop filter sets, and apply the determined one or more adaptive loop filters to the video data.

Abstract: An example device for filtering a decoded block of video data includes one or more processing units configured to construct filters for classes of blocks of a current picture of video data. To construct filters for each of the classes, the processing units are configured to determine a value of a flag that indicates whether a fixed filter is used to predict a set of filter coefficients of the class, and in response to the fixed filter being used to predict the set of filter coefficients, determine an index value into a set of fixed filters and predict the set of filter coefficients of the class using a fixed filter of the set of fixed filters identified by the index value.

Abstract: A video encoder and video decoder are configured to perform a neural network (NN)-based filter process on reconstructed blocks of video data. In one example, the NN-based filter process uses reconstruction samples of the block, prediction samples of the block, and supplementary data related to the block as inputs. The NN-based filter process includes an initial processing of one or more types of the supplementary data with fewer computations relative to the initial processing of the reconstruction samples and the prediction samples.

Abstract: A video coder is configured to perform a neural network (NN)-based filter process on reconstructed blocks of vide data. In one example, a video coder may receive a picture of video data, and reconstruct a block of the picture of video data to generate a reconstructed block. The video coder may perform the NN-based filter process on the reconstructed block to generate a filtered block, wherein the NN-based filter process includes performing a plurality separable convolutions to approximate a multi-dimensional convolution.

Abstract: An method of decoding video data includes deriving, for a current block of video data and using decoder side intra mode derivation (DIMD), a list of intra modes using reconstructed samples of neighboring blocks; constructing, for the current block, a most probable mode (MPM) list, wherein constructing the MPM list comprises inserting, into the MPM list, at least one intra mode from the derived list of intra modes; and predicting, using a candidate selected from the constructed MPM list, the current block.

Abstract: A method of decoding video data includes determining a plurality of hypotheses of a current block based on a plurality of motion vectors. Each of the plurality of motion vectors is associated with one of the plurality of hypotheses, and each of the plurality of hypotheses is based on a set of samples in a reference picture having a motion vector that identifies a top-left sample of the set of samples. The method includes determining one or more neighboring samples in the same picture as the current block, for each of the plurality of hypotheses, determining respective correlation values between at least one sample of a respective hypothesis and at least one sample of the one or more neighboring samples, determining the motion vector for the current block based on the determined respective correlation values, and reconstructing the current block based on the determined motion vector.

Abstract: A video encoder or video decoder are configured to reconstruct the video data to generate reconstructed video data. The video encoder or video decoder may further perform a plurality of loop filter operations on the reconstructed video data in parallel, wherein the plurality of loop filter operations includes a first filter operation that is not a bilateral filter operation or a sample adaptive offset (SAO) filter operation, and perform a joint clipping operation on a first output of the first filter and a second output of a second loop filter operation of the plurality of loop filter operations. The first filter operation may be a cross-component sample adaptive offset (CCSAO) filter operation.

Abstract: Techniques are described for using an inter-intra-prediction block. A video coder may generate a first prediction block according to an intra-prediction mode and generate a second prediction block according to an inter-prediction mode. The video coder may weighted combine, such as based on the intra-prediction mode, the two prediction blocks to generate an inter-intra-prediction block (e.g., final prediction block). In some examples, an inter-intra candidate is identified in a list of candidate motion vector predictors, and an inter-intra-prediction block is used based on identification of the inter-intra candidate in the list of candidate motion vector predictors.

Abstract: 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.

Abstract: A method of decoding video data, including receiving a first block of video data encoded using an inter-prediction mode associating a first intra-prediction mode with the first block of video data, wherein the first intra-prediction mode is associated with a second block of video data, and determining a second intra-prediction mode for a neighbor block of video data based at least in part on the first intra-prediction mode.

Abstract: A video decoder can be configured to determine that a current block of the video data is coded in a bi-prediction inter mode; receive a first syntax element identifying a motion vector predictor from a first candidate list of motion vector predictors; receive a second syntax element identifying a motion vector difference; determine a first motion vector for the current block based on the motion vector predictor and the motion vector difference; determine a second motion vector for the current block from a second list of candidate motion vector predictors based on bilateral matching; and determine a prediction block for the current block using the first motion vector and the second motion vector.

Abstract: A device may perform a first prediction process for a first block of video data to produce a first residual. The device may apply a first transform process to the first residual to generate first transform coefficients for the first block of video data and encode the first transform coefficients. The device may perform a second prediction process for a second block of video data to produce a second residual. The device may determine that a second transform process, which includes the first transform process and at least one of a pre-adjustment operation or a post-adjustment operation, is to be applied to the second residual. The device may apply the first transform process and the pre- or post-adjustment operation to the second residual to generate second transform coefficients for the second block. The coding device may code the first and second transform coefficients.

Abstract: 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.

Abstract: An example device for filtering decoded video data includes a memory configured to store video data; and one or more processors implemented in circuitry and configured to: decode a picture of video data; code a value for a syntax element representing a neural network model to be used to filter a portion of the decoded picture, the value representing an index into a set of pre-defined neural network models, the index corresponding to the neural network model in the set of pre-defined neural network models; and filter the portion of the decoded picture using the neural network model corresponding to the index.

Abstract: Example devices, systems, and techniques are described. An example technique includes determining that resampling is to be applied to a first reference frame for a slice of point cloud data or a frame of the point cloud data. The technique includes applying resampling to the first reference frame to generate a resampled reference frame. The technique includes determining one or more inter prediction candidates based on the resampled reference frame. The technique includes processing the slice of the point cloud data or the frame of the point cloud data based on the one or more inter prediction candidates.

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.