Aspects of the disclosure provide methods and apparatuses for video encoding/decoding. In some examples, an apparatus for video decoding includes processing circuitry that decodes prediction information for a plurality of first blocks in a current coded picture that is a part of a coded video sequence. The prediction information indicates that the plurality of first blocks is coded in a local illumination compensation (LIC) mode. The processing circuitry selects a neighboring region for each of the plurality of first blocks. The selected neighboring region and the respective first block form a second block. The processing circuitry performs an inter prediction for the plurality of second blocks in parallel. The processing circuitry determines a set of LIC parameters for each of the plurality of first blocks based on the selected neighboring region of the respective first block and reconstructs the plurality of first blocks based on the sets of LIC parameters.

A device may be configured to signal scaling window information according to one or more of the techniques described herein.

A device may be configured to signal scaling window information according to one or more of the techniques described herein.

A method implemented by a video coding apparatus includes applying a neural network (NN) filter to an unfiltered sample of a video unit to generate a filtered sample. The NN filter is based on an NN filter model configured to obtain an attention based on a coding parameter input. The method also includes performing a conversion between a video media file and a bitstream based on the filtered sample that was generated.

Several systems, methods and integrated circuits capable of reducing blocking artifacts in video data are disclosed. In an embodiment, a system for reducing blocking artifacts in video data includes a processing module and a deblocking module. The deblocking module comprises a luma deblocking filter and a chroma deblocking filter configured to filter an edge between adjacent blocks associated with the video data, where a block of the adjacent blocks corresponds to one of a prediction block and a transform block. The processing module is communicatively associated with the deblocking module and is operable to configure at least one filter coefficient corresponding to the chroma deblocking filter based on one or more filter coefficients corresponding to the luma deblocking filter. The processing module is further configured to cause the chroma deblocking filter to filter the edge between the adjacent blocks based on the configured at least one filter coefficient.

Several systems, methods and integrated circuits capable of reducing blocking artifacts in video data are disclosed. In an embodiment, a system for reducing blocking artifacts in video data includes a processing module and a deblocking module. The deblocking module comprises a luma deblocking filter and a chroma deblocking filter configured to filter an edge between adjacent blocks associated with the video data, where a block of the adjacent blocks corresponds to one of a prediction block and a transform block. The processing module is communicatively associated with the deblocking module and is operable to configure at least one filter coefficient corresponding to the chroma deblocking filter based on one or more filter coefficients corresponding to the luma deblocking filter. The processing module is further configured to cause the chroma deblocking filter to filter the edge between the adjacent blocks based on the configured at least one filter coefficient.

Embodiments of video coding systems and methods are described for reducing coding latency introduced by decoder-side motion vector refinement (DMVR). In one example, two non-refined motion vectors are identified for coding of a first block of samples (e.g. a first coding unit) using bi-prediction. One or both of the non-refined motion vectors are used to predict motion information for a second block of samples (e.g. a second coding unit). The two non-refined motion vectors are refined using DMVR, and the refined motion vectors are used to generate a prediction signal of the first block of samples. Such embodiments allow the second block of samples to be coded substantially in parallel with the first block without waiting for completion of DMVR on the first block. In additional embodiments, optical-flow-based techniques are described for motion vector refinement.

Embodiments of video coding systems and methods are described for reducing coding latency introduced by decoder-side motion vector refinement (DMVR). In one example, two non-refined motion vectors are identified for coding of a first block of samples (e.g. a first coding unit) using bi-prediction. One or both of the non-refined motion vectors are used to predict motion information for a second block of samples (e.g. a second coding unit). The two non-refined motion vectors are refined using DMVR, and the refined motion vectors are used to generate a prediction signal of the first block of samples. Such embodiments allow the second block of samples to be coded substantially in parallel with the first block without waiting for completion of DMVR on the first block. In additional embodiments, optical-flow-based techniques are described for motion vector refinement.

An image processing device that updates a pixel value of a processing target image and generates a new image generates a first feature vector based on the processing target image and a first feature map generated with at least one pre-decided filter; updates the processing target image to generate an updated image; generates a second feature vector based on the updated image and a second feature map generated with at least one pre-decided filter; performs quality evaluation of the updated image based on the first and second feature vectors and generates a quality feedback vector which is a vector based on a result of the quality evaluation; performs an encoding amount evaluation on the updated image and generates an encoding amount feedback vector which is a vector based on a result of the encoding amount evaluation; and determines an updating amount in updating of the updated image based on the quality feedback vector and the encoding amount feedback vector.

An image processing device that updates a pixel value of a processing target image and generates a new image generates a first feature vector based on the processing target image and a first feature map generated with at least one pre-decided filter; updates the processing target image to generate an updated image; generates a second feature vector based on the updated image and a second feature map generated with at least one pre-decided filter; performs quality evaluation of the updated image based on the first and second feature vectors and generates a quality feedback vector which is a vector based on a result of the quality evaluation; performs an encoding amount evaluation on the updated image and generates an encoding amount feedback vector which is a vector based on a result of the encoding amount evaluation; and determines an updating amount in updating of the updated image based on the quality feedback vector and the encoding amount feedback vector.