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公开(公告)号：US12072442B2
公开(公告)日：2024-08-27
申请号：US17456045
申请日：2021-11-22
Applicant: NVIDIA Corporation
Inventor： Tommi Koivisto , Pekka Janis , Tero Kuosmanen , Timo Roman , Sriya Sarathy , William Zhang , Nizar Assaf , Colin Tracey
IPC: G06V10/46 , B60W50/00 , G01S7/41 , G05D1/00 , G06F16/35 , G06F18/21 , G06F18/214 , G06F18/23 , G06F18/2413 , G06N3/044 , G06N3/045 , G06N3/084 , G06N20/00 , G06V10/20 , G06V10/44 , G06V10/762 , G06V10/764 , G06V10/77 , G06V10/774 , G06V20/58 , G01S7/48 , G01S13/86 , G01S13/931 , G01S17/931 , G06N3/047 , G06N3/048
CPC classification number: G01S7/417 , B60W50/00 , G05D1/0246 , G06F16/35 , G06F18/214 , G06F18/217 , G06F18/23 , G06F18/2414 , G06N3/044 , G06N3/045 , G06N3/084 , G06N20/00 , G06V10/255 , G06V10/454 , G06V10/46 , G06V10/762 , G06V10/764 , G06V10/7715 , G06V10/774 , G06V20/58 , G06V20/584 , G01S7/412 , G01S7/4802 , G01S13/867 , G01S2013/9318 , G01S2013/9323 , G01S17/931 , G06N3/047 , G06N3/048
Abstract: In various examples, detected object data representative of locations of detected objects in a field of view may be determined. One or more clusters of the detected objects may be generated based at least in part on the locations and features of the cluster may be determined for use as inputs to a machine learning model(s). A confidence score, computed by the machine learning model(s) based at least in part on the inputs, may be received, where the confidence score may be representative of a probability that the cluster corresponds to an object depicted at least partially in the field of view. Further examples provide approaches for determining ground truth data for training object detectors, such as for determining coverage values for ground truth objects using associated shapes, and for determining soft coverage values for ground truth objects.
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Patent Agency Ranking
公开(公告)号：US20190258878A1
公开(公告)日：2019-08-22
申请号：US16277895
申请日：2019-02-15
Applicant: NVIDIA Corporation
Inventor： Tommi Koivisto , Pekka Janis , Tero Kuosmanen , Timo Roman , Sriya Sarathy , William Zhang , Nizar Assaf , Colin Tracey
Abstract: In various examples, detected object data representative of locations of detected objects in a field of view may be determined. One or more clusters of the detected objects may be generated based at least in part on the locations and features of the cluster may be determined for use as inputs to a machine learning model(s). A confidence score, computed by the machine learning model(s) based at least in part on the inputs, may be received, where the confidence score may be representative of a probability that the cluster corresponds to an object depicted at least partially in the field of view. Further examples provide approaches for determining ground truth data for training object detectors, such as for determining coverage values for ground truth objects using associated shapes, and for determining soft coverage values for ground truth objects.
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公开(公告)号：US20240192320A1
公开(公告)日：2024-06-13
申请号：US18582358
申请日：2024-02-20
Applicant: NVIDIA Corporation
Inventor： Tommi Koivisto , Pekka Janis , Tero Kuosmanen , Timo Roman , Sriya Sarathy , William Zhang , Nizar Assaf , Colin Tracey
IPC: G01S7/41 , B60W50/00 , G01S7/48 , G01S13/86 , G01S13/931 , G01S17/931 , G06F16/35 , G06F18/21 , G06F18/214 , G06F18/23 , G06F18/2413 , G06N3/044 , G06N3/045 , G06N3/047 , G06N3/048 , G06N3/084 , G06N20/00 , G06V10/20 , G06V10/44 , G06V10/46 , G06V10/762 , G06V10/764 , G06V10/77 , G06V10/774 , G06V20/58
CPC classification number: G01S7/417 , B60W50/00 , G06F16/35 , G06F18/214 , G06F18/217 , G06F18/23 , G06F18/2414 , G06N3/044 , G06N3/045 , G06N3/084 , G06N20/00 , G06V10/255 , G06V10/454 , G06V10/46 , G06V10/762 , G06V10/764 , G06V10/7715 , G06V10/774 , G06V20/58 , G06V20/584 , G01S7/412 , G01S7/4802 , G01S13/867 , G01S2013/9318 , G01S2013/9323 , G01S17/931 , G06N3/047 , G06N3/048
Abstract: In various examples, detected object data representative of locations of detected objects in a field of view may be determined. One or more clusters of the detected objects may be generated based at least in part on the locations and features of the cluster may be determined for use as inputs to a machine learning model(s). A confidence score, computed by the machine learning model(s) based at least in part on the inputs, may be received, where the confidence score may be representative of a probability that the cluster corresponds to an object depicted at least partially in the field of view. Further examples provide approaches for determining ground truth data for training object detectors, such as for determining coverage values for ground truth objects using associated shapes, and for determining soft coverage values for ground truth objects.
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公开(公告)号：US20220101635A1
公开(公告)日：2022-03-31
申请号：US17456045
申请日：2021-11-22
Applicant: NVIDIA Corporation
Inventor： Tommi Koivisto , Pekka Janis , Tero Kuosmanen , Timo Roman , Sriya Sarathy , William Zhang , Nizar Assaf , Colin Tracey
IPC: G06V20/58 , G06V10/25 , G06V10/774 , G06V10/77 , G06N20/00
Abstract: In various examples, detected object data representative of locations of detected objects in a field of view may be determined. One or more clusters of the detected objects may be generated based at least in part on the locations and features of the cluster may be determined for use as inputs to a machine learning model(s). A confidence score, computed by the machine learning model(s) based at least in part on the inputs, may be received, where the confidence score may be representative of a probability that the cluster corresponds to an object depicted at least partially in the field of view. Further examples provide approaches for determining ground truth data for training object detectors, such as for determining coverage values for ground truth objects using associated shapes, and for determining soft coverage values for ground truth objects.
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公开(公告)号：US11210537B2
公开(公告)日：2021-12-28
申请号：US16277895
申请日：2019-02-15
Applicant: NVIDIA Corporation
Inventor： Tommi Koivisto , Pekka Janis , Tero Kuosmanen , Timo Roman , Sriya Sarathy , William Zhang , Nizar Assaf , Colin Tracey
IPC: G06K9/00 , G06K9/46 , G06K9/62 , B60W50/00 , G06N3/04 , G01S7/41 , G05D1/02 , G06N3/08 , G06K9/32 , G06K9/48 , G01S13/86 , G01S7/48 , G01S17/931 , G01S13/931
Abstract: In various examples, detected object data representative of locations of detected objects in a field of view may be determined. One or more clusters of the detected objects may be generated based at least in part on the locations and features of the cluster may be determined for use as inputs to a machine learning model(s). A confidence score, computed by the machine learning model(s) based at least in part on the inputs, may be received, where the confidence score may be representative of a probability that the cluster corresponds to an object depicted at least partially in the field of view. Further examples provide approaches for determining ground truth data for training object detectors, such as for determining coverage values for ground truth objects using associated shapes, and for determining soft coverage values for ground truth objects.
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公开(公告)号：US20140369554A1
公开(公告)日：2014-12-18
申请号：US14031551
申请日：2013-09-19
Applicant: Nvidia Corporation
Inventor： Elif Albuz , Colin Tracey , Navjot Garg , Yun-Ta Tsai , Dawid Pajak
CPC classification number: G06T5/20 , G06T5/002 , G06T5/008 , G06T11/60 , G06T2207/20124 , G06T2207/20192 , G06T2207/30201
Abstract: A face beautification system and a method of face beautification. On embodiment of the face beautification system includes: (1) a coarse feature detector configured to generate an approximation of facial features in an image, (2) an edge-preserving filter configured to reduce distortions in the approximation, and (3) a feature enhancer operable to selectively filter a facial feature from said approximation and carry out an enhancement.
Abstract translation: 面美化体系和面部美化方法。 面部美化系统的实施例包括：（1）粗糙特征检测器，被配置为生成图像中的面部特征的近似，（2）边缘保留滤波器，被配置为减少近似中的失真，以及（3）特征 增强器可操作以从所述近似选择性地过滤面部特征并执行增强。
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