Abstract:
A method comprising: encoding pictures into a bitstream, the bitstream comprising at least two scalability layers, pictures being associated with access units and pictures being associated individually with one of the at least two scalability layers; indicating in the bitstream inter-layer prediction dependencies, indicative of direct reference layers, if any, of a first scalability layer and indirect reference layers, if any, of the first scalability layer; selecting an earlier picture in decoding order as a basis for deriving picture order count (POC) related variables for a current picture based on a pre-defined algorithm, the current picture being associated with a current scalability layer, wherein the earlier picture is the closest preceding picture, in decoding order, to the current picture among a set of pictures that are associated with the current scalability layer or any direct or indirect reference layer of the current scalability layer.
Abstract:
In an example embodiment, a method, apparatus and computer program product are provided. The method includes defining a plurality of depth layers of a depth map. At least one depth layer of the plurality of depth layers is associated with a respective depth limit. The method further includes determining, for the at least one depth layer, a respective texture view layer of a first picture. The method further includes deriving a measure of a respective texture property for the respective texture view layer. Selective filtering is applied to the respective texture view layer based on the measure of the respective texture property and the respective depth limit associated with the at least one depth layer.
Abstract:
An example apparatus includes: 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 perform: receiving a media bitstream comprising one or more media units and at least a first enhancement information message, wherein the first enhancement information message comprises or identifies a neural network, and wherein the received media bitstream comprises a third enhancement information message; decoding the one or more media units; and using the neural network to enhance or filter the decoded one or more media units within a temporal scope determined with the third enhancement information message, a spatial scope determined with the third enhancement information message, or a spatio-temporal scope determined with the third enhancement information message.
Abstract:
An example apparatus, method, and 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 neural network representation (NNR) bitstream comprises one or more of the at least one information units, and wherein the syntax definitions provide one or more mechanisms for introducing a weight update compression interpretation into the NNR bitstream.
Abstract:
The embodiments relate to a method for encoding two or more tensors. The method comprises processing the two or more tensors having respective dimensions so that the dimensions of said two or more sensors have the same number (510); identifying which axis of each individual tensor is swappable to result in concatenable tensors around an axis of concatenation (520): reshaping the tensors so that the dimensions are modified based on the swapped axis (530): concatenating the tensors around the axis of concatenation to result in concatenated tensor (540): compressing the concatenated tensor (550); generating syntax structures for carrying concatenation and axis swapping information (560): and generating a bitstream by combining the syntax structures and the compressed concatenated tensor (570). The embodiments also relate to a method for decoding, and to apparatuses for implementing the methods.
Abstract:
There are disclosed various methods, apparatuses and computer program products for video encoding and decoding. In some embodiments a method comprises at least one of the following: encoding into a bitstream an indication that motion fields are stored, but only for inter-layer motion prediction; encoding into a bitstream an indication on a limited scope of motion field usage; encoding into a bitstream an indication whether or not to use the motion field for prediction; encoding into a bitstream an indication of storage parameters for storing motion information.
Abstract:
A method comprising encoding a bitstream comprising a base layer, a first enhancement layer and a second enhancement layer; encoding an indication of both the base layer and the first enhancement layer used for prediction for the second enhancement layer in the bitstream; encoding, in the bitstream, an indication of a first set of prediction types that is applicable from the base layer to the second enhancement layer, wherein the first set of prediction types is a subset of all prediction types available for prediction between layers, and encoding, in the bitstream, an indication of a second set of prediction types that is applicable from the base layer or the first enhancement layer to the second enhancement layer, wherein the second set of prediction types is a subset of all prediction types available for prediction between layers.
Abstract:
The embodiments relate to a method comprising receiving an encoded video comprising a GDR picture and recovering pictures following the GDR picture in decoding order; decoding information that a slice-based GDR is in use, wherein each of the GDR picture and the recovering pictures comprises a first set of slices comprising a clean area and a second set of slices comprising rest of the picture; relabeling the GDR picture as an intra-coded random access point picture in a modified bitstream; including only the first set of slices of the GDR picture and the recovering pictures into the modified bitstream; decoding information on a picture width and height of each of the GDR picture and the recovering pictures; modifying the picture width and height to exclude the second set of slices; and including the modified information on the picture width and height to the modified bitstream.
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 perform: determine a subset of parameters to overfit from a set of candidate parameters of decoder side neural network to be overfitted (OPs); wherein the subset of parameters to overfit is smaller than the set of candidate parameters to be overfitted; and overfit the determined subset of parameters.
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.