Video coding using a constructed reference frame may include generating, by a processor in response to instructions stored on a non-transitory computer readable medium, an encoded video and outputting an output bitstream. Generating the encoded video includes receiving an input video stream, generating a constructed reference frame, generating an encoded constructed reference frame by encoding the constructed reference frame, including the encoded constructed reference frame in an output bitstream such that the constructed reference frame is a non-showable frame, generating an encoded frame by encoding a current frame from the input video stream using the constructed reference frame as a reference frame, and including the encoded frame in the output bitstream.

An image encoding method including: a constraint information generating step of generating tile constraint information indicating whether or not there is a constraint in filtering on boundaries between adjacent tiles among a plurality of tiles obtained by dividing a picture, and storing the tile constraint information into a sequence parameter set; and a filter information generating step of generating, for each of the boundaries, one of a plurality of filter information items respectively indicating whether or not filtering is executed on the boundaries, and storing the plurality of filter information items into a plurality of picture parameter sets, wherein, in the filter information generating step, the plurality of filter information items which indicate identical content are generated when the tile constraint information indicates that there is the constraint in the filtering.

An image encoding method including: a constraint information generating step of generating tile constraint information indicating whether or not there is a constraint in filtering on boundaries between adjacent tiles among a plurality of tiles obtained by dividing a picture, and storing the tile constraint information into a sequence parameter set; and a filter information generating step of generating, for each of the boundaries, one of a plurality of filter information items respectively indicating whether or not filtering is executed on the boundaries, and storing the plurality of filter information items into a plurality of picture parameter sets, wherein, in the filter information generating step, the plurality of filter information items which indicate identical content are generated when the tile constraint information indicates that there is the constraint in the filtering.

An apparatus to facilitate real-time playback of point cloud sequence data is disclosed. The apparatus comprises one or more processors to receive point cloud data of a captured scene, decompose the point cloud data into a plurality of point cloud patches, wherein each point cloud patch is associated with an object in the scene and includes contextual information regarding the point cloud patch, encode each of the point cloud patches via a deep-learning based algorithm to generate encoded point cloud patches, receive a viewpoint selection from a client, assign a priority to data chunks within each encoded point cloud patch based on the viewpoint selection and the contextual information and transmit the data chunks to the client based on the assigned priority.

An encoder may segment volumetric video data into one or more regions; determine at least one radiative transfer property of the one or more regions; indicate the at least one radiative transfer property of the one or more regions in a sub-stream; and include the sub-stream in a bitstream configured to describe the volumetric video data. A decoder may receive a bitstream describing volumetric video data; extract a sub-stream from the received bitstream; determine whether the extracted sub-stream comprises at least one radiative transfer property for a region of the volumetric video data; based on a determination that the extracted sub-stream comprises the at least one radiative transfer property for the region, determine a value for the at least one radiative transfer property for the region; and render the region based on the determined value for the at least one radiative transfer property.

Aspects of the disclosure provide methods and apparatuses for neural network processing, such as in video processing. In some examples, an apparatus for neural network processing includes processing circuitry. The processing circuitry determines that an input for a convolution operation includes a first input channel that is piecewise constant. Then, the processing circuitry calculates a first intermediate output channel based on other channels of the input for the convolution operation; and then generates an output of the convolution operation based on a combination (e.g., a linear combination) of the first intermediate output channel and the first input channel.

An image coding method includes selecting two or more transform components from among a plurality of transform components that include a translation component and non-translation components, the two or more transform components serving as reference information that represents a reference destination of a current block; coding selection information that identifies the two or more transform components that have been selected from among the plurality of transform components; and coding the reference information of the current block by using reference information of a coded block different from the current block.

An image coding method includes selecting two or more transform components from among a plurality of transform components that include a translation component and non-translation components, the two or more transform components serving as reference information that represents a reference destination of a current block; coding selection information that identifies the two or more transform components that have been selected from among the plurality of transform components; and coding the reference information of the current block by using reference information of a coded block different from the current block.

A Scalable Video Coding (SVC) process for scalable video coding takes into account color gamut primaries along with spatial resolution. The process for re-sampling uses video color data obtained from an encoder or decoder process of a base layer (BL) in a multi-layer system to enable improved encoding and decoding in an enhancement layer (EL) or higher layers taking into account color conversion between layers. Examples of applicable SVC include MPEG-4 and High Efficiency Video Coding (HEVC). With the SVC process, video data expressed in one color gamut space can be used for prediction in encoding with a different color space.

A Scalable Video Coding (SVC) process for scalable video coding takes into account color gamut primaries along with spatial resolution. The process for re-sampling uses video color data obtained from an encoder or decoder process of a base layer (BL) in a multi-layer system to enable improved encoding and decoding in an enhancement layer (EL) or higher layers taking into account color conversion between layers. Examples of applicable SVC include MPEG-4 and High Efficiency Video Coding (HEVC). With the SVC process, video data expressed in one color gamut space can be used for prediction in encoding with a different color space.