Abstract: Video coding may include generating, by a processor, a decoded frame by decoding a current frame from an encoded bitstream and outputting a reconstructed frame based on the decoded frame. Decoding includes identifying a current encoded block from the current frame, identifying a prediction coding model for the current block, wherein the prediction coding model is a machine learning prediction coding model from a plurality of machine learning prediction coding models, identifying reference values for decoding the current block based on the prediction coding model, obtaining prediction values based on the prediction coding model and the reference values, generating a decoded block corresponding to the current encoded block based on the prediction values, and including the decoded block in the decoded frame.

Abstract: Guided restoration is used to restore video data degraded from a video frame. The video frame is divided into restoration units (RUs) which each correspond to one or more blocks of the video frame. Restoration schemes are selected for each RU. The restoration schemes may indicate to use one of a plurality of neural networks trained for the guided restoration. Alternatively, the restoration schemes may indicate to use a neural network and a filter-based restoration tool. The video frame is then restored by processing each RU according to the respective selected restoration scheme. During encoding, the restored video frame is encoded to an output bitstream, and the use of the selected restoration schemes may be signaled within the output bitstream. During decoding, the restored video frame is output to an output video stream.

Abstract: A method for encoding a current frame of a video includes jointly determining respective motion models for reference frames and encoding the current frame using the respective motion models. The reference frames are used for encoding the current frame. Jointly determining respective motion models for reference frames includes determining respective aggregated residuals for combinations of candidate motion models and selecting the combination of candidate motion models that corresponds to the smallest aggregated residual. The respective motion models correspond to the candidate motion models of the selected combination.

Abstract: An apparatus for decoding a current block of a video frame includes a memory and a processor. The processor is configured to execute instructions stored in the memory to identify a parameterized motion model; associate the parameterized motion model with a segment of a reference frame; and, in response to determining that the current block is encoded using the parameterized motion model, decode the current block using the parameterized motion model.

Abstract: A method includes segmenting the video frame with respect to a reference frame resulting in a segmentation, determining a first motion vector for the current block based on the segmentation, determining a second motion vector for the current block using translational motion compensation, and encoding, for the current block, the one of the first motion vector and the second motion vector corresponding to a smaller error. The segmentation includes a segment containing the current block and a parameterized motion model for the segment. Another method includes identifying a parameterized motion model corresponding to a motion model type, associating the parameterized motion model with a segment of a reference frame, and, in response to determining that the current block is encoded using the parameterized motion model, decoding the current block using the parameterized motion model.

Abstract: A method for encoding a current frame of a video includes jointly determining respective motion models for reference frames and encoding the current frame using the respective motion models. The reference frames are used for encoding the current frame. Jointly determining respective motion models for reference frames includes determining respective aggregated residuals for combinations of candidate motion models and selecting the combination of candidate motion models that corresponds to the smallest aggregated residual. The respective motion models correspond to the candidate motion models of the selected combination.

Abstract: A current block of a video frame can be encoded or decoded using parameterized motion models. First and second parameterized motion models are identified. The first parameterized motion model corresponds to a first motion model type, and the second parameterized motion model corresponds to a second motion model type. The first and second parameterized motion models are associated with one or more reference frames. One of the first or second parameterized motion models is selected along with an associated reference frame, such as based on a lowest prediction error. A motion vector is generated between the current block and the selected reference frame by warping pixels of the current block to a warped patch of the selected reference frame according to the selected parameterized motion model. A prediction block is generated using the motion vector, and the current block is encoded or decoded using the prediction block.

Abstract: Encoding and decoding using parametrized motion models are disclosed. A method includes segmenting the video frame with respect to a reference frame resulting in a segmentation, determining a first motion vector for the current block based on the segmentation, determining a second motion vector for the current block using translational motion compensation, and encoding, for the current block, the one of the first motion vector and the second motion vector corresponding to a smaller error. The segmentation includes a segment containing the current block and a parameterized motion model for the segment. Another method includes identifying a parameterized motion model corresponding to a motion model type, associating the parameterized motion model with a segment of a reference frame, and, in response to determining that the current block is encoded using the parameterized motion model, decoding the current block using the parameterized motion model.

Abstract: Generating a compound predictor block of a current block includes generating, for the current block, predictor blocks including a first predictor block formed of first predictor pixels. Using at least a subset of the first predictor pixels, a first modulation value for modulating a first weight to be applied to a first predictor pixel of the first predictor pixels is determined.

Abstract: Restoring a degraded tile of a degraded frame resulting from reconstruction is disclosed. A method includes, for a scaling factor of at least some scaling factors, recursively filtering the degraded tile using the scaling factor to generate a respective restored tile, and determining a respective error for the respective restored tile with respect to the source tile. The method also includes selecting an optimal scaling factor from the at least some scaling factors and encoding, in an encoded bitstream, a scaling parameter based on the optimal scaling factor. The optimal scaling factor corresponding to a smallest respective error. An apparatus includes a processor and non-transitory memory storing instructions. The instructions cause the processor to determine, from an encoded bitstream, a scaling factor, which determines how strongly edges in the degraded tile affect filtering operations, and recursively filter, resulting in a restored tile, the degraded tile using the scaling factor.

Abstract: A peptide-POD with ability to penetrate and deliver fluorophores, siRNA, DNA and quantum dots to cells in culture and retinal and ocular tissues in vivo is provided herein. POD couples to adenovirus vectors, enhancing tropism for certain cells, potentially providing a safer and more efficacious method to deliver molecules to ocular and other tissues in vivo. POD constructs are therapeutic delivery vehicles for treating cells and tissues, including ocular cells and tissues suffering from retinal degeneration.

Abstract: A peptide-POD with ability to penetrate and deliver fluorophores, siRNA, DNA and quantum dots to cells in culture and retinal and ocular tissues in vivo is provided herein. POD couples to adenovirus vectors, enhancing tropism for certain cells, potentially providing a safer and more efficacious method to deliver molecules to ocular and other tissues in vivo. POD constructs are therapeutic delivery vehicles for treating cells and tissues, including ocular cells and tissues suffering from retinal degeneration.