Abstract: A hardware accelerator comprises a PE array, an internal buffer unit, and a data scheduler. The data scheduler obtains multiple image lines from the internal buffer unit and schedules the PE array to sequentially perform MAC (multiply-accumulate) operations on the multiple image lines. There are overlapping pixel lines between adjacent image lines, and the overlapping pixel lines are subjected to MAC operations in both of their adjacent image lines to which they belong. During the MAC operations on each image line, the PEs of the PE array are scheduled to perform MAC operations in tiles on multiple tiles included in each image line. For adjacent tiles, the operation result of the overlapping portion between the previous tile and the subsequent tile is cached, and combined with the operation result of the non-overlapping portion of the subsequent tile to form the MAC operation result of the subsequent tile.

Abstract: A method for processing a video data stream, a video decoding apparatus, and a method for encoding data stream are provided. The method includes: receiving a video data stream; generating a layer list using at least the patch-layer association information, the layer list including a first layer associated with the first view, the first layer being based on a first depth of the first view; assigning a first layer identification to the first layer; updating the view list section by adding the first layer as a second view; selecting a first target view for rendering on an output device; selecting one or more patches using at least the layer list and the patch list section; combining the selected one or more patches to form a first intermediate output frame; and performing post processing using at least the view list section.

Abstract: The present disclosure relates to a method for scheduling computation resources for generating feature maps for video. The method comprises determining runtime for generating feature maps of a reference picture and a predicted picture, determining available computation resources for generating the feature maps, and allocating, based on the runtime, one or more computation resources among the available computation resources for generating the feature maps such that the feature maps are generated at regular time intervals.

Abstract: Embodiments of the disclosure provide resolution-based decoding and encoding methods and a bitstream. The method includes the following. A bitstream is parsed to obtain a current patch. Whether the current patch is a patch whose resolution is to be changed is determined. When the current patch is a patch whose resolution is to be changed, the bitstream is parsed to obtain a scaling-rate parameter of the current patch. A scaling factor for the current patch is determined based on the scaling-rate parameter of the current patch. Coordinates of the current patch in a three-dimension (3D) space coordinate system are obtained based on the scaling factor for the current patch.

Abstract: An encoding method, a decoding method and apparatus are provided. The decoding method includes: according to a code stream, obtaining spliced map set information and video data to be decoded; performing metadata decoding on the spliced map set information, so as to obtain respective auxiliary information in at least two heterogeneous formats; and performing video decoding on the video data, so as to obtain a spliced image, wherein the spliced image is composed of image sub-blocks corresponding to the at least two heterogeneous formats.

Abstract: A method for of encoding an application screen comprises partitioning graphic data into a plurality of graphic layers and classifying each of the plurality of graphic layers as either a screen content (SC) or a non-screen content (non-SC) layer. The method further comprises classifying each of the plurality of graphic layers as either a screen content (SC) or a non-screen content (non-SC) layer. Further, the method comprises rendering and encoding the one or more SC layers using a first codec and the one or more non-SC layers using a second codec.

Abstract: Embodiments of the present application provide encoding and decoding methods, an encoder, a decoder, and a storage medium. The decoding method includes: a decoder decodes a code stream, and determines a first indication parameter; when the first indication parameter indicates that a sub-block image unit that does not include geometric information exists, a second indication parameter corresponding to the sub-block image unit is determined; and when the second indication parameter indicates that the sub-block image unit does not include geometric information, reconstruction processing is performed according to texture information corresponding to the sub-block image unit.

Abstract: The present disclosure discloses a batch computing system and an associated method. The batch computing system includes a memory, a task manager and an inference computer. The memory stores a shared model parameter set common to a plurality of tasks that is generated by fine tuning a shared model and a task-specific parameter set of each task. The inference computer receives a plurality of task requests, derives a data length and a designated task of each task request, and enables the task manager to read a task-specific parameter set and a shared model parameter set corresponding to each task request. The inference computer further assigns task requests corresponding to the shared model to a plurality of computation batches, performs, in batch, the common computation of designated tasks in each batch computation, and performs task-specific computation operations of the designated tasks of each batch computation.

Abstract: A method for processing a video data stream, a video decoding apparatus, and a method for encoding data stream are provided. The method includes: receiving a video data stream; generating a layer list using at least the patch-layer association information, the layer list including a first layer associated with the first view, the first layer being based on a first depth of the first view; assigning a first layer identification to the first layer; updating the view list section by adding the first layer as a second view; selecting a first target view for rendering on an output device; selecting one or more patches using at least the layer list and the patch list section; combining the selected one or more patches to form a first intermediate output frame; and performing post processing using at least the view list section.

Abstract: Transcoding bitrate prediction techniques can include receiving a first encoded content. A transcoder bitrate can be estimated based on regression over a video quality estimator of the first encoded content and a second encoded content. The estimated transcoder bitrate can be utilized to transcoding the first encoded content into the second encoded.

Abstract: A decoding method, a decoder, and an encoder are provided. A view synthesis technology is used to obtain, according to a reference view image, a synthesized image of a view to be encoded, comprising a texture image and a depth image, and a hole filling technology is used to predict hole area information and perform hole filling on the synthesized image of said view to obtain a predicted image.

Abstract: The present disclosure relates to a method for compensating an image. The method comprises estimating transform coefficients of a frequency component for a first image based on the first image, performing a dot multiplication operation between the estimated transform coefficients and a basis function associated with the frequency component to generate a compensation image, and combining the first image and the compensation image to generate a combined image.

Abstract: An image filling method and apparatus, a decoding method and apparatus, an electronic device, and a medium are provided. The image filling method includes: determining an available pixel and an unavailable pixel at the periphery of a void according to the depth of pixels in the peripheral region of the void in an image to be filled, where the depth value of the available pixel is greater than the depth value of the unavailable pixel; and filling the void at least according to the available pixel.

Abstract: A technique includes modifying a neural network model to sparsify the model. The model includes a plurality of kernel element weights, which are parameterized according to a plurality of dimensions. Modifying the model includes, in a given iteration of the plurality of iterations, training the model based on a structure regularization in which kernel element weights that share a dimension in common are removed as a group to create corresponding zero kernel elements in the model; and compressing the model to exclude zero kernel element weights from the model to prepare the model to be trained in another iteration.

Abstract: The present disclosure relates to a system and method for image processing. In some embodiments, an exemplary image processing method includes: receiving an image; compressing, with a compression neural network, the image into a compressed representation; and performing, with a processing neural network, a machine learning task on the compressed representation to generate a learning result. The compression neural network and the processing neural network are jointly trained.

Abstract: The present disclosure relates to a method and an apparatus for map reduce. In some embodiments, an exemplary processing unit includes: a 2-dimensional (2D) processing element (PE) array comprising a plurality of PEs, each PE comprising a first input and a second input, the first inputs of the PEs in a linear array in a first dimension of the PE array being connected in series and the second inputs of the PEs in a linear array in a second dimension of the PE array being connected in parallel, each PE being configured to perform an operation on data from the first input or second input; and a plurality of reduce tree units, each reduce tree unit being coupled with the PEs in a linear array in the first dimension or the second dimension of the PE array and configured to perform a first reduction operation.

Abstract: A method for of encoding an application screen comprises partitioning graphic data into a plurality of graphic layers and classifying each of the plurality of graphic layers as either a screen content (SC) or a non-screen content (non-SC) layer. The method further comprises classifying each of the plurality of graphic layers as either a screen content (SC) or a non-screen content (non-SC) layer. Further, the method comprises rendering and encoding the one or more SC layers using a first codec and the one or more non-SC layers using a second codec.

Abstract: Embodiments of the disclosure provide systems and methods for processing video content. The method can include: receiving raw video data of a video; determining a texture complexity for the video based on the raw video data; determining an encoding mode for the raw video data based on the texture complexity; and encoding the raw video data using the determined encoding mode.

Abstract: The present disclosure relates to a method for compensating an image. The method comprises estimating transform coefficients of a frequency component for a first image based on the first image, performing a dot multiplication operation between the estimated transform coefficients and a basis function associated with the frequency component to generate a compensation image, and combining the first image and the compensation image to generate a combined image.

Abstract: A method for of encoding an application screen comprises partitioning graphic data into a plurality of graphic layers and classifying each of the plurality of graphic layers as either a screen content (SC) or a non-screen content (non-SC) layer. The method further comprises classifying each of the plurality of graphic layers as either a screen content (SC) or a non-screen content (non-SC) layer. Further, the method comprises rendering and encoding the one or more SC layers using a first codec and the one or more non-SC layers using a second codec.