Interdigital Vc Holdings, Inc.

Interdigital Madison Patent Holdings, Sas

Interdigital Ce Patent Holdings, Sas

Interdigital Patent Holdings, Inc.

Thomson Licensing

Fabrice Leleannec

Tangi Poirier

Franck Galpin

Fabrice Urban

Edouard Francois

Antoine Robert

Ya Chen

Philippe Bordes

Fabien Racape

Dominique Thoreau

Sebastien Lasserre

Gagan Bihari Rath

Yannick Olivier

David Touze

Philippe De Lagrange

Pierre Andrivon

Patrick Lopez

Karam Naser

Thierry Viellard

Michel Kerdranvat

Catherine Serre

Sunil Jaiswal

Simon Danten

Sébastien Lasserre

Piere Andrivon

Christine Guillemot

Ronan Boitatd

Sebastien Lassere

Mikaël Le Pendu

When dependent scalar quantization is used, the choice of the quantizer depends on the decoding of the preceding transform coefficient, and the entropy decoding of a transform coefficient depends on quantizer choice. To maintain high throughput in hardware implementations for transform coefficient entropy coding, several decision schemes of the scaler quantizer are proposed. In one implementation, the state transition and the context model selection are based on only regular coded bins. For example, the state transition can be based on the sum of the SIG, gt1 and gt2 flags, the exclusive-or function of the SIG, gt1 and gt2 flags, or based on only the gt1 or gt2 flag. When a block of transform coefficients is coded, the regular mode bins can be coded first in one or more scan passes, and the remaining bypass coded bins are grouped together in another one or more scan passes.

Scalar quantizer decision scheme for dependent scalar quantization

Implementations are described for determining, for a block being encoded in a picture, at least one predictor candidate, determining for the at least one predictor candidate, one or more corresponding control point generator motion vectors, based on motion information associated to the at least one predictor candidate, determining for the block being encoded, one or more corresponding control point motion vectors, based on the one or more corresponding control point generator motion vectors determined for the at least one predictor candidate, determining, based on the one or more corresponding control point motion vectors determined for the block, a corresponding motion field, and encoding the block based on the corresponding motion field.

Methods and apparatuses for video encoding and video decoding

A video coding system uses a value of a chroma quantization parameter table to quantize or de-quantize chroma values of a block of the video, the chroma quantization parameter table being directly coded in a set of parameters at the picture level or at the sequence level of the coded video stream. A corresponding encoding method, encoding device, decoding method, decoding device, and non-transitory readable medium are proposed.

Chroma quantization parameter adjustment in video encoding and decoding

A decoding method for decoding a block of an image is disclosed that comprises: determining a split mode for said block in a set of split modes; splitting said block into at least two sub-blocks responsive to said split mode; decoding each of the at least two sub-blocks; wherein said set of split modes comprises at least one split mode for asymmetrically splitting said block into the at least two sub-blocks.

Encoding and decoding methods and corresponding devices

Different implementations are described, particularly implementations for determining a set of predictor candidates for affine merge coding mode from neighboring blocks for motion compensation of a picture block based on a motion model. The motion model, may be, e.g., an affine model in a merge mode or AMVP mode for a video content encoder or decoder. The motion model, may be, e.g., an affine model based on top-left/top-right control point motion vectors or an affine model based on top-left/bottom-left control point motion vectors. Such affine model may be signaled by a flag. In an embodiment, predictor candidates are sorted in the set based on a criterion such as, e.g., a validity check or a vectors coherence cost. In an embodiment, a predictor candidate is selected from the set based on a motion model for each of the multiple predictor candidates, and may be based on a criterion such as, e.g., a rate distortion cost. The corresponding motion field is determined based on, e.g., one or more corresponding control point motion vectors for the block being encoded or decoded. The corresponding motion field of an embodiment identifies motion vectors used for prediction of sub-blocks of the block being encoded or decoded.

Predictor candidates for motion compensation

A decoding method is disclosed that comprises: determining whether a current block of a picture extends beyond a boundary of the picture; determining for each split mode of a plurality of split modes whether said current block is allowed to undergo splitting according to said split mode by checking whether at least one of the split line is co-located with one of the picture border or whether the size of the block part inside the picture along the picture boundary is a multiple of a minimum block size; decoding from a bitstream a current split mode of the current block responsive to the allowed split modes; and decoding the current block according to the current split mode.

Methods and apparatus for picture encoding and decoding

A decoding method is disclosed. First, context for a syntax element associated with a current transform coefficient of a block of a picture is determined. The context is determined based on the area of said block, on the position of the current transform coefficient within the block and on the number of non-zero neighboring transform coefficients in a local template. Second, the syntax element is decoded based at least on the determined context. Advantageously, the local template depends on the shape of said block.

An encoding method is disclosed. At least one context is first determined for encoding a syntax element associated with a block of a picture responsive to a current quantization parameter associated with the block. Second, the syntax element is context-based entropy encoded with the at least one determined context.

Context-based binary arithmetic encoding and decoding

A block of video data is split using one or more of several possible partition operations by using the partitioning choices obtained through use of a deep learning-based image partitioning. In at least one embodiment, the block is split in one or more splitting operations using a convolutional neural network. In another embodiment, inputs to the convolutional neural network come from pixels along the block's causal borders. In another embodiment, boundary information, such as the location of partitions in spatially neighboring blocks, is used by the convolutional neural network. Methods, apparatus, and signal embodiments are provided for encoding.

Deep learning based image partitioning for video compression

The present principles relate to a method and device. A method for encoding a residual block comprises: obtaining () a first coding mode relative to a first 2D transform when coding the residual blocks according to a coding mode relative to a first 2D transform is enabled; obtaining () a second coding mode relative to a second 2D transform when coding the residual blocks according to a coding mode relative to a second 2D transform is enabled; and encoding () the residual block according to either said first coding mode or said second coding mode or both; the method is characterized in that enabling or disabling () the coding of the residual block according to said second coding mode depends on said first coding mode. The present principles relate also to a method and device for encoding/decoding a picture.

Method and apparatus for selecting a coding mode used for encoding/decoding a residual block

A method for reconstructing a picture block is disclosed, wherein the block is predicted using local illumination compensation. The parameters of local illumination compensation are determined according to a selection of reconstructed samples located to the left and above of the current block. In the case where some of them are unavailable, they may be replaced using different techniques.

Method and device for picture encoding and decoding using illumination compensation

The present principles relates to a method for encoding an image unit comprising image data represented by a luminance channel and at least one chrominance channel, the method comprising obtaining a luma coding-tree by splitting a luminance unit representative of the luminance channel of said image unit and obtaining a chroma coding-tree by splitting a chrominance unit representative of at least one chrominance channel of said image unit. The method is characterized in that obtaining said chroma coding-tree comprises: determining whether said chroma coding-tree and said luma coding-tree are identical; and signaling an information data indicating whether said chroma coding-tree and said luma coding-tree are identical.

Method and device for encoding/decoding an image unit comprising image data represented by a luminance channel and at least one chrominance channel

A cross-component dependent tool to be used for a chroma block of a picture is enabled responsive to a size of said chroma block and to a size of at least one luma block co-located with the chroma block. Then, the chroma block is decoded responsive to said enablement of said cross-component dependent tool. A encoding and decoding methods are presented as well as encoding and decoding devices.

Method and device for picture encoding and decoding

PROF (Prediction Refinement with Optical Flow) and BDOF (Bi-directional Optical Flow) use the optical flow model to provide sample-wise motion compensation refinement. In one implementation, to calculate the spatial gradients in BDOF, an extended region is generated around a block to be coded. To simplify the computation, BDOF may use the same padding operations as in PROF, namely, a padding sample is copied from the nearest integer neighbor in the reference picture. BDOF and PROF can also be used together when sub-block based affine motion-compensated prediction is used. BDOF can be applied after PROF generates new prediction blocks, or BDOF can use the spatial gradients in the original prediction blocks to re-use the computations with PROF. In addition, BDOF and PROF operations can be combined, and the prediction adjustment will be directly based on the spatial gradients in the original prediction blocks.

Bi-prediction refinement in affine with optical flow

Different quantization matrices may be transmitted corresponding to different block sizes, color components and prediction modes. To more efficiently signal the coefficients of the quantization matrices, in one implementation, a unified matrix identifier matrixId is used, based on a size identifier (sizeId) that relates to CU size with larger sizes listed first, and a matrix type (matrixTypeId) with luma QMs listed first. For example, the unified identifier is derived as: matrixId=N*sizeId+matrixTypeId, where N is the number of possible type identifiers, e.g., N=6. This single identifier allows referring to any previously transmitted matrix when using prediction (copy), and transmitting larger matrices first avoids interpolation in the prediction process. When a block uses the Intra Block Copy prediction mode, QM identifier may be derived as if the block uses the INTER prediction mode.

Growing community of inventors

Mouazé, France

Fabrice Leleannec