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: Various embodiments provide an apparatus, a method, and a computer program product. 1. An apparatus incudes at least one processor; and at least one non-transitory memory includes 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 an overfitting operation, at an encoder side, to obtain an overfitted probability model, wherein overfitting comprises one or more training operations applied to a probability model, wherein one or more parameters of the probability model are trained; use the overfitted probability model to provide probability estimates to a lossless codec or a substantially lossless codec for encoding data or a portion of the data; and signal information to a decoder on whether to perform the overfitting operation at the decoder side.

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 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: 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.

Abstract: Data may be encoded to minimize distortion after decoding, but the quality required for presentation of the decoded data to a machine and the quality required for presentation to a human may be different. To accommodate different quality requirements, video data may be encoded to produce a first set of encoded data and a second set of encoded data, where the first set may be decoded for use by one of a machine consumer or a human consumer, and a combination of the first set and the second set may be decoded for use by the other of a machine consumer or a human consumer. The first and second set may be produced with a neural encoder and a neural decoder, and/or may be produced with the use of prediction and transform neural network modules. A human-targeted structure and a machine-targeted structure may produce the sets of encoded data.

Abstract: A method comprising obtaining a 360-degree video content from a video source; projecting the 360-degree video content onto a 2D image plane; dividing the projected 360-degree video content into a plurality of regions, wherein the regions are partly overlapping and each region covers a region of the 360-degree video content suitable for a viewport presentation; receiving a request for a viewport orientation of the 360-degree video content from a client; and providing the client with an viewport presentation of the region corresponding to the requested viewport orientation.

Abstract: An apparatus may be configured to: transmit, to a client, an indication of one or more request-response overload capabilities; receive, from the client, at least one request for a plurality of media segments based, at least partially, on the indication of the one or more request-response overload capabilities; and transmit, to the client, at least one response comprising the plurality of media segments. The apparatus may be, for example, a media server, an HTTP overload handler, an edge server, a DANE, etc.

Abstract: A method comprising: authoring a plurality of sets of media tracks comprising at least a first set of media tracks and a second set of media tracks into a media file format, wherein a subset of tracks of the first set comprises alternate data for each other and a subset of tracks of the second set comprises alternate data for each other; and including, in or along a bitstream comprising a media file including or inferring said media tracks, an indication that said subset of tracks of the first set are alternatives to each other and said subset of tracks of the second set are alternatives to each other upon playback of the media tracks.

Abstract: A method, apparatus and computer program product creates a viewpoint position structure for media content. The viewpoint position structure specifies a position of a viewpoint defined in a reference coordinate system and an offset of the reference coordinate system with respect to a geographical reference. The method, apparatus and computer program product cause storage of the viewpoint position structure. An indication may be created as to whether the media content is augmented reality media content. The augmented reality media content may comprise a background that is at least partially transparent. The offset may be determined, within the reference coordinate system, relative to a geomagnetic reference direction, based upon one or more of a viewpoint yaw angle, a viewpoint pitch angle, or a viewpoint roll angle.

Abstract: There is provided methods, apparatuses and computer program products for video coding and decoding. A first part of a first coded video representation is decoded, and information on decoding a second coded video representation is received and parsed. The coded second representation differs from the first coded video representation in chroma format, sample bit depth, color gamut and/or spatial resolution, and the information indicates if the second coded video representation may be decoded using processed decoded pictures of the first coded video representation as reference pictures.

Abstract: An example method is provided to include receiving a media bitstream comprising one or more media units and a first enhancement information message, wherein the first enhancement information message comprises at least two independently parsable structures, a first independently parsable structure comprising information about at least one purpose of one or more neural networks (NNs) to be applied to the one or more media units, and a second independently parsable structure comprising or identifying one or more neural networks; decoding the one or more media units; and using the one or more neural networks to enhance or filter one or more frames of the decoded the one or more media units, based on the at least one purpose. An example method includes. Corresponding apparatuses and computer program products are also provided.

Abstract: An 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 having metadata or compressed neural network data of a portion of the at least one neural network; and wherein a serialized bitstream comprises one or more of the at least one information unit.

Abstract: An 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: provide signal information to identify an atlas identifier on a sample of a volumetric media track, or on the volumetric media track in a multi-track container; wherein the signal information allows a file parser to link volumetric media tracks with different atlas identifiers that originate from a volumetric media elementary stream; and wherein the file parser is able to reconstruct the volumetric media elementary stream based on the signal information and data encapsulated in the multi-track container.