Qualcomm Incorporated

Nokia Corporation

Nokia Mobile Phones Limited

Velos Media, LLC

Shumaker & Sieffert, P.a.

Other

Nokia Technologies Oy

Velos Media International Limited

Marta Karczewicz

Vadim Seregin

Wei-Jung Chien

Jianle Chen

Li Feng Zhang

Geert Van Der Auwera

Rajan Laxman Joshi

Joel Sole Rojals

Muhammed Zeyd Coban

Adarsh Krishnan Ramasubramonian

Ying Hai Chen

Xianglin Wang

Xiang Yang Li

Han Huang

Xin Zhao

Peisong Chen

Bappaditya Ray

Dmytro Rusanovskyy

Liwei Guo

Krishnakanth Rapaka

Nan Hu

Wei Pu

Yan Ye

Luong Pham Van

Amir Said

In Suk Chong

Hilmi Enes Egilmez

Kai Zhang

Hsiao-Chiang Chuang

Chun-Chi Chen

Yi-Wen Chen

Cheng-Teh Hsieh

Hongtao Wang

Ye-Kui Wang

Feng Zou

Yunfei Zheng

Chao Pang

Yao-Jen Chang

Sungwon Lee

Yung-Hsuan Chao

Louis Joseph Kerofsky

Yu Han

Yan Zhang

Done Bugdayci Sansli

Yu-Chen Sun

Hongbin Liu

Woo-Shik Kim

Zhi Zhang

Alican Nalci

Chengjie Tu

Jani Lainema

Vijayaraghavan Thirumalai

Rahul P Panchal

Kevin Pascal Andre Reuze

Jie Dong

Yuriy Reznik

Yong He

Yang Yu

Bogdan-Paul Dobrin

Fnu Hendry

Ossi Kalevo

Chao-Hsiung Hung

Hyukjune Chung

Jewon Kang

Jaehong Chon

Ragip Kurceren

Rong Zhang

Venkata Meher Satchit Anand Kotra

Keming Cao

Xiang Li

Anand Meher Kotra

Giovanni Motta

Sanjeev Kumar

Justin Ridge

Akshay Gadde

Thibaud Laurent Biatek

Ankitesh Kumar Singh

Yiliang L Bao

Antti Hallapuro

Yong Wang

Nikolai Konrad Leung

Kai Wang

Shu Xiao

Auke Joris Wiggers

Jacek Nieweglowski

Emre Baris Aksu

Tao Wang

Natan Jacobson

Andrew Edmund Turner

Phoom Sagetong

Seyfullah Halit Oguz

Po-Han Lin

Yekui Wang

Amit Rohatgi

Prasanjit Panda

Viktor Varsa

Guoxin Jin

A method of decoding video data includes determining a vector predictor for a current block; determining a first set of vector difference candidates based on a first pel-interval, the first pel-interval defining a first distance between consecutive vector difference candidates in the first set of vector difference candidates starting with the vector predictor; determining a second set of vector difference candidates based on the first set of vector difference candidates and a second pel-interval, the second pel-interval defining a second distance between consecutive vector difference candidates in the second set of vector difference candidates; constructing a vector difference candidate list based on the second set of vector difference candidates; determining a vector for the current block based on the vector predictor and a vector difference from the vector difference candidate list; and reconstructing the current block based on the vector for the current block.

Vector difference candidate list construction

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

An example device for filtering a decoded block of video data includes one or more processing units configured to construct a plurality of filters for classes of blocks of a current picture of video data. To construct the plurality of 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.

Predicting filter coefficients from fixed filters for video coding

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.

Reusing adaptive loop filter (ALF) sub-picture boundary processing for raster-scan slice boundaries

A method of encoding or decoding video data includes determining that geometric partition mode is enabled for a current block of the video data, the geometric partition mode comprising a plurality of split modes that each defines an edge for partitioning; for each split mode among at least two of the plurality of split modes, determining a respective cost associated with a respective split mode; constructing, based on the respective costs associated with the respective split modes, a mapping list including index values respectively associated with values indicative of the respective split modes, where a lower index value is associated with a first split mode having a lower cost than a second split mode with a higher index value; determining a split mode amongst the plurality of split modes within the mapping list; and reconstructing a current block of the video data based on the split mode.

Geometric partition mode in video coding

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: decode a current block of the video data to form a decoded block; determine that a current sample of the decoded block neighbors a sample along a virtual boundary in the decoded block and neighbors one or more samples that are not along any virtual boundary in the decoded block; compute band information for cross component sample adaptive offset (CCSAO) for the current sample using at least one of the one or more samples that are not along any virtual boundary in the decoded block and without using the sample along the virtual boundary; and perform CCSAO on the current sample using the band information.

Virtual boundary processing for CCSAO, bilateral filter and adaptive loop filter for video coding

A device for decoding video data receives a picture of video data; reconstructs a block of the picture of video data to generate a reconstructed block; applies a neural network (NN)-based filter process to the reconstructed block to generate a filtered block, wherein the NN-based filter process includes a first backbone block process followed by a second backbone block process, wherein the first backbone block process comprises a first M×N convolution followed by a first N×M convolution, and the second backbone block process comprises a second N×M convolution followed by a second M×N convolution, wherein N and M are different integer values; determines a decoded block of video data based on the filtered block; and outputs a decoded version of the picture, wherein the decoded version of the picture comprises the decoded block of video data.

NN-based in loop filter architectures with separable convolution and switching order of decomposition

An example device for decoding video data includes a memory configured to store video data; and a processing system including one or more processors implemented in circuitry, the processing system being configured to: determine that a previously coded block of video data was coded using uni-prediction mode for which a bi-prediction syntax element is not assigned a value; determine that a current block of the video data is to be coded using a bi-prediction mode and that motion information of the current block is to be predicted from the previously coded block, including from the bi-prediction syntax element of the previously coded block; and in response to the bi-prediction syntax element of the previously coded block not having an assigned value, decode the current block using a substitute value for the bi-prediction syntax element.

Using substitute motion information when coding video data

A G-PCC coder may determine an occupancy of a reference child node in a reference node, wherein the reference node is in a reference frame of point cloud data used for inter prediction of a current node in a current frame of the point cloud data. The G-PCC coder may further determine a context for decoding a current occupancy bit of a current child node of the current node based on the occupancy of the reference child node, and arithmetic decode the current occupancy bit using the context.

Occupancy coding using inter prediction with octree occupancy coding based on dynamic optimal binary coder with update on the fly (OBUF) in geometry-based point cloud compression

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

An example device for coding point cloud data includes a memory configured to store point cloud data; and one or more processors implemented in circuitry and configured to: determine at least one of 1) that a node of an octree of the point cloud data is not inter predictable or 2) that angular mode is enabled for the node; in response to determining the at least one of 1) that the node is not inter predictable or 2) that angular mode is enabled for the node, determine an inferred direct coding mode (IDCM) mode for the node; and code occupancy data of the node using the determined IDCM mode.

Coding point cloud data using direct mode for inter-prediction in G-PCC

A device for encoding or decoding point cloud data may be configured to, responsive to determining to predict a current point in a current frame using an inter prediction mode: identify a reference frame; derive one or more motion compensated reference points from the reference frame; selectively resample points in the reference frame based on the one or more motion compensated reference points to generate a resampled reference frame; and inter predict the current point in the current frame based on the resampled reference frame.

Inter prediction coding for geometry point cloud compression

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.

Methods of subblock skipping for affine motion search for video coding

An example device for decoding video data includes one or more processors configured to: determine that a first weight and a second weight are specified for a bi-prediction mode predicted current block of video data; determine whether the current block is to be predicted using multi-hypothesis prediction (MHP) mode with the bi-prediction mode as a base mode; in response to determining that the current block is to be predicted using the MHP mode with the bi-prediction mode as the base mode, determine an additional inter-prediction mode of the MHP mode; generate a first prediction block according to the bi-prediction mode; generate a second prediction block according to the additional inter-prediction mode; generate a final prediction block for the current block according to the MHP mode using the first prediction block and the second prediction block; and decode the current block using the final prediction block.

Multiple hypothesis prediction for video coding

An example device for filtering 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: apply one or more neural network processing blocks to intermediate filtered video data, each of the neural network processing blocks including a first 1×1 convolutional filter, a parametric rectified linear unit (PReLU) filter, a second 1×1 convolutional filter, and a 3×3 convolutional filter; apply additional neural network processing blocks to output of the one or more neural network processing blocks to form filtered video data; and output the filtered video data.

Reduced complexity multi-mode neural network filtering of video data

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Marta Karczewicz