Nokia Technologies Oy

Nokia Corporation

Core Wireless Licensing S.a.r.l.

Nokia Mobile Phones Limited

Microsoft Technology Licensing, LLC

Nokia Oy

Roac Nd Investments L.l.c.

Provenance Asset Group LLC

Sisvel International S.a.

Miska Matias Hannuksela

Emre Baris Aksu

Ye-Kui Wang

Jani Lainema

Kemal Ugur

Francesco Cricri

Kashyap Kammachi Sreedhar

Sujeet Shyamsundar Mate

Hamed Rezazadegan Tavakoli

Igor D Curcio

Ying Hai Chen

Vinod Kumar Malamal Vadakital

Alireza Aminlou

Igor Danilo Diego Curcio

Sebastian Schwarz

Ari Hourunranta

Dmytro Rusanovskyy

Francesco Cricrì

Lukasz Kondrad

Imed Bouazizi

Srikanth Manchenahally Gopalakrishna

Honglei Zhang

Matti Salmi

Roberto Castagno

Stephan Wenger

Dogu Cetin

Mika Rantanen

Alireza Zare

Saba Ahsan

Lauri Ilola

Mehmet Oguz Bici

Lauri Aleksi Ilola

Caglar Aytekin

Kashyap Kammachi-Sreedhar

Chenghao Liu

Nam Le

Antti Johannes Eronen

Harri Juhani Pekonen

Yu You

Pekka Talmola

Mikko Johannes Honkala

Marja Salmimaa

Timo Juhani Ahonen

Daniel Vaquero

Kerem Caglar

Juha-Pekka Hippeläinen

Xianglin Wang

Limin Wang

Krit Panusopone

Seungwook Hong

Jussi Leppanen

Vidya Raghavan Setlur

Pasi Sakari Ojala

Jussi Vesma

Toni Paila

Antti Hallapuro

Houqiang Li

Iraj Saniee

David Leon

Ville-Veikko Mattila

Payman Aflaki Beni

Suresh Chitturi

Justin Ridge

Ramakrishna Vedantham

Joachim Wabnig

Dominique Müller

Michael Ingrassia

Tolga Capin

Viktor Varsa

Xingyang Ni

Yi Guo

Ru-Shang Wang

Jonne Juhani Mäkinen

Ramin Ghaznavi Youvalari

Atanas Gotchev

Tuomas Virtanen

Peter O Fasogbon

Mihail Georgiev

Ali Karaoglu

Nannan Zou

Roope Olavi Jarvinen

Mehdi Rezaei

Christoph Bachhuber

Goutham Rangu

Yat Hong Lam

Annamaria Mesaros

Ye Kui Wang

Jani Toiminen

Daidi Zhong

Ru Shang Wang

Dong Tian

Payman Aflaki-Beni

Olli Kilpelainen

Jani Kattelus

Toni Heittola

Ying Chen

Various embodiments provide example apparatus, method, and computer program product. The example 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: define a derived image item; and define a single stream item property, wherein the single stream item property is used to indicate that input image items of the derived image item are concatenated in encoded domain to obtain a single stream and are to be decoded by a single decoder.

Method and apparatus for encoding, decoding, or progressive rendering of image

An apparatus comprising: at least one processor; and at least one non-transitory memory storing instructions that, when executed by the at least one processor, cause the apparatus at least to: indicate a mixed network abstraction layer unit type pictures sample group used to merge video base tracks having a subpicture track; indicate a sample group description entry of the mixed network abstraction layer unit type pictures sample group, the sample group description entry indicating a group of pairs of mixed network abstraction layer unit type track reference indices, which reference video subpicture tracks or track groups; and wherein when a video bitstream is resolved from a video base track containing a mixed network abstraction layer unit type sample group with merging pairs of video subpicture tracks signaled in a mixed network abstraction layer unit type pictures sample group entry, then there is mixing of different network abstraction layer unit types.

Coded picture with mixed VCL NAL unit type

Apparatuses, methods, and computer programs for compressing a neural network are disclosed. An apparatus includes at least one processor; and at least one non-transitory memory including computer program code, the memory and the computer program code configured to, with the at least one processor, cause the apparatus to: receive information from a second device, where the information comprises at least one parameter configured to be used for compression of a neural network, where the at least one parameter is in regard to at least one first aspect or task of the neural network; and compress the neural network, where the neural network is compressed based, at least partially, upon the at least one parameter received from the second device. The apparatus may also receive a compressed neural network from the second device, and further compress the compressed neural network based on the information.

High-level syntax for priority signaling in neural network compression

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 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: define or extend a file format data structure to comprise: a cell size to indicate dimensions of a region, in pixels, comprising a mask value; a mask coding method to indicate a coding method applied to a mask or data of a media; mask coding parameters to indicate additional encoding or decoding parameters needed to process the coded mask data; and a mask configuration comprising the mask related information as a mask configuration structure.

Method and apparatus for signaling of regions and region masks in image file format

A method comprising: determining a number of units that are to be assigned to partitions and are initialized as unassigned; indicating or inferring a number of explicitly sized partitions to be assigned; indicating sizes for the explicitly sized partitions and accordingly marking unassigned units as assigned to partitions in a pre-defined scan order; indicating a count of units; repetitively assigning the count of units to partitions and accordingly marking unassigned units as assigned in the pre-defined scan order until the number of unassigned units is less than the count of units; and assigning, if the number of unassigned units is greater than 0, the unassigned units to a last partition.

Apparatus, a method and a computer program for video coding and decoding

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 () for said input block as a processing step for encoding the block; combining () an output of a learning-based model with one or more data sources () by a combination process; encoding block to a bitstream (); 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 () 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.

Method, an apparatus and a computer program product for video encoding and video decoding

There is disclosed a method, an apparatus and a computer program product for video encoding and decoding. In accordance with an embodiment the method comprises obtaining coded data of a sub-picture, the sub-picture belonging to a picture, and the sub-picture belonging to a sub-picture sequence and determining whether to use the sub-picture as a source for a manipulated reference sub-picture. If the determining reveals that the sub-picture is to be used as the source for the manipulated reference sub-picture, the manipulated reference sub-picture is generated from the sub-picture to be used as a reference for a subsequent sub-picture of the sub-picture sequence.

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.

Method, an apparatus and a computer program product for implementing gradual decoding refresh

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 (); identifying which axis of each individual tensor is swappable to result in concatenable tensors around an axis of concatenation (); reshaping the tensors so that the dimensions are modified based on the swapped axis (); concatenating the tensors around the axis of concatenation to result in concatenated tensor (); compressing the concatenated tensor (); generating syntax structures for carrying concatenation and axis swapping information (); and generating a bitstream by combining the syntax structures and the compressed concatenated tensor (). The embodiments also relate to a method for decoding, and to apparatuses for implementing the methods.

Method, an apparatus and a computer program product for neural network compression

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.

Method, an apparatus and a computer program product for video conferencing

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.

A method, apparatus, and computer program product provide for management of luma mapping with chroma scaling (LMCS) processes for Gradual Decoding Refresh (GDR) pictures. In the context of a method, the method accesses a picture to be decoded and determines whether the picture is within a GDR period. The method can also prevent a LMCS decoding process from being applied to the picture within the GDR period. Another method can determine whether a virtual boundary is within a current coding tree unit of a picture with a GDR period and if so, prevent a chroma residual scaling decoding process associated with LMCS from being applied to one or more coding units within a clean area. Another method can pad a neighboring pixel area from one or more reconstructed pixels in a clean area for a chroma residual scaling decoding process associated with LMCS.

Luma mapping with chroma scaling for gradual decoding refresh

Four or more bitstream versions of a same content are encoded and divided into segments of independently coded tile sets representing multiple spatial regions. First and second bitstreams include independently coded tile sets encoded at a first quality. Third and fourth bitstreams include independently coded tile sets encoded at a second quality. First and third bitstreams have first random access picture interval. Second and fourth bitstreams have second random access picture interval. Independently coded tile sets are grouped into multiple groups of collocated sub-picture tracks, only one of said tile sets per group is intended to be received and/or decoded per any segment. Instruction(s) are generated for merging tile sets of different spatial locations into coded picture(s), causing a tile set originating from a random access picture to be decoded as a tile set originating from a non-random-access picture when merged with a tile set originating from a non-random-access picture.

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.

Apparatus method and computer program product for probability model overfitting

An apparatus includes circuitry configured to: receive a sequence of pictures; encode a picture among the sequence of pictures as one or more slices and one or more tiles, wherein a slice comprises an integer number of tiles or is included in a tile; encode, into a slice header of a slice of the one or more slices, a subpicture identifier indicative of a subpicture that comprises the slice; wherein the subpicture identifier is indicative of a subpicture position for the subpicture comprising the slice, the subpicture identifier being among one or more subpicture identifiers indicative of one or more subpicture positions for one or more subpictures comprising one or more slices; and wherein the subpicture is an independently decodable spatiotemporal unit characterized in that a sequence of collocated subpictures is decodable independently of other subpictures.

Method and apparatus for tile-relative addressing in video coding

Growing community of inventors

Tampere, Finland

Miska Matias Hannuksela