An example device for processing point cloud data includes a memory configured to store the point cloud data and one or more processors implemented in circuitry and coupled to the memory. The one or more processors are configured to count a number of edges of a cube of point cloud data comprising a vertex. The one or more processors are configured to set a variable based on a total of the counting. The one or more processors are also configured to process the point cloud data based on the variable.

Neural image compression with adaptive intra-prediction is performed by at least one processor and includes receiving an optimal partition and a compressed representation of an input comprising a first set of blocks, for each block in the first set of blocks, receiving a block selection signal indicating one of a first recovered block and a second recovered block as a currently recovered block, and based on the received block selection signal, performing one of a first recovery and a second recovery, and merging the currently recovered blocks to obtain a reconstructed image. The first recovery comprises compute the first recovered block based on a respective block in the first set of blocks directly. The second recovery comprises generating a recovered residual based on a computed residual, partitioning the first predicted block and adding the recovered residual to obtain the second recovered block.

Systems and methods for providing a framework for predicting future frames using diverse sampling are provided. In one embodiment, a method for predicting future frames includes receiving a video having a first frame from a first time and a second frame from a second time. The first frame and the second frame are represented in image space. The method also includes updating a prediction model based on the video. The method further includes determining whether a stopping condition is satisfied. In response to determining that the stopping condition has been satisfied, the method includes generating a plurality of future frames for a third time after the second time. The plurality of future frames is generated based on a normalized distance metric that preserves distance of samples in the latent space to the image space. The method yet further includes selecting a candidate frame from the plurality of future frames.

Systems, methods, and instrumentalities are disclosed relating to intra prediction of a video signal based on mode-dependent subsampling. A block of coefficients associated with a first sub block of a video block, one or more blocks of coefficients associated with one or more remaining sub blocks of the video block, and an indication of a prediction mode for the video block may be received. One or more interpolating techniques, a predicted first sub block, and the predicted sub blocks of the one or more remaining sub blocks may be determined. A reconstructed first sub block and one or more reconstructed remaining sub blocks may be generated. A reconstructed video block may be formed based on the prediction mode, the reconstructed first sub block, and the one or more reconstructed remaining sub blocks.

Systems, methods, and instrumentalities are disclosed relating to intra prediction of a video signal based on mode-dependent subsampling. A block of coefficients associated with a first sub block of a video block, one or more blocks of coefficients associated with one or more remaining sub blocks of the video block, and an indication of a prediction mode for the video block may be received. One or more interpolating techniques, a predicted first sub block, and the predicted sub blocks of the one or more remaining sub blocks may be determined. A reconstructed first sub block and one or more reconstructed remaining sub blocks may be generated. A reconstructed video block may be formed based on the prediction mode, the reconstructed first sub block, and the one or more reconstructed remaining sub blocks.

The present disclosure relates to advanced image signal processing technology including: i) rapid localization for machine-readable indicia including, e.g., 1-D and 2-D barcodes; and ii) barcode reading and decoders. One claim recites: an image processing method comprising: obtaining 2-dimensional (2D) image data representing a 1-dimensional (1D) barcode within a first image area; generating a plurality of scanlines across the first image area; for each of the plurality of scanlines, synchronizing the scanline, including decoding an initial set of numerical digits represented by the scanline, in which said synchronizing provides a scale estimate for the scanline; using a path decoder to decode remaining numerical digits within the scanline, the path decoder decoding multiple numerical digits in groups; and providing decoded numerical digits as an identifier represented by the scanline. Of course, other combinations and claims are described within the present disclosure.

The present disclosure relates to advanced image signal processing technology including: i) rapid localization for machine-readable indicia including, e.g., 1-D and 2-D barcodes; and ii) barcode reading and decoders. One claim recites: an image processing method comprising: obtaining 2-dimensional (2D) image data representing a 1-dimensional (1D) barcode within a first image area; generating a plurality of scanlines across the first image area; for each of the plurality of scanlines, synchronizing the scanline, including decoding an initial set of numerical digits represented by the scanline, in which said synchronizing provides a scale estimate for the scanline; using a path decoder to decode remaining numerical digits within the scanline, the path decoder decoding multiple numerical digits in groups; and providing decoded numerical digits as an identifier represented by the scanline. Of course, other combinations and claims are described within the present disclosure.

Example methods, apparatus, systems and articles of manufacture (e.g., physical storage media) to implement multi-plane image (MPI) compression are disclosed. Example apparatus disclosed herein include an interface to access an input multiplane image stack corresponding to a source camera viewpoint, the input multiplane image stack including a plurality of texture images and a corresponding plurality of alpha images, ones of the alpha images including pixel values representative of transparency of corresponding pixels in respective ones of the texture images. Disclosed example apparatus also include a compressed image encoder to at least one of (i) convert the plurality of texture images to a single composite texture image to generate a compressed multiplane image stack, or (ii) convert the plurality of alpha images to a single composite alpha image to generate the compressed multiplane image stack. In some disclosed examples, the interface is to output the compressed multiplane image stack.

A video coding method includes the following. A bitstream is decoded to obtain a feature map of a target object in a current picture. The feature map of the target object in the current picture is input to a visual task network and a prediction result output by the visual task network is obtained.

A video coding method includes the following. A bitstream is decoded to obtain a feature map of a target object in a current picture. The feature map of the target object in the current picture is input to a visual task network and a prediction result output by the visual task network is obtained.