公开(公告)号：US20240296308A1

公开(公告)日：2024-09-05

申请号：US18646852

申请日：2024-04-26

Applicant: SHANGHAITECH UNIVERSITY

Inventor： Yueyang ZHENG ,  Chaolin RAO ,  Minye WU ,  Xin LOU ,  Pingqiang ZHOU ,  Jingyi YU

IPC: G06N3/04

CPC classification number: G06N3/04

Abstract: A computing system for encoding a machine learning model comprises a plurality of layers and a plurality of computation units. A first set of computation units are configured to process data at a first bit width. A second set of computation units are configured to process at a second bit width. The first bit width is higher than the second bit width. A memory is coupled to the computation units. A controller is coupled to the computation units and the memory. The controller is configured to provide instructions for encoding the machine learning model. The first set of computation units are configured to compute a first set of layers and the second set of computation units are configured to compute a second set of layers.

公开(公告)号：US20240013479A1

公开(公告)日：2024-01-11

申请号：US18369904

申请日：2023-09-19

Applicant: SHANGHAITECH UNIVERSITY

Inventor： Minye WU ,  Chaolin RAO ,  Xin LOU ,  Pingqiang ZHOU ,  Jingyi YU

IPC: G06T15/55 ,  G06T15/20 ,  G06T17/20

CPC classification number: G06T15/55 ,  G06T15/20 ,  G06T17/20 ,  G06T2210/56

Abstract: A computer-implemented method includes encoding a radiance field of an object onto a machine learning model; conducting, based on a set of training images of the object, a training process on the machine learning model to obtain a trained machine learning model, wherein the training process includes a first training process using a plurality of first test sample points followed by a second training process using a plurality of second test sample points located within a threshold distance from a surface region of the object; obtaining target view parameters indicating a view direction of the object; obtaining a plurality of rays associated with a target image of the object; obtaining render sample points on the plurality of rays associated with the target image; and rendering, by inputting the render sample points to the trained machine learning model, colors associated with the pixels of the target image.

公开(公告)号：US20240281256A1

公开(公告)日：2024-08-22

申请号：US18646818

申请日：2024-04-26

Applicant: SHANGHAITECH UNIVERSITY

Inventor： Yuhan GU ,  Chaolin RAO ,  Minye WU ,  Xin LOU ,  Pingqiang ZHOU ,  Jingyi YU

IPC: G06F9/38 ,  G06T1/20 ,  G06T15/00

CPC classification number: G06F9/3885 ,  G06T1/20 ,  G06T15/005

Abstract: A computing core for rendering an image computing core comprises a position encoding logic and a plurality of pipeline logics connected in series in a pipeline. The position encoding logic is configured to transform coordinates and directions of sampling points corresponding to a portion of the image into high dimensional representations. The plurality of pipeline logics are configured to output, based on the high dimensional representation of the coordinates and the high dimensional representation of the directions, intensity and color values of pixels corresponding to the portion of the image in one pipeline cycle. The plurality of pipeline logics are configured to run in parallel.

公开(公告)号：US20240104822A1

公开(公告)日：2024-03-28

申请号：US18531755

申请日：2023-12-07

Applicant: SHANGHAITECH UNIVERSITY

Inventor： Chaolin RAO ,  Minye WU ,  Xin LOU ,  Pingqiang ZHOU ,  Jingyi YU

IPC: G06T15/00 ,  G06T7/90

CPC classification number: G06T15/005 ,  G06T7/90 ,  G06T2207/20084

Abstract: An image rendering system comprising a preprocessing unit coupled to a feature extract unit and a color rendering unit over a data bus. The preprocessing unit generates vector representations of spatial coordinates of sample points along camera rays corresponding to pixels of an image to be rendered. The feature extract unit generates a feature map of the image based on the vector representations, color and intensity values of the sample point through a first machine learning model. The color rendering unit renders the image based on the feature map through a second machine learning model. The first machine learning model is different from the second machine learning model.

公开(公告)号：US20240371078A1

公开(公告)日：2024-11-07

申请号：US18574044

申请日：2022-01-11

Applicant: SHANGHAITECH UNIVERSITY

Inventor： Jingyi YU ,  Yuyao ZHANG ,  Xin LOU ,  Qing WU ,  Chaolin RAO ,  Jiawen YANG

IPC: G06T15/08 ,  G06T9/00 ,  G06T19/20

Abstract: An image rendering system for rendering two-dimensional images in real-time. The image rendering system can receive an implicit representation model of a three-dimensional image. The image rendering system can construct, based on voxel coordinates, a three-dimensional image based on the implicit representation model. The image rendering system can rotate the three-dimensional image to an orientation in a computing space based on a user input. The image rendering system can generate a two-dimensional image based on the rotated three-dimensional image.