Abstract: Described are systems and methods for encoding or decoding a picture part of video information can include using a refinement mode per block where the refinement mode can be based on a refinement parameter. The refinement mode can include a cross-component refinement that can be a cross-component chroma refinement. The refinement mode can include enabling selection per block of a refinement parameter where the refinement parameter can include one or more chroma refinement parameters included in a chroma refinement table.

Abstract: A cross-component dependent tool to be used for a chroma block of a picture is enabled responsive to a size of said chroma block and to a size of at least one luma block co-located with the chroma block. Then, the chroma block is decoded responsive to said enablement of said cross-component dependent tool. A encoding and decoding methods are presented as well as encoding and decoding devices.

Abstract: Different quantization matrices may be transmitted corresponding to different block sizes, color components and prediction modes. To more efficiently signal the coefficients of the quantization matrices, in one implementation, a unified matrix identifier matrixId is used, based on a size identifier (sizeId) that relates to CU size with larger sizes listed first, and a matrix type (matrixTypeId) with luma QMs listed first. For example, the unified identifier is derived as: matrixId=N*sizeId+matrixTypeId, where N is the number of possible type identifiers, e.g., N=6. This single identifier allows referring to any previously transmitted matrix when using prediction (copy), and transmitting larger matrices first avoids interpolation in the prediction process. When a block uses the Intra Block Copy prediction mode, QM identifier may be derived as if the block uses the INTER prediction mode.

Abstract: Systems, methods, and instrumentalities are disclosed for performing motion compensation with long-term history-based motion vector predictor candidate(s). A device configured for performing such motion compensation may include a processor. The processor may be configured to obtain a long-term motion vector predictor candidate. The processor may also be configured to add the long-term motion vector predictor candidate to a history-based motion vector prediction (HMVP) list for a current block. The processor may also be configured to decode the current block using the HMVP list having the long-term motion vector prediction candidate.

Abstract: At least a method and an apparatus are presented for efficiently encoding or decoding video. For example, one or more chroma residual scaling parameters are determined based one or more luma mapping parameters and based on a corrective value of the one or more chroma residual scaling parameters. The video is encoded or decoded based on the determined one or more chroma residual scaling parameters.

Abstract: A device may obtain, for a video block, a supplemental information indicator and decode the video block based on the supplemental information indicator associated with the video block. The supplemental information indicator may indicate whether the depth information associated with the video block and/or the motion information associated with the video block is available. Supplemental information associated with the video block (e.g., the depth information associated with the video block and/or the motion information associated with the video block) may be available, for example, in video data. In examples, a device may obtain a video block. If the supplemental information indicator associated with the video block indicates that depth information associated with the video block is available, the device may obtain the depth information from video data sent to the device and decode the video block using the depth information.

Abstract: At least a method and an apparatus are presented for efficiently encoding or decoding video. For example, a number of states used in a dependent quantization DQ is determined for a transform block; and the DQ/inverse DQ with the determined number of states is applied to the transform block. According to non-limiting examples, the usage of DQ and the number of states used for DQ is based on the number of coded coefficients in the transform block, the transform block size, the prediction mode (intra/inter) of the block, the color components (luma/chroma), the quantization parameter of the block, the transforms type.

Abstract: A method and an apparatus for converting film grain metadata are provided. In an embodiment, a first film grain metadata is obtained, the first film grain metadata complying with a first film grain syntax and being representative of a first film grain model. At least one part of the first film grain metadata is converted to at least one part of a second film grain metadata, the second film grain metadata complying with a second film grain syntax and being representative of a second film grain model, wherein the second film grain syntax is different from the first film grain syntax, or the second film grain model is different from the first film grain model, or both the second film grain syntax and the second film grain model are different from the first film grain syntax and the first film grain model.

Abstract: Decoding and/or encoding video information included in a bitstream can involve a predicted quantization matrix associated with at least a portion of the video information and a syntax element indicating that at least one coefficient of the predicted quantization matrix is to be interpreted as a residual such that the decoding and/or encoding of at least a portion of the video information is based on a combination of the predicted quantization matrix and the residual, where the syntax element is obtained from the bitstream during decoding, or included in the bitstream during encoding.

Abstract: Compression technology comprises deriving chroma quantization parameter (Qpc) based on luma Qp using luma-to-chroma Qp mapping table. Such a table may be shared by the encoder and the decoder. However, in some cases, signaling such a table in the data stream instead of having it fixed by a standard may be advantageous. The syntax used to encode, signal and decode this table has a cost in terms of bitrate. The present principles propose to signaling of a luma-to-chroma mapping table in the data stream according to different embodiments.

Abstract: A method for reconstructing a block of an image, said block comprising a plurality of components and being predictively encoded from a reference block, includes if a single quantized residual block is used to jointly encode at least two components of the plurality of components, deriving at least one quantization matrix from a plurality of scaling lists each defined for one component of the plurality of components; and, applying one of the at least one derived quantization matrix to the single quantized residual block to obtain a reconstructed residual block for each of the at least two components.

Abstract: A method may include applying a first machine learning model trained to perform an open-set detection by at least identifying, based at least on image data indicative of one or more objects present in at least one environment in which one or more vehicles operate, at least one new class of objects. A dataset including a plurality of classes of objects may be updated to include the at least one new class of objects. In some cases, the dataset may be further updated to include a label associated with the at least one new class of objects. A second machine learning model may be trained, or in some cases updated, based at least on the updated dataset including the at least one new class of objects. Related systems and computer program products are also provided.

Abstract: Different quantization matrices may be transmitted corresponding to different block sizes, color components and prediction modes. To more efficiently signal the coefficients of the quantization matrices, in one implementation, a unified matrix identifier matrixId is used, based on a size identifier (sizeId) that relates to CU size with larger sizes listed first, and a matrix type (matrixTypeId) with luma QMs listed first. For example, the unified identifier is derived as: matrixId=N*sizeId+matrixTypeId, where N is the number of possible type identifiers, e.g., N=6. This single identifier allows referring to any previously transmitted matrix when using prediction (copy), and transmitting larger matrices first avoids interpolation in the prediction process. When a block uses the Intra Block Copy prediction mode, QM identifier may be derived as if the block uses the INTER prediction mode.

Abstract: A method comprising: executing a streaming session establishment process allowing establishing a streaming session between two peers in a network, wherein the streaming session establishment process comprises receiving (404) information allowing controlling a power consumption of a decoding process applied for decoding a stream representative of a content to be streamed in the streaming session

Abstract: Systems, methods, and instrumentalities are disclosed for cross-component depth-luma coding. Depth information may be used as information for joint or cross-component coding of texture information (e.g., luma, chroma, or R, G, B colour component information). The depth information may be used to jointly code the corresponding texture information. In examples, a device may determine whether a coding mode, such as a joint depth-color coding mode (JDCC) (e.g., joint depth-luma coding mode (JDLC)) is used for a current block. If JDCC coding mode is used for the block, then the device may decode depth sample(s) in the block and predict the corresponding color sample(s) (e.g., luma sample(s) and/or chroma sample(s)) in the block based on the decoded depth sample(s).

Abstract: Methods and apparatuses are described for signaling decoding data in a video bitstream, using a syntax element indicating whether the decoding data are explicitly coded in the video bitstream or inferred from previous data of the video bitstream. A bitstream, a computer-readable storage medium, and a computer program product are also described.

Abstract: Decoding and/or encoding video information included in a bitstream can involve a predicted quantization matrix associated with at least a portion of the video information and a syntax element indicating that at least one coefficient of the predicted quantization matrix is to be interpreted as a residual such that the decoding and/or encoding of at least a portion of the video information is based on a combination of the predicted quantization matrix and the residual, where the syntax element is obtained from the bitstream during decoding, or included in the bitstream during encoding.

Abstract: Compression technology comprises deriving chroma quantization parameter (Qpc) based on luma Qp using luma-to-chroma Qp mapping table. Such a table may be shared by the encoder and the decoder. However, in some cases, signaling such a table in the data stream instead of having it fixed by a standard may be advantageous. The syntax used to encode, signal and decode this table has a cost in terms of bitrate. The present principles propose to signaling of a luma-to-chroma mapping table in the data stream according to different embodiments.

Abstract: Systems, methods, and instrumentalities are disclosed for adapting media (e.g., video) processing operations and/or parameters based on one or more viewing conditions in a media environment (e.g., to achieve power saving). Such viewing conditions may include a distance between a display device and a viewer, a viewpoint or viewing direction of the viewer towards the display device, and/or an ambient light level in the media environment. Aspects of the medical processing that may be adapted based on the viewing conditions may be associated with deblocking, sample adaptive offset (SAO) filtering, adaptive loop filtering (ALF), cross component adaptive loop filtering (CCALF), motion compensation, post-inter prediction processing, bi-prediction, residual scaling, luma mapping, chroma residual scaling (LMCS), geometric block partitioning, HDR signal reconstruction, etc.

Abstract: Provided are methods for detecting when a vehicle is encountering an out of operational design domain (ODD) scenario, which can include training a generative adversarial network (GAN) including a generator network and a discriminator network. The generator network may be trained to generate synthesized scenarios. The discriminator network may be trained to distinguish between true scenarios and the synthesized scenarios generated by the generator network. The trained discriminator network may be applied to detect when a vehicle encounters an out of operational design domain (ODD) scenario. Some methods described also include controlling the motion of the vehicle in response to an output of the trained discriminator network indicating that the vehicle is encountering the out of operational design domain (ODD) scenario. Systems and computer program products are also provided.