Abstract: Techniques related to accelerated video enhancement using deep learning selectively applied based on video codec information are discussed. Such techniques include applying a deep learning video enhancement network selectively to decoded non-skip blocks that are in low quantization parameter frames, bypassing the deep learning network for decoded skip blocks in low quantization parameter frames, and applying non-deep learning video enhancement to high quantization parameter frames.

Abstract: Techniques related to quantization parameter estimation for coding intra and scene change frames are discussed. Such techniques include generating features based on an intra or scene change frame including a proportion of smooth blocks and one or both of a measure of block variance and a prediction distortion, and applying a machine learning model to generate an estimated quantization parameter for encoding the intra or scene change frame.

Abstract: A method, system, and article is directed to automatic content-dependent image processing algorithm selection.

Abstract: Techniques related to accelerated video enhancement using deep learning selectively applied based on video codec information are discussed. Such techniques include applying a deep learning video enhancement network selectively to decoded non-skip blocks that are in low quantization parameter frames, bypassing the deep learning network for decoded skip blocks in low quantization parameter frames, and applying non-deep learning video enhancement to high quantization parameter frames.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to encode and decode video using quantization matrices. An example apparatus includes interface circuitry to access an input frame of video, quantization matrix syntax encoder circuitry to encode a set of user-defined quantization matrices into a sequence header associated with a sequence of video frames including the input frame, adaptive quantization matrix selector circuitry to select a subset of quantization matrices from a combination of a set of default quantization matrices and the set of user-defined quantization matrices, adaptive segment selector circuitry to select a first one of the subset of quantization matrices for a first segment of the input frame, the input frame to be divided into a plurality of segments including the first segment, and encoder circuitry to quantize transform coefficients of the first segment of the input frame based on the first one of the subset of quantization matrices.

Abstract: An example apparatus for encoding video frames includes a mask selector to select a subset of visual masks according to an actual target compression ratio and GOP configuration and a complexity estimator to estimate a picture level spatial/temporal complexity for a current frame. The example apparatus further includes a GOP adaptive visual mask selector to specify a visual mask from the subset of the visual masks corresponding to the estimated spatial and temporal complexity value a good enough picture QP deriver to derive a good enough picture QP value using the visual mask. The example apparatus also includes an adjustor to adjust the good enough picture QP value based on block level human visual system sensitivity and statistics of already encoded frames to obtain a final human visual system QP map.

Abstract: A display apparatus includes a communication interface configured to communicate with another display apparatus, a display configured to display contents being shared with the other display apparatus and a video call user interface (UI) for a video call with a user of the other display apparatus, and a processor, in response to at least one of a gesture and a voice of the user included in video call data received from the other display apparatus satisfying a predetermined condition, configured to control the display to change a size of the video call UI displayed on the display.

Abstract: A display apparatus includes a communication interface configured to communicate with another display apparatus, a display configured to display contents being shared with the other display apparatus and a video call user interface (UI) for a video call with a user of the other display apparatus, and a processor, in response to at least one of a gesture and a voice of the user included in video call data received from the other display apparatus satisfying a predetermined condition, configured to control the display to change a size of the video call UI displayed on the display.

Abstract: Often when there is a glare on a display screen the user may be able to mitigate the glare by tilting or otherwise moving the screen or changing their viewing position. However, when driving a car there are limited options for overcoming glares on the dashboard, especially when you are driving for a long distance in the same direction. Embodiments are directed to eliminating such glare. Other embodiments are related to mixed reality (MR) and filling in occluded areas.

Abstract: Techniques related to adaptive quantization matrix selection using machine learning for video coding are discussed. Such techniques include applying a machine learning model to generate an estimated quantization parameter for a frame and selecting a set of quantization matrices for encode of the frame from a number of sets of quantization matrices based on the estimated quantization parameter.

Abstract: Techniques related to video coding include content adaptive quantization that provides a selection between objective quality and subjective quality delta QP offsets. An adaptive method generates an objective quality delta QP offset that achieves a best peak signal-to-noise ratio (PSNR) and/or structural similarity (SSIM) score, which refers to a similarity between images. Also, the adaptive method generates a subjective quality delta QP offset that achieves the best video multi-method assessment fusion (VMAF) score and/or multi-scale structural similarity (MSSIM) score.

Abstract: Often when there is a glare on a display screen the user may be able to mitigate the glare by tilting or otherwise moving the screen or changing their viewing position. However, when driving a car there are limited options for overcoming glares on the dashboard, especially when you are driving for a long distance in the same direction. Embodiments are directed to eliminating such glare. Other embodiments are related to mixed reality (MR) and filling in occluded areas.

Abstract: Techniques related to adaptive quantization matrix selection using machine learning for video coding are discussed. Such techniques include applying a machine learning model to generate an estimated quantization parameter for a frame and selecting a set of quantization matrices for encode of the frame from a number of sets of quantization matrices based on the estimated quantization parameter.

Abstract: Techniques related to quantization parameter estimation for coding intra and scene change frames are discussed. Such techniques include generating features based on an intra or scene change frame including a proportion of smooth blocks and one or both of a measure of block variance and a prediction distortion, and applying a machine learning model to generate an estimated quantization parameter for encoding the intra or scene change frame.

Abstract: Techniques related to adaptive quality boosting for low latency video coding are discussed. Such techniques include segmenting each of a number of temporally adjacent video frames into unique high encode quality regions and encoding each of the video frames by applying a coding quality boost to the high encode quality regions relative to other regions of the video frames.

Abstract: Techniques related to video coding include content adaptive quantization that provides a selection between objective quality and subjective quality delta QP offsets.

Abstract: Systems, apparatuses and methods may include a source device that generates a scene change notification in response to a movement of a camera, modifies an encoding scheme associated with the video content captured by the camera in response to the scene change notification, identifies a full-frame difference threshold, wherein scene analysis information includes frame difference data, and compares the frame difference data to an intermediate threshold that is less than the full-frame difference threshold, wherein the scene change notification is generated when the frame difference data exceeds the intermediate threshold. A sink device may obtain transport quality data associated with video content, modify an output parameter of a display based on the transport quality data, determine a view perspective of a still image containing a plurality of image slices, retrieve only a subset of the plurality of image slices based on the view perspective and decode the retrieved subset.

Abstract: Techniques related to adaptive quality boosting for low latency video coding are discussed. Such techniques include segmenting each of a number of temporally adjacent video frames into unique high encode quality regions and encoding each of the video frames by applying a coding quality boost to the high encode quality regions relative to other regions of the video frames.

Abstract: An example apparatus for encoding video frames includes a mask selector to select a subset of visual masks according to an actual target compression ratio and GOP configuration and a complexity estimator to estimate a picture level spatial/temporal complexity for a current frame. The example apparatus further includes a GOP adaptive visual mask selector to specify a visual mask from the subset of the visual masks corresponding to the estimated spatial and temporal complexity value a good enough picture QP deriver to derive a good enough picture QP value using the visual mask. The example apparatus also includes an adjustor to adjust the good enough picture QP value based on block level human visual system sensitivity and statistics of already encoded frames to obtain a final human visual system QP map.

Abstract: Techniques related to quantization parameter estimation for coding intra and scene change frames are discussed. Such techniques include generating features based on an intra or scene change frame including a proportion of smooth blocks and one or both of a measure of block variance and a prediction distortion, and applying a machine learning model to generate an estimated quantization parameter for encoding the intra or scene change frame.