POINT CLOUD ATTRIBUTE ENCODING METHOD, DECODING METHOD, ENCODING DEVICE, AND DECODING DEVICE

    公开(公告)号:US20230419554A1

    公开(公告)日:2023-12-28

    申请号:US18252872

    申请日:2020-11-27

    CPC classification number: G06T9/001 G06T9/40

    Abstract: A point cloud attribute encoding method, a decoding method, an encoding device and a decoding device are disclosed, the point cloud attribute encoding method including: constructing an N-layer binary tree by partitioning a target point cloud according to positions of points within the point cloud, N being an integer greater than 1; for a target node at layer P of the binary tree, obtaining child nodes of the target node, determining a first attribute coefficient and second attribute coefficients of the target node by transforming first attribute coefficients of the child nodes, P being an integer greater than or equal to 1 and less than or equal to N−1; using the first attribute coefficient of a root node and the second attribute coefficients of each target node in the binary tree as output coefficients of the point cloud attribute encoding method.

    Point Cloud Attribute Encoding Method and Apparatus, and Point Cloud Attribute Decoding Method and Apparatus

    公开(公告)号:US20240371046A1

    公开(公告)日:2024-11-07

    申请号:US18683359

    申请日:2022-08-23

    Abstract: A point cloud attribute encoding method and apparatus, decoding method and apparatus are disclosed. The point cloud attribute encoding method includes: sorting point cloud data to be encoded to obtain sorted point cloud data; constructing a multilayer structure based on the sorted point cloud data and distances between the sorted point cloud data; obtaining an encoding mode corresponding to each of nodes in the multilayer structure. The encoding mode corresponding to each of the nodes is a direct encoding mode, a predictive encoding mode, or a transform encoding mode. The predictive encoding mode is to encode a node based on information of a neighboring node corresponding to the node. The transform encoding mode is to encode the node based on a transform matrix; and encoding point cloud attributes for each of the nodes based on the multilayer structure and the respective encoding mode.

    Method and system for achieving optimal separable convolutions

    公开(公告)号:US12045310B2

    公开(公告)日:2024-07-23

    申请号:US17469274

    申请日:2021-09-08

    CPC classification number: G06F18/21 G06N3/02

    Abstract: Disclosed is a method and system for achieving optimal separable convolutions, the method is applied to image analyzing and processing and comprises steps of: inputting an image to be analyzed and processed; calculating three sets of parameters of a separable convolution: an internal number of groups, a channel size and a kernel size of each separated convolution, and achieving optimal separable convolution process; and performing deep neural network image process. The method and system in the present disclosure adopts implementation of separable convolution which efficiently reduces a computational complexity of deep neural network process. Comparing to the FFT and low rank approximation approaches, the method and system disclosed in the present disclosure is efficient for both small and large kernel sizes and shall not require a pre-trained model to operate on and can be deployed to applications where resources are highly constrained.

    On-Chip Wavefront Sensor, Optical Chip, and Communication Device

    公开(公告)号:US20240039628A1

    公开(公告)日:2024-02-01

    申请号:US18278250

    申请日:2021-06-28

    CPC classification number: H04B10/0795 G01J2009/002

    Abstract: An on-chip wavefront sensor, an optical chip, and a communication device are disclosed. The on-chip wavefront sensor includes an antenna array configured for separating received spatial light to obtain a plurality of sub-light spots; a reference light source module configured for generating a plurality of intrinsic light beams; a phase shifter array configured for performing phase shifting processing on the intrinsic light beams to obtain reference light; and an optical detection module configured for performing coherent balanced detection according to the reference light and the sub-light spots to obtain a photocurrent corresponding to each of the sub-light spots.

    MANY-TO-MANY LASER COMMUNICATION NETWORKING DEVICE AND METHOD

    公开(公告)号:US20230353242A1

    公开(公告)日:2023-11-02

    申请号:US18342115

    申请日:2023-06-27

    CPC classification number: H04B10/118 H04B10/503

    Abstract: Disclosed are a many-to-many laser communication networking device and a method. The device includes: an optical field array control module, a transceiver lens array module, an array phase detection module, an array characteristic splitting module, a beam switching array module and a signal transmission module. The optical field array control module is configured to receive a plurality of beams of laser light with different angles, and adjust the corresponding angle of the laser. The transceiver lens array module is configured to convert the angle-adjusted laser into beams of second optical fiber light. The array characteristic splitting module is configured to analyze the second optical fiber light to obtain the second characteristic information. The beam switching array module is configured to control the second optical fiber light to be demodulated into baseband signals via a first path or to be forwarded via a second path according to the second characteristic information.

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