One or more methods and systems are provided for encoding, decoding and playback of a video content in a client-server architecture. The invention proposes a video encoding and decoding method that includes identification of activities in the video content, identification of corresponding API's with related parameters corresponding to activity and storing those API's along with base frame and object frame in the database. In this invention, animation API functions are created for unknown/random activities. The playback involves decoding the data, which is a set of instructions to play the animation with given objects and base frames, and animating object frame over base frame using said API functions.

A method of coding at least one image comprising the steps of splitting the image into a plurality of blocks, of grouping said blocks into a predetermined number of subsets of blocks, of coding each of said subsets of blocks in parallel, the blocks of a subset considered being coded according to a predetermined sequential order of traversal. The coding step comprises, for a current block of a subset considered, the sub-step of predictive coding of said current block with respect to at least one previously coded and decoded block, and the sub-step of entropy coding of said current block on the basis of at least one probability of appearance of a symbol.

A method of coding at least one image comprising the steps of splitting the image into a plurality of blocks, of grouping said blocks into a predetermined number of subsets of blocks, of coding each of said subsets of blocks in parallel, the blocks of a subset considered being coded according to a predetermined sequential order of traversal. The coding step comprises, for a current block of a subset considered, the sub-step of predictive coding of said current block with respect to at least one previously coded and decoded block, and the sub-step of entropy coding of said current block on the basis of at least one probability of appearance of a symbol.

A method of coding at least one image comprising the steps of splitting the image into a plurality of blocks, of grouping said blocks into a predetermined number of subsets of blocks, of coding each of said subsets of blocks in parallel, the blocks of a subset considered being coded according to a predetermined sequential order of traversal. The coding step comprises, for a current block of a subset considered, the sub-step of predictive coding of said current block with respect to at least one previously coded and decoded block, and the sub-step of entropy coding of said current block on the basis of at least one probability of appearance of a symbol.

A method of coding at least one image comprising the steps of splitting the image into a plurality of blocks, of grouping said blocks into a predetermined number of subsets of blocks, of coding each of said subsets of blocks in parallel, the blocks of a subset considered being coded according to a predetermined sequential order of traversal. The coding step comprises, for a current block of a subset considered, the sub-step of predictive coding of said current block with respect to at least one previously coded and decoded block, and the sub-step of entropy coding of said current block on the basis of at least one probability of appearance of a symbol.

A method of coding at least one image comprising the steps of splitting the image into a plurality of blocks, of grouping said blocks into a predetermined number of subsets of blocks, of coding each of said subsets of blocks in parallel, the blocks of a subset considered being coded according to a predetermined sequential order of traversal. The coding step comprises, for a current block of a subset considered, the sub-step of predictive coding of said current block with respect to at least one previously coded and decoded block, and the sub-step of entropy coding of said current block on the basis of at least one probability of appearance of a symbol.

A method of coding at least one image comprising the steps of splitting the image into a plurality of blocks, of grouping said blocks into a predetermined number of subsets of blocks, of coding each of said subsets of blocks in parallel, the blocks of a subset considered being coded according to a predetermined sequential order of traversal. The coding step comprises, for a current block of a subset considered, the sub-step of predictive coding of said current block with respect to at least one previously coded and decoded block, and the sub-step of entropy coding of said current block on the basis of at least one probability of appearance of a symbol.

A method, system and computer program product for segmenting generic foreground objects in images and videos. For segmenting generic foreground objects in videos, an appearance stream of an image in a video frame is processed using a first deep neural network. Furthermore, a motion stream of an optical flow image in the video frame is processed using a second deep neural network. The appearance and motion streams are then joined to combine complementary appearance and motion information to perform segmentation of generic objects in the video frame. Generic foreground objects are segmented in images by training a convolutional deep neural network to estimate a likelihood that a pixel in an image belongs to a foreground object. After receiving the image, the likelihood that the pixel in the image is part of the foreground object as opposed to background is then determined using the trained convolutional deep neural network.

Techniques are disclosed for coding point cloud data using a scene model. An example device for coding point cloud data includes a memory configured to store the point cloud data and one or more processors implemented in circuitry and communicatively coupled to the memory. The one or more processors are configured to determine or obtain a scene model corresponding with a first frame of the point cloud data, wherein the scene model represents objects within a scene, the objects corresponding with at least a portion of the first frame of the point cloud data. The one or more processors are also configured to code a current frame of the point cloud data based on the scene model.

Systems, methods, and devices for managing media storage and delivery, including obtaining, by a media access function (MAF), a glTF file corresponding to a scene; determining that the glTF file has a CBOR format; converting the glTF file into a converted glTF file having a JSON format using a first CBOR parser function implemented by the MAF; and obtaining media content corresponding to the scene based on the converted glTF file.