Disclosed is a method and device for processing Image, and an image transmitting system. The method includes that: data to be transmitted are processed according to a first resolution to obtain first image data, wherein the image resolution represented by each row of image data in the first image data is the first resolution, and the first resolution is the maximum resolution set by a system; and the first image data is folded to obtain second image data, wherein the number of rows of the second image data is greater than that of the first image data, the image resolution represented by each row of image data in the second image data is a second resolution, and the second resolution is less than the first resolution.

A three-dimensional data encoding method includes: generating one or more items of first information each of which is common to two or more frames among a plurality of frames and includes information indicating one or more partial regions included in a frame; generating items of second information each of which is for a different one of the plurality of frames and includes information indicating a feature of a partial point cloud consisting of three-dimensional points of each of the partial regions; and encoding, for each item of data of the partial point cloud, point cloud data of the three-dimensional points. The items of second information include information indicating one of the one or more items of first information.

An image processing system includes: a memory; and a processor coupled to the memory and configured to: generate information that indicates a feature portion that affects image recognition processing, by executing image recognition processing on first image data acquired at a first time; predict information that indicates the feature portion at a second time after the first time, based on the information that indicates the feature portion at the first time; and encode second image data acquired at the second time, by using a compression rate based on the predicted information that indicates the feature portion.

An image processing system includes: a memory; and a processor coupled to the memory and configured to: generate information that indicates a feature portion that affects image recognition processing, by executing image recognition processing on first image data acquired at a first time; predict information that indicates the feature portion at a second time after the first time, based on the information that indicates the feature portion at the first time; and encode second image data acquired at the second time, by using a compression rate based on the predicted information that indicates the feature portion.

Aspects of the disclosure provide methods and apparatuses for mesh coding (e.g., compression and decompression). In some examples, an apparatus for mesh coding includes processing circuitry. The processing circuitry decodes, using a point cloud compression (PCC) decoder and from a bitstream, a point cloud that includes points corresponding to at least one of vertices in a mesh or sampling points of polygons in the mesh. The processing circuitry determines, based on the point cloud, estimated connectivity information of the vertices in the mesh, and generate, a reconstructed mesh frame based on the point cloud and the estimated connectivity information.

Methods, systems and device for efficiently compressing task-oriented dynamic meshes using occupancy networks are described herein. A single trained occupancy network model is able to reconstruct a mesh video using a few additional points per input mesh frame. To optimize the compression of the model and points, the estimated rate to compress the occupancy network is able to be included in the loss function. This minimizes the number of bits to encode the model, while it tries to reproduce the meshes as well as possible. An adaptive subsampling per input mesh is added to optimize the mesh reconstruction and the N-point point clouds compression. To optimize the model to perform a particular task, a metric is added to the cost function that takes this task into account.

A transaction card construction and computer-implemented methods for a transaction card are described. The transaction card has vector-formatted visible information applied by a laser machining system. In some embodiments, systems and methods are disclosed for enabling the sourcing of visible information using a scalable vector format The systems and methods may receive a request to add visible information to a transaction card and capture an image of the visible information. The systems and methods may capture data representing the image. The systems and methods may also determine an ambient color saturation of the image. Further, systems and methods may translate the image based on the ambient color saturation of the image. The systems and methods may also map the translated image to a bounding box and convert the mapped image into vector format. In addition, the systems and methods may provide the converted image to a laser machining system.

A transaction card construction and computer-implemented methods for a transaction card are described. The transaction card has vector-formatted visible information applied by a laser machining system. In some embodiments, systems and methods are disclosed for enabling the sourcing of visible information using a scalable vector format The systems and methods may receive a request to add visible information to a transaction card and capture an image of the visible information. The systems and methods may capture data representing the image. The systems and methods may also determine an ambient color saturation of the image. Further, systems and methods may translate the image based on the ambient color saturation of the image. The systems and methods may also map the translated image to a bounding box and convert the mapped image into vector format. In addition, the systems and methods may provide the converted image to a laser machining system.

Embodiments are generally directed to compression in machine learning and deep learning processing. An embodiment of an apparatus for compression of untyped data includes a graphical processing unit (GPU) including a data compression pipeline, the data compression pipeline including a data port coupled with one or more shader cores, wherein the data port is to allow transfer of untyped data without format conversion, and a 3D compression/decompression unit to provide for compression of untyped data to be stored to a memory subsystem and decompression of untyped data from the memory subsystem.

The present disclosure relates to an information processing apparatus and method capable of suppressing an increase in load of reproduction processing.

To generate, by using tile identification information indicating a tile of a point cloud corresponding to a data unit of a bitstream of the point cloud expressing an object having a three-dimensional shape as a set of points, tile management information that is information for managing the tile corresponding to a subsample including a single or a plurality of consecutive data units of the bitstream stored as a sample in a file, and to generate the file that stores the bitstream and the tile management information. The present disclosure can be applied to, for example, an information processing apparatus, an information processing method, or the like.