Abstract: A video decoding method includes: selecting a first intra prediction mode and a second intra prediction mode from a most probable mode (MPM) list; determining a first predictor based on the first intra prediction mode; determining a second predictor based on the second intra prediction mode; blending the first predictor and the second predictor to obtain a blended predictor for intra prediction; and decoding one or more pictures using the blended predictor.

Abstract: Systems and methods are described for video coding using generalized bi-prediction. In an exemplary embodiment, to code a current block of a video in a bitstream, a first reference block is selected from a first reference picture and a second reference block is selected from a second reference picture. Each reference block is associated with a weight, where the weight may be an arbitrary weight ranging, e.g., between 0 and 1. The current block is predicted using a weighted sum of the reference blocks. The weights may be selected from among a plurality of candidate weights. Candidate weights may be signaled in the bitstream or may be derived implicitly based on a template. Candidate weights may be pruned to avoid out-of-range or substantially duplicate candidate weights. Generalized bi-prediction may additionally be used in frame rate up conversion.

Abstract: Systems and methods are disclosed for encoding and for decoding of video data, including predicting a video block of the video data using decoder-side intra mode derivation (DIMD). The disclosed predicting techniques include selecting candidate intra prediction modes based on intra prediction modes used by neighboring video blocks. Techniques disclosed further include determining respective costs of using the selected candidate intra prediction modes to predict samples in a template region adjacent to the video block, deriving an intra prediction mode from the selected candidate intra prediction modes having the lowest cost, and predicting samples in the video block using the derived intra prediction mode.

Abstract: Processing a 360-degree video content for video coding may include receiving the video content in a first geometry. The video content may include unaligned chroma and luma components associated with a first chroma sampling scheme. The unaligned chroma and luma components may be aligned to a sampling grid associated with a second chroma sampling scheme that has aligned chroma and luma components. A geometric conversion to the video content may be performed. The video content, that may comprise the aligned chroma and luma components, in the first geometry may be converted to a second geometry. The first geometry may be a stitched geometry, and the second geometry may be a coding geometry. The converted video content in the second geometry may include the chroma and luma components aligned to the sampling grid associated with the second chroma sampling scheme.

Abstract: Methods and apparatuses are provided for encoding and decoding video data based on a supplemental enhancement information (SEI) message. An exemplary method includes: generating a reconstructed frame sequence based on a compressed video; decoding a supplemental enhancement information (SEI) message with respect to the reconstructed frame sequence, according to the compressed video; and performing temporal upsampling to the reconstructed frame sequence based on the SEI message by using a neural network.

Abstract: Methods and apparatuses are provided for processing video data by using an object mask information (OMI) supplemental enhancement information (SEI) message. An exemplary encoding method includes: receiving a video sequence; and encoding one or more pictures of the video sequence to generate a bitstream, comprising: encoding an auxiliary picture indicating a mask of an object in a primary picture, the mask of the object being represented by a sample value of the auxiliary picture; and generating a supplemental enhancement information (SEI) message indicating an attribute of the mask of the object.

Abstract: A system may receive an input image block, and input the input image block into multiple models which may be trained using a plurality of different datasets of image blocks. Each model of the multiple models may be trained using a dataset having similar attributes. The system may determine a model having a highest compression efficiency from among the multiple models, and encode the input image block using the determined model.

Abstract: Systems and methods are described for video coding using affine motion models with adaptive precision. In an example, a block of video is encoded in a bitstream using an affine motion model, where the affine motion model is characterized by at least two motion vectors. A precision is selected for each of the motion vectors, and the selected precisions are signaled in the bitstream. In some embodiments, the precisions are signaled by including in the bitstream information that identifies one of a plurality of elements in a selected predetermined precision set. The identified element indicates the precision of each of the motion vectors that characterize the affine motion model. In some embodiments, the precision set to be used is signaled expressly in the bitstream; in other embodiments, the precision set may be inferred, e.g., from the block size, block shape or temporal layer.

Abstract: A technique for suspended particle detection which includes irradiating at least one particle with a light source of a certain wavelength and capturing image data relating to the at least one particle with an image sensor or a camera. The technique further includes obtaining a frame of grayscale image data comprising luminance values of image data captured by the image sensor or camera. The technique also includes analyzing the image data in the frame to identify at least one particle captured in the frame. Analyzing the image data in the frame includes identifying pixels having luminance values that satisfy a threshold, determining particle contours of the at least one particle based, on the identified pixels, and generating at least one of quantitative or qualitative information for the at least one particle based, at least partially on the analyzing of the image data.

Abstract: The present disclose provides methods and systems for processing chroma signals. According to some embodiments, the method can include: determining, based on a value of a flag that indicates whether a chroma tool offsets related syntax element is present in a picture parameter set (PPS) raw byte sequence payload (RBSP) syntax structure, whether one or more chroma deblocking parameters are present in a picture header or a slice header associated with the PPS; and in response to the flag having a first value, decoding the one or more chroma deblocking parameters, or in response to the flag having a second value, skipping decoding the one or more chroma deblocking parameters.

Abstract: Methods and apparatuses are provided for processing video data by using generative face video supplemental enhancement information (SEI) messages. An exemplary method for generating a face picture includes: receiving a bitstream; decoding coded information of the bitstream to obtain a base picture and a supplemental enhancement information (SEI) message; determining whether the SEI message applies to a neural network for generating a face picture; in response to the SEI message applies to the neural network for generating the face picture, determining a mode and a corresponding face information parameter used to code the face picture based on the SEI message; and generating the face picture based on the base picture and the face information parameter by the neural network.

Abstract: A method of decoding a bitstream to output one or more pictures for a video stream, includes: receiving a bitstream; and decoding, using coded information of the bitstream, one or more pictures. The decoding includes: determining, based on an identifying number, whether a face video generative compression scheme is used; in response to a determination that the face video generative compression scheme is used, decoding a supplemental enhancement information (SEI) message, the SEI message comprising facial information; and reconstructing a face picture based on the facial information and a base picture associated with the SEI message.

Abstract: A method of decoding a bitstream to output one or more pictures for a video stream includes: decoding a bitstream to construct a merge candidate list including one or more merge candidates; determining whether a first candidate from the merge candidate list is a uni-motion candidate; in response to the first candidate being the uni-motion candidate, determining a bi-motion candidate based on the first candidate and one or more candidate motion vectors; and adding the bi-motion candidate to the merge candidate list.

Abstract: A method of decoding a video bitstream includes: determining a control point motion vector predictor (CPMVP) for an affine coded target block; refining the CPMVP based on a template matching (TM) cost to get a refined CPMVP; deriving the control point motion vector (CPMV) based on the refined CPMVP and a control point motion vector difference (CPMVD); and decoding the affine coded target block based on the CPMV.

Abstract: A method of decoding a bitstream includes: receiving a bitstream; and decoding, using coded information of the bitstream, one or more pictures, by: obtaining a first prediction signal based on a first block vector associated with a target subblock on a boundary of a target block of the one or more pictures; obtaining a second prediction signal based on prediction information from a neighboring subblock of the target subblock; and performing a motion compensation, based on the first prediction signal and the second prediction signal, to predict the target subblock.

Abstract: The present disclosure provides a method of encoding a video sequence. The method includes: receiving a video sequence; encoding the video sequence by determining that an implicit geometric partitioning mode (GPM) is applied to a coding block, a coding block being split into two geometric partitions; and performing an intra and inter prediction on the coding block.

Abstract: The present disclosure provides a method of encoding a video sequence. The method includes receiving a video sequence; encoding the video sequence by deriving one or more intra modes for intra prediction; performing template matching (TM) tests on a template region using different filters for the one or more intra modes; and selecting one or more intra filters based on a TM cost.

Abstract: A method for decoding a bitstream associated with a video sequence is provided. The method includes: decompressing a bitstream associated with a video sequence; reconstructing one or more frames of the video sequence based on the decompressed bitstream; determining a sequence-level mean intersection of union (MIOU) based on one or more reconstructed frames; obtaining a decision metric according to the sequence-level MIOU to determine a resampling ratio and whether to perform a temporal resampling; and resampling the one or more reconstructed frames based on the decision metric.

Abstract: Systems, methods, and instrumentalities may be provided for determining whether to bypass bi-directional optical flow (BDOF) if BDOF is used in combination with bi-prediction with coding unit (CU) weights (e.g., generalized bi-prediction (GBi)). A coding system may combine coding modes, coding techniques, and/or coding tools. The coding system may include a wireless transmit/receive unit (WTRU). For example, the coding system may combine BDOF and bi-prediction with CU weights (BCW). BDOF may include refining a motion vector associated with a current CU based at least in part on gradients associated with a location in the current CU. The coding system may determine that BDOF is enabled, and/or that bi-prediction with CU weights is enabled for the current CU. The coding system's determination that bi-prediction with CU weights is enabled and/or that BDOF is enabled may be based on one or more indications.

Abstract: A video decoding method includes decoding an image bitstream associated with a video sequence to obtain a reconstructed key frame; extracting features of the reconstructed key frame; decoding a feature bitstream associated with the video sequence to obtain a motion token; reconstructing a dense motion based on the features of the reconstructed key frame and the motion token; and generating video content based on the reconstructed dense motion.