Abstract: A method includes generating a bitstream defining a presentation, the presentation comprising an omnidirectional visual media content and a first visual media component and a second visual media component; indicating in the bitstream a first presentation timeline and a second presentation timeline; and indicating in the bitstream a switching mode with respect to the first presentation timeline associated with the first visual media component, or with respect to the second presentation timeline associated with the second visual media component, the switching mode being indicated dependent on a viewpoint of a user; wherein the switching mode provides an indication of switching to the first visual media component or to the second visual media component, the first visual media component corresponding to content captured from a first omnidirectional camera in a first location, and the second visual media component corresponding to content captured from a second omnidirectional camera in a second location.

Abstract: The embodiments relate to a method comprising indicating a video bitstream format wherein one or more image regions are allowed in a picture of a video bitstream (710); indicating at least a first substitute image region (720); indicating mapping information to locate the first substitute image region in the picture; wherein a first video bitstream comprising the first substitute image region at a location according to the mapping information conforms to the video bitstream format (730). The embodiments also concern a method at a receiver, and technical equipment for implementing the methods.

Abstract: An apparatus may be configured to: determine at least one image; determine at least one camera parameter; determine at least one distortion parameter, wherein the at least one distortion parameter comprises at least one entrance pupil parameter; determine at least one control point of the at least one image; and refine the at least one distortion parameter based, at least partially, on the at least one control point and the at least one camera parameter.

Abstract: An apparatus comprising: at least one processor; and at least one memory storing instructions that, when executed by the at least one processor, cause the apparatus at least to: maintain a first parameter update tree that tracks residuals of weight updates of a machine learning model; maintain a second parameter update tree that tracks the weight updates of the machine learning model; pass the first parameter update tree and the residuals to an encoder; receive a first bitstream generated for the residuals from the encoder; pass the second parameter update tree and the weight updates to the encoder; receive a second bitstream generated for the weight updates from the encoder; and determine whether to signal to a decoder the first bitstream generated for the residuals or the second bitstream generated for the weight updates.

Abstract: There is disclosed an apparatus and a method for spatial computing service session description for volumetric XR conversation. In accordance an embodiment the method comprises receiving volumetric video from a plurality of sources, the volumetric video data comprising color images and depth images representing at least a part of a scene; determining which of the plurality of sources belong to a same group; selecting a group identifier for the group; associating the volumetric video with the group identifier indicative of from which group the volumetric video data is received; associating the volumetric video with a source identifier indicative of from which source of the group the volumetric video data is received; associating the color image of the volumetric video with a color data identifier; and associating the depth image of the volumetric video with a depth data identifier.

Abstract: In example embodiments, an apparatus, a method, and a computer program product are provided. The apparatus comprises at least one processor; and at least one non-transitory memory including computer program code; wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus at least to perform determine a processing order of building blocks to encode or decode a media item; and determine a number of processing steps required to encode or decode the media item; wherein the processing order of building blocks and the number of processing steps are determined based on a content of the media item by using a guided probability model based on a neural network.

Abstract: In example embodiments, an apparatus, a method, and a computer program product are provided. The apparatus includes at least one processor; and at least one non-transitory memory including computer program code; wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus at least to perform: encode or decode a high-level bitstream syntax for at least one neural network; wherein the high-level bitstream syntax comprises at least one information unit, wherein the at least one information unit comprises syntax definitions for the at least one neural network or a portion of the at least one neural network; and wherein a serialized bitstream comprises one or more of the at least one information units.

Abstract: Various embodiments provide an apparatus, a method, and a computer program product. The apparatus includes at least one processor; and at least one non-transitory memory comprising computer program code; wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus at least to perform: organize plurality of decoders side neural networks based on one or more task categories or one or more tasks; and select a decoder side neural network based at least on the one or more task categories or the one or more task.

Abstract: Media content is received for streaming to a user device. A neural network is trained based on a first portion of the media content. Weights of the neural network are updated to overfit the first portion of the media content to provide a first overfitted neural network. The neural network or the first overfitted neural network is trained based on a second portion of the media content. Weights of the neural network or the first overfitted neural network are updated to overfit the second portion of the media content to provide a second overfitted neural network. The first portion and the second portion of the media content are sent with associations to the first overfitted neural network and the second overfitted to the user equipment.

Abstract: Various embodiments provide an apparatus, a method, and a computer program product. An example apparatus includes at least one processor; and at least one non-transitory memory comprising computer program code; wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus at least to iteratively perform following until a stopping criterion is met: provide a finetuning driving content (FDC) or a content derived from FDC to a decoder side neural network (DSNN); compute an output of the DSNN as a processed FDC; compute a loss based on the processed FDC and an approximated ground truth data (AGT) associated with the FDC; compute an update to the DSNN; and apply the computed update to the DSNN.

Abstract: A method, apparatus and computer program product encode, into a media description, a first information item indicative of a first locator for segment metadata for a set of representations. The method, apparatus and computer program product encode, into the media description, one or more representation-specific information items indicative of representation-specific locator for segment media data for one or more representations of the set of representations. The method, apparatus and computer program product cause storage of the media description with the set of representations.

Abstract: The embodiments relate to method for encoding and decoding, wherein the method for encoding comprises receiving an input block of a video frame for encoding; applying at least a learning-based model (702) for said input block as a processing step for encoding the block; combining (703) an output of a learning-based model with one or more data sources (712, 713) by a combination process; encoding block to a bitstream (40); using a result of the combination process as additional input for the learning-based model for encoding a subsequent block; and encoding to a bitstream combination information (720) used in the combination process, said combination information comprising at least one or more combination parameters. The embodiments also relate to technical equipment for implementing the methods.

Abstract: A method, an apparatus, and a computer program product are provided. An example method includes defining an enhancement message comprising at least one of the following: an identifying number for identifying a post-processing filter; a mode identity (idc) field used of indicating association of a post-processing filter with the identifying number; a flag for specifying the enhancement message being used for a current layer; and the payload byte comprising a bitstream; and using the enhancement message for at least one of specifying a neural network that is used as a post-processing filter or cancelling a use of a previous post-processing filter with the same identifying number.

Abstract: The embodiments relate to a method comprising establishing a three-dimensional conversational interaction with one or more receivers; generating a pointcloud relating to a user and capturing audio from one or more audio source; generating conversational scene description comprising at least a first dynamic object describing a virtual space for the three-dimensional conversational interaction, wherein the first dynamic object refers to one or more objects specific to the three-dimensional conversational interaction, wherein said one or more objects comprises at least data relating to transformable pointcloud; audio obtained from said one or more audio source and input obtained from one or more connected devices controlling at least the pointcloud, wherein said objects are linked to each other for seamless manipulation; applying the conversational scene description into a metadata, and transmitting the metadata with the respective audio in realtime to said one or more receivers.

Abstract: The embodiments relate to a method including determining a foreground area covering a viewport of 360-degree video and one or more other areas of 360-degree video, not containing the foreground area in its entirety; concluding a first set of tile streams among available tile streams of the 360-degree video to cover the foreground area; concluding a second set of tile streams among the available tile streams of the 360-degree video, to cover the one or more other areas; and requesting transmission of a first set of portions of the first set of tile streams and a second set of portions of the second set of tile streams, wherein the portions in the first set of portions have a shorter duration that portions in the second set of portions.

Abstract: The embodiments relate to a method for encoding and a decoding, and apparatuses for the same. The method for encoding comprises receiving a block of a video frame for encoding (1510); making a decision on whether or not a learning-based model is to be applied as a processing step for encoding the block (1520); applying the learning-based model for said input block according to the decision, where the learning-based model has been selectively fine-tuned according to information relating to activation of the learning-based model of previously-decoded blocks (1530); encoding a signal corresponding to the decision on usage of the learning-based model into a bitstream (1540); and encoding the block into a bitstream with an information whether the block is to be used for finetuning (1550).

Abstract: The embodiments relate to a method at a sender device, the method including receiving, as a response to a delivered indication of a number of supported subpictures, from a receiver an indication on a number of subpictures allowed in an encoded image data; partitioning a bitstream representing an image data into subpictures, the amount of which corresponds to the indicated number of subpictures; generating an encoded bitstream including said subpictures; delivering the encoded bitstream to a receiver apparatus; and delivering required parameter sets for said subpictures to said receiver apparatus. The embodiments also concern a method at a receiver device, and corresponding devices.

Abstract: Described are methods, apparatuses and computer program products for signaling and storing compressed point clouds. Sub-sample entries associated with sequences of sub-samples within sequences of samples may indicate whether sequences of sub-samples were encapsulated alone in a track, without other sub-samples or additional header data. Sub-sample entry types can be indexed at track-level sub-sample description boxes. Point cloud compression coded bitstream component types may be signaled by including respective point cloud unit header information in a codec-specific parameters-related field of track level sub-sample description boxes. Sub-sample information boxes may indicate sub-sample entry indices for respective sub-samples. A flag in such information boxes may indicate the presence of sub-sample description entry indexes. Description index boxes can contain sub-sample description entry indexes in the same container as sub-sample information boxes.

Abstract: There are disclosed various methods, apparatuses and computer program products for video encoding and decoding. In some embodiments the method for video encoding comprises obtaining compressed volumetric video data representing a three-dimensional scene or object (71); capsulating the compressed volumetric video data into a data structure (72); obtaining data of a two-dimensional projection of at least a part of the three-dimensional scene as seen from a certain viewport (73); and including the data of the two-dimensional projection into the data structure (74).

Abstract: A method, apparatus and computer program product are provided to signal and store compressed point clouds in video encoding. The method, apparatus and computer program product may be utilized in conjunction with a variety of video formats. Relative to encoding of compressed point clouds, the method, apparatus and computer program product access a point cloud compression coded bitstream and cause storage of the point cloud compression coded bitstream. The point cloud compression coded bitstream comprises a texture information bitstream, a geometry information bitstream, and an auxiliary metadata bitstream. Relative to the decoding of compressed point clouds, the method, apparatus and computer program product receive a point cloud compression coded bitstream and decode the point cloud compression coded bitstream.