Apple Inc.

Dolby Laboratories Licensing Corporation

Thomson Licensing

Microsoft Technology Licensing, LLC

Guangdong Oppo Mobile Telecommunications Corp., Ltd.

Fastvdo LLC

Ntt Docomo, Inc.

Maxim Integrated Products, Inc.

Integrated Device Technology, Inc.

Interdigital Vc Holdings, Inc.

Geo Semiconductor Inc.

Magnum Semiconductor, Inc.

Dolby Laboratories Licensing Coporation

Alexandros Michael Tourapis

Athanasios Leontaris

Khaled Mammou

Yeping Su

Jungsun Kim

David William Singer

Fabrice A Robinet

Peshala Vishvajith Pahalawatta

Hsi-Jung Wu

Walter J Husak

Valery G Valentin

Jill MacDonald Boyce

Kevin J Stec

Peng Yin

Guy Cote

Krishnakanth Rapaka

Jun Xin

David Ruhoff

Yan Ye

Yuwen He

David Flynn

Yunfei Zheng

Yeqing Wu

Xiaosong Zhou

Mei Guo

Hye-Yeon Cheong

Hilmi Enes Egilmez

Dominik Mehlem

Yixin Du

Dazhong Zhang

Jeffrey Allen Cooper

Shipeng Li

Feng Wu

Jiefu Zhai

Jae Hoon Kim

Hang Yuan

Ming Chen

Xiaohua Yang

Gary Joseph Sullivan

Jim Chen Chou

Steven E Saunders

Joan Llach

Krasimir D Kolarov

Pankaj N Topiwala

Zhen Li

Andrea Cremaschi

Jill Macdonald Boyce

Xiaoan Lu

Cristina Gomila

Haitao Guo

Sorin Constantin Cismas

Albert E Keinath

Lulin Chen

Guoxin Jin

Frank Bossen

Deepak S Tolani

Zhenzhen Gao

Marius Preda

Dimitri Podborski

Guichun Li

Timothy John Millet

Lowell Leroy Winger

Arash Vosoughi

Kenneth I Greenebaum

Alican Nalci

José Roberto Alvarez

Jose Roberto Alvarez

Jaehong Chon

Zhifeng Chen

Fanyi Duanmu

Linfeng Guo

Xingyu Zhang

Krzysztof Hebel

Michael Willis Milne, Jr

Van Luong Pham

Dzung T Hoang

Jean Begaint

Walt J Husak

Jingteng Xue

Sean Fitzpatrick

Liviu Traian Christian Tulvan

Daniel Joseph Bell

Limin Lu

Chao Cao

Jill Mac Boyce

Jill Mac Donald Boyce

An encoder or decoder can perform enhanced motion vector prediction by receiving an input block of data for encoding or decoding and accessing stored motion information for at least one other block of data. Based on the stored motion information, the encoder or decoder can generate a list of one or more motion vector predictor candidates for the input block in accordance with an adaptive list construction order. The encoder or decoder can predict a motion vector for the input block based on at least one of the one or more motion vector predictor candidates.

Enhanced motion vector prediction

A system comprises an encoder configured to compress attribute information and/or spatial for a point cloud and/or a decoder configured to decompress compressed attribute and/or spatial information for the point cloud. To compress the attribute and/or spatial information, the encoder is configured to convert a point cloud into an image based representation. Also, the decoder is configured to generate a decompressed point cloud based on an image based representation of a point cloud. Additionally, an encoder is configured to signal and/or a decoder is configured to receive a supplementary message comprising volumetric tiling information that maps portions of 2D image representations to objects in the point. In some embodiments, characteristics of the object may additionally be signaled using the supplementary message or additional supplementary messages.

Point cloud compression with supplemental information messages

A system comprises an encoder configured to compress attribute information and/or spatial information for a point cloud and/or a decoder configured to decompress compressed attribute and/or spatial information for the point cloud. To compress the attribute and/or spatial information, the encoder is configured to convert a point cloud into an image based representation. Also, the decoder is configured to generate a decompressed point cloud based on an image based representation of a point cloud. In some embodiments, a bit stream structure may be used to communicate compressed point cloud data. The bit stream structure may include point cloud compression network abstraction layer (PCCNAL) units that enable use of groups of frames (GOFs), frame, and sub-frame signaling of patch information. Such a bit stream structure may permit low delay streaming and random access reconstruction of point clouds amongst other applications.

Bit stream structure for compressed point cloud data

Techniques are proposed to improve temporal motion projection in video coding. Candidate reference frames available for use in temporal motion projection are sorted in processing order according to scores assigned based on estimates of the reference frames' suitability for prediction. Such estimates may be based on temporal distance between each candidate reference frame and that reference frame's prediction references. Estimates may be based, for each reference frame, based on an estimate of coding quality of a reference frame from which the respective candidate reference frame makes a prediction reference. Once sorted, the candidate reference frames may be processing in the sorting order to supply prediction data to a current frame that is to be coded from the candidate reference frames. Additionally, hardware friendly designs of motion field hole filling and motion vector smoothing operations are proposed. Such designs can reduce hardware implementation complexity and benefit hardware parallel processing in several aspects: by removing the dependency among different processing block rows for hole filling and motion vector smoothing so that it is becomes easier and friendlier to achieve hardware parallel processing; by reducing the hardware bandwidth loading overhead; by improving hardware pipeline throughput; and/or by avoiding adding a line buffer to store the data from the above row since a line buffer will increase hardware cost.

Hardware friendly design for motion field processing and quality improvement of motion field

Improved neural-network-based image and video coding techniques are presented, including hybrid techniques that include both tools of a host codec and neural-network-based tools. In these improved techniques, the host coding tools may include conventional video coding standards such H.266 (VVC). In an aspects, source frames may be partitioned and either host or neural-network-based tools may be selected per partition. Coding parameter decisions for a partition may be constrained based on the partitioning and coding tool selection. Rate control for host and neural network tools may be combined. Multi-stage processing of neural network output may use a checkerboard prediction pattern.

Hybrid neural network based end-to-end image and video coding method

Techniques for encoding video with motion compensation include a compressed bitstream syntax that includes a list of all motion prediction reference frames without distinguishing between short-term reference frame and long-term reference frames. The list of reference frames may be provided in a slice header and may apply to encoded data video data within the corresponding slice. The list may be prefaced with a single number indicating the total number of reference frames. In an aspect delta POC reference numbers may be encoded with a flag indicating the sign of the delta POC when the absolute value of the POC is not equal to zero. In another aspect, a flag may be encoded for every reference frame indicating if POC information should be used when scaling prediction references, and a weighting parameter may be included when POC information should be used.

Reference picture management and list construction

A system compresses and decompresses attribute information for visual volumetric content, such as a mesh representation. Attribute values are included in the visual volumetric representation, wherein at least some of the attribute values include unitary vectors, such as surface normal vectors or surface tangent vectors having a magnitude of one unit. In order to compress the attribute information the three-dimensional unit vectors are mapped into two dimensional parametric coordinates for a planar representation of a unit sphere. To reduce negative effects on compression due to distortion or discontinuities in the planar representation, mappings for compressing respective unit vectors are adaptively selected.

Compression of attribute values comprising unit vectors

Low complexity, hardware-friendly techniques are proposed for video coding systems to mitigate banding artifacts while maintaining the compression efficiency. In general, the proposed techniques consist of two stages including a banding detection stage and a de-banding stage. The banding detection stage may identify the image/video regions where the banding artifact may be present based on gradient information and other information. The de-banding stage may apply corrective techniques to regions identified as likely to possess banding artifacts. In one embodiment, the de-banding adapts the filtering logic proposed by prior video coding standards for other filtering applications to mitigate banding. When implemented over the AV1 video coding standard and the AOM Video Model (AVM) reference software, the proposed technique improves subjective quality significantly at a reasonable hardware implementation cost. The methods and embodiments presented in this document can be beneficial find application in a wide variety of image/video coding standards and systems.

Techniques for contouring/banding artifact removal in compressed image/video

Techniques are described for express and implied signaling of transform mode selections in video coding. Information derived from coefficient samples in a given transform unit (TU) or prediction unit (PU) may constrain or modify signaling of certain syntax elements at the coding block (CB), TU, or PU levels. For instance, based on the spatial locations of decoded coefficients, the spatial patterns of coefficients, or the correlation with the coefficients in neighboring blocks, various syntax elements such as the transform type and related flags/indices or secondary transform modes/flags indices, a residual coding mode, intra and inter prediction modes, and scanning order may be disabled or constrained. In another case, if the coefficient samples match a desired spatial pattern or have other desired properties then a default transform type, a default secondary transform type, a default intra and inter prediction mode or other block level modes may be inferred at the decoder side. Similar ideas may be extended to infer intra-block copy (IBC) flags/modes/indices from coefficient samples, or to infer flags and modes related to predictive coding techniques such as block-wise differential pulse code modulation (BDPCM), i.e., horizontal and vertical BDPCM modes, palette mode syntax and other block level flags/indices.

Coefficient-based transform and mode signaling

A system comprises an encoder configured to compress and encode data for a three-dimensional mesh. To compress the three-dimensional mesh, the encoder determines a compressed base mesh bit stream and a compressed motion bitstream. A network abstraction layer syntax defined for the compressed base mesh bit stream and the compressed motion bitstream, allows for various parameters to be defined and applied to both bit streams, such as timing information and faceIDs for faces of polygons of the mesh.

Base mesh data and motion information sub-stream format for video-based dynamic mesh compression

In an example method, a decoder obtains a data stream representing video content. The video content is partitioned into one or more logical units, and each of the logical units is partitioned into one or more respective logical sub-units. The decoder determines that the data stream includes first data indicating that a first logical unit has been encoded according to a flexible skip coding scheme. In response, the decoder determines a first set of decoding parameters based on the first data, and decodes each of the logical sub-units of the first logical unit according to the first set of decoding parameters.

Encoding and decoding video content using prediction-aware flexible skip coding

A method of compressing a 3D textured mesh M(i), the 3D textured mesh being defined by connectivity C(i), geometry G(i), texture coordinates T(i), and texture connectivity CT(i), wherein the mesh is associated with one or more 2D image attribute maps A(i) describing attributes associated with the mesh surface, can include pre-processing 3D textured mesh M(i) and attribute maps A(i) to generate a base mesh m(i) and displacement field d(i); and processing 3D textured mesh M(i), attribute maps A(i), base mesh m(i), and the displacement field d(i) to generate a compressed bitstream b(i).

Image/video-based mesh compression

A three-dimensional (3D) mesh encoder is provided. The 3D mesh encoder can include a pre-processing stage configured to generate the mesh M by re-sampling the mesh M and computing a new atlas of parametrization with a fewer number of patches and relatively lower parameterization distortion. The 3D mesh encoder may include an attribute transfer stage for transferring attributes to the re-sampled mesh M.

Attribute transfer for efficient dynamic mesh coding

A video dynamic mesh coding (v-DMC) decoding system, includes a de-multiplexer that receives and demultiplexes an encoded v-DMC bitstream into: a parameter set and mesh data, geometry, atlas data, and attribute video substreams. The decoding system also includes: a mesh data substream decoder; a video decoder that decodes the geometry data substream; an atlas data substream decoder; a mesh subdivision component that subdivides the one or more base meshes into one or more resampled base meshes based upon the decoded atlas data; a displacement decoder that outputs one or more displacements to verticies of the one or more resampled base meshes; a mesh position refinement component that applies the one or more displacements to the one or more resampled base meshes and outputs one or more resultant meshes; and a video decoder that decodes the attribute video substream into one or more texture images.

V-mesh bitstream structure including syntax elements and decoding process with reconstruction

Embodiments feature families of rate allocation and rate control methods that utilize advanced processing of past and future frame/field picture statistics and are designed to operate with one or more coding passes. At least two method families include: a family of methods for a rate allocation with picture look-ahead; and a family of methods for average bit rate (ABR) control methods. At least two other methods for each method family are described. For the first family of methods, some methods may involve intra rate control. For the second family of methods, some methods may involve high complexity ABR control and/or low complexity ABR control. These and other embodiments can involve any of the following: spatial coding parameter adaptation, coding prediction, complexity processing, complexity estimation, complexity filtering, bit rate considerations, quality considerations, coding parameter allocation, and/or hierarchical prediction structures, among others.

Video compression and transmission techniques

Growing community of inventors

West Windsor, NJ, United States of America

Alexandros Michael Tourapis