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11.发明授权公开(公告)号：US12124533B2
公开(公告)日：2024-10-22
申请号：US17482875
申请日：2021-09-23
Applicant: Intel Corporation
Inventor： Anbang Yao , Ming Lu , Yikai Wang , Scott Janus , Sungye Kim
IPC: G06F18/2136 , G06T11/00
CPC classification number: G06F18/2136 , G06T11/00 , G06T2207/20076 , G06T2207/20081
Abstract: Embodiments are generally directed to methods and apparatuses of spatially sparse convolution module for visual rendering and synthesis. An embodiment of a method for image processing, comprising: receiving an input image by a convolution layer of a neural network to generate a plurality of feature maps; performing spatially sparse convolution on the plurality of feature maps to generate spatially sparse feature maps; and upsampling the spatially sparse feature maps to generate an output image.
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公开(公告)号：US11915450B2
公开(公告)日：2024-02-27
申请号：US17396633
申请日：2021-08-06
Applicant: Intel Corporation
Inventor： Yiwei He , Ming Lu , Haihua Lin , Liwei Liao , Jiansheng Chen , Xiaofeng Tong , Qiang Li , Wenlong Li
IPC: G06T7/73 , G06T15/20 , G06T7/292 , G06V10/44 , G06V20/40 , G06V20/64 , G06V40/10 , G06F18/214 , G06V30/10
CPC classification number: G06T7/75 , G06F18/2148 , G06T7/292 , G06T15/205 , G06V10/457 , G06V20/42 , G06V20/64 , G06V40/103 , G06T2207/30224 , G06V30/10
Abstract: Embodiments are generally directed to methods and apparatuses for determining a frontal body orientation. An embodiment of a method for determining a three-dimensional (3D) orientation of frontal body of a player comprises: detecting each of a plurality of players in each of a plurality of frames captured by a plurality of cameras; for each of the plurality of cameras, tracking each of the plurality of players between continuous frames captured by the camera; and associating the plurality of frames captured by the plurality of cameras to generate the 3D orientation of each of the plurality of players.
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公开(公告)号：US11869171B2
公开(公告)日：2024-01-09
申请号：US17090170
申请日：2020-11-05
Applicant: Intel Corporation
Inventor： Anbang Yao , Ming Lu , Yikai Wang , Xiaoming Chen , Junjie Huang , Tao Lv , Yuanke Luo , Yi Yang , Feng Chen , Zhiming Wang , Zhiqiao Zheng , Shandong Wang
CPC classification number: G06T5/002 , G06N3/04 , G06T2207/20081 , G06T2207/20084
Abstract: Embodiments are generally directed to an adaptive deformable kernel prediction network for image de-noising. An embodiment of a method for de-noising an image by a convolutional neural network implemented on a compute engine, the image including a plurality of pixels, the method comprising: for each of the plurality of pixels of the image, generating a convolutional kernel having a plurality of kernel values for the pixel; generating a plurality of offsets for the pixel respectively corresponding to the plurality of kernel values, each of the plurality of offsets to indicate a deviation from a pixel position of the pixel; determining a plurality of deviated pixel positions based on the pixel position of the pixel and the plurality of offsets; and filtering the pixel with the convolutional kernel and pixel values of the plurality of deviated pixel positions to obtain a de-noised pixel.
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公开(公告)号：US11816894B2
公开(公告)日：2023-11-14
申请号：US17485411
申请日：2021-09-25
Applicant: Intel Corporation
Inventor： Haihua Lin , Xiaofeng Tong , Wenlong Li , Ming Lu , Jiansheng Chen , Liwei Liao
CPC classification number: G06V20/42 , G06T7/248 , G06V10/462 , G06V10/95 , G06V20/46 , G06V40/23 , G06T2207/30224
Abstract: Embodiments are generally directed to methods and apparatuses for determining a game status. An embodiment of a method for determining a game status comprises: detecting players and a ball in a plurality of continuous frames captured by a plurality of cameras; obtaining tracking data of the players and the ball of the plurality of continuous frames; and determining a game status for each of the plurality of continuous frames based on the tracking data of the players and the ball of the plurality of continuous frames.
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公开(公告)号：US20220292825A1
公开(公告)日：2022-09-15
申请号：US17626994
申请日：2019-08-13
Applicant: Intel Corporation
Inventor： Yikai Fang , Qiang Li , Wenlong Li , Haihua Lin , Chen Ling , Ming Lu , Hongzhi Tao , Xiaofeng Tong , Yumeng Wang
Abstract: Methods, systems and apparatuses may provide for technology that selects a player from a plurality of players based on an automated analysis of two-dimensional (2D) video data associated with a plurality of cameras, wherein the selected player is nearest to a projectile depicted in the 2D video data. The technology may also track a location of the selected player over a subsequent plurality of frames in the 2D video data and estimate a location of the projectile based on the location of the selected player over the subsequent plurality of frames.
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Patent Agency Ranking
公开(公告)号：US20220184481A1
公开(公告)日：2022-06-16
申请号：US17438393
申请日：2019-07-31
Applicant: Intel Corporation
Inventor： Xiaofeng Tong , Qiang Li , Wenlong Li , Haihua Lin , Ming Lu
Abstract: An example system for game status detection and trajectory fusion is described herein. The system includes a tracker to obtain a ball position and a player position based on images from a plurality of cameras and a fusion controller to combine multiple trajectories that are detected via the ball position to obtain a fused trajectory. The system also includes a finite state machine configured to model a game pattern, wherein a game status is determined via the ball position, the player position and the fused trajectory as input to the finite state machine.
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公开(公告)号：US11308675B2
公开(公告)日：2022-04-19
申请号：US16971132
申请日：2018-06-14
Applicant: Intel Corporation
Inventor： Shandong Wang , Ming Lu , Anbang Yao , Yurong Chen
Abstract: Techniques related to capturing 3D faces using image and temporal tracking neural networks and modifying output video using the captured 3D faces are discussed. Such techniques include applying a first neural network to an input vector corresponding to a first video image having a representation of a human face to generate a morphable model parameter vector, applying a second neural network to an input vector corresponding to a first and second temporally subsequent to generate a morphable model parameter delta vector, generating a 3D face model of the human face using the morphable model parameter vector and the morphable model parameter delta vector, and generating output video using the 3D face model.
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公开(公告)号：US20220076447A1
公开(公告)日：2022-03-10
申请号：US17396633
申请日：2021-08-06
Applicant: Intel Corporation
Inventor： Yiwei He , Ming Lu , Haihua Lin , Liwei Liao , Jiansheng Chen , Xiaofeng Tong , Qiang Li , Wenlong Li
Abstract: Embodiments are generally directed to methods and apparatuses for determining a frontal body orientation. An embodiment of a method for determining a three-dimensional (3D) orientation of frontal body of a player comprises: detecting each of a plurality of players in each of a plurality of frames captured by a plurality of cameras; for each of the plurality of cameras, tracking each of the plurality of players between continuous frames captured by the camera; and associating the plurality of frames captured by the plurality of cameras to generate the 3D orientation of each of the plurality of players.
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19.发明申请公开(公告)号：US20200082264A1
公开(公告)日：2020-03-12
申请号：US16609735
申请日：2018-05-22
Applicant: INTEL CORPORATION
Inventor： Yiwen Guo , Anbang Yao , Hao Zhao , Ming Lu , Yurong CHEN
Abstract: Methods and apparatus are disclosed for enhancing a neural network using binary tensor and scale factor pairs. For one example, a method of optimizing a trained convolutional neural network (CNN) includes initializing an approximation residue as a trained weight tensor for the trained CNN. A plurality of binary tensors and scale factor pairs are determined. The approximation residue is updated using the binary tensors and scale factor pairs.
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20.发明申请公开(公告)号：US20250061172A1
公开(公告)日：2025-02-20
申请号：US18883195
申请日：2024-09-12
Applicant: Intel Corporation
Inventor： Anbang Yao , Ming Lu , Yikai Wang , Scott Janus , Sungye Kim
IPC: G06F18/2136 , G06T11/00
Abstract: Embodiments are generally directed to methods and apparatuses of spatially sparse convolution module for visual rendering and synthesis. An embodiment of a method for image processing, comprising: receiving an input image by a convolution layer of a neural network to generate a plurality of feature maps; performing spatially sparse convolution on the plurality of feature maps to generate spatially sparse feature maps; and upsampling the spatially sparse feature maps to generate an output image.
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