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公开(公告)号：US20240070874A1
公开(公告)日：2024-02-29
申请号：US18135654
申请日：2023-04-17
Applicant: NVIDIA Corporation
Inventor： Muhammed Kocabas , Ye Yuan , Umar Iqbal , Pavlo Molchanov , Jan Kautz
CPC classification number: G06T7/20 , G06T7/70 , G06T2207/20084 , G06T2207/30196 , G06T2207/30252 , G06T2210/12
Abstract: Estimating motion of a human or other object in video is a common computer task with applications in robotics, sports, mixed reality, etc. However, motion estimation becomes difficult when the camera capturing the video is moving, because the observed object and camera motions are entangled. The present disclosure provides for joint estimation of the motion of a camera and the motion of articulated objects captured in video by the camera.
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公开(公告)号：US20230368501A1
公开(公告)日：2023-11-16
申请号：US18114177
申请日：2023-02-24
Applicant: NVIDIA Corporation
Inventor： Seonwook Park , Shalini De Mello , Pavlo Molchanov , Umar Iqbal , Jan Kautz
IPC: G06V10/772 , G06F7/57 , G06F17/18 , G06N3/088 , G06N3/045 , G06N3/047 , G06V10/774 , G06V10/82
CPC classification number: G06V10/772 , G06F7/57 , G06F17/18 , G06N3/088 , G06N3/045 , G06N3/047 , G06V10/774 , G06V10/82
Abstract: A neural network is trained to identify one or more features of an image. The neural network is trained using a small number of original images, from which a plurality of additional images are derived. The additional images generated by rotating and decoding embeddings of the image in a latent space generated by an autoencoder. The images generated by the rotation and decoding exhibit changes to a feature that is in proportion to the amount of rotation.
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公开(公告)号：US11748887B2
公开(公告)日：2023-09-05
申请号：US16378464
申请日：2019-04-08
Applicant: NVIDIA Corporation
Inventor： Varun Jampani , Wei-Chih Hung , Sifei Liu , Pavlo Molchanov , Jan Kautz
IPC: G06V10/00 , G06T7/11 , G06T7/143 , G06F17/15 , G06N3/088 , G06F18/40 , G06N3/045 , G06N3/047 , G06V10/764 , G06V10/82 , G06V10/94 , G06V20/40
CPC classification number: G06T7/11 , G06F17/15 , G06F18/40 , G06N3/045 , G06N3/047 , G06N3/088 , G06T7/143 , G06V10/764 , G06V10/82 , G06V10/945 , G06V20/41
Abstract: Systems and methods to detect one or more segments of one or more objects within one or more images based, at least in part, on a neural network trained in an unsupervised manner to infer the one or more segments. Systems and methods to help train one or more neural networks to detect one or more segments of one or more objects within one or more images in an unsupervised manner.
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公开(公告)号：US20220292360A1
公开(公告)日：2022-09-15
申请号：US17201768
申请日：2021-03-15
Applicant: NVIDIA Corporation
Inventor： Maying Shen , Pavlo Molchanov , Hongxu Yin , Jose Manuel Alvarez Lopez
Abstract: Apparatuses, systems, and techniques to remove one or more nodes of a neural network. In at least one embodiment, one or more nodes of a neural network are removed, based on, for example, whether the one or more nodes are likely to affect performance of the neural network.
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公开(公告)号：US20220067525A1
公开(公告)日：2022-03-03
申请号：US17002660
申请日：2020-08-25
Applicant: NVIDIA Corporation
Inventor： Dilip Sequeira , Pavlo Molchanov , Gregory Heinrich , Edvard Olav Valter Fagerholm
Abstract: Apparatuses, systems, and techniques to reduce a size of neural networks. In at least one embodiment, a size of a neural network is reduced by at least removing one or more neurons of the neural network and adjusting one or more layers of the neural network to compensate for the removed one or more neurons.
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Patent Agency Ranking
公开(公告)号：US20210271977A1
公开(公告)日：2021-09-02
申请号：US17325024
申请日：2021-05-19
Applicant: NVIDIA Corporation
Inventor： Xiaodong Yang , Pavlo Molchanov , Jan Kautz
Abstract: A method, computer readable medium, and system are disclosed for visual sequence learning using neural networks. The method includes the steps of replacing a non-recurrent layer within a trained convolutional neural network model with a recurrent layer to produce a visual sequence learning neural network model and transforming feedforward weights for the non-recurrent layer into input-to-hidden weights of the recurrent layer to produce a transformed recurrent layer. The method also includes the steps of setting hidden-to-hidden weights of the recurrent layer to initial values and processing video image data by the visual sequence learning neural network model to generate classification or regression output data.
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公开(公告)号：US10860859B2
公开(公告)日：2020-12-08
申请号：US16202703
申请日：2018-11-28
Applicant: NVIDIA Corporation
Inventor： Xiaodong Yang , Pavlo Molchanov , Jan Kautz , Behrooz Mahasseni
Abstract: Detection of activity in video content, and more particularly detecting in video start and end frames inclusive of an activity and a classification for the activity, is fundamental for video analytics including categorizing, searching, indexing, segmentation, and retrieval of videos. Existing activity detection processes rely on a large set of features and classifiers that exhaustively run over every time step of a video at multiple temporal scales, or as a small improvement computationally propose segments of the video on which to perform classification. These existing activity detection processes, however, are computationally expensive, particularly when trying to achieve activity detection accuracy, and moreover are not configurable for any particular time or computation budget. The present disclosure provides a time and/or computation budget-aware method for detecting activity in video that relies on a recurrent neural network implementing a learned policy.
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公开(公告)号：US10783393B2
公开(公告)日：2020-09-22
申请号：US16006709
申请日：2018-06-12
Applicant: NVIDIA Corporation
Inventor： Pavlo Molchanov , Stephen Walter Tyree , Jan Kautz , Sina Honari
Abstract: A method, computer readable medium, and system are disclosed for sequential multi-tasking to generate coordinates of landmarks within images. The landmark locations may be identified on an image of a human face and used for emotion recognition, face identity verification, eye gaze tracking, pose estimation, etc. A neural network model processes input image data to generate pixel-level likelihood estimates for landmarks in the input image data and a soft-argmax function computes predicted coordinates of each landmark based on the pixel-level likelihood estimates.
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公开(公告)号：US10481696B2
公开(公告)日：2019-11-19
申请号：US15060545
申请日：2016-03-03
Applicant: NVIDIA Corporation
Inventor： Pavlo Molchanov , Shalini Gupta , Kihwan Kim , Kari Pulli
IPC: G06F3/01 , G01S13/42 , G01S7/35 , G01S7/41 , G01S13/58 , G06K9/00 , G06K9/62 , G06K9/78 , B60R11/04 , G06N3/04 , G06N3/08
Abstract: An apparatus and method for radar based gesture detection. The apparatus includes a processing element and a transmitter configured to transmit radar signals. The transmitter is coupled to the processing element. The apparatus further includes a plurality of receivers configured to receive radar signal reflections, where the plurality of receivers is coupled to the processing element. The transmitter and plurality of receivers are configured for short range radar and the processing element is configured to detect a hand gesture based on the radar signal reflections received by the plurality of receivers.
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公开(公告)号：US10168785B2
公开(公告)日：2019-01-01
申请号：US15060525
申请日：2016-03-03
Applicant: NVIDIA Corporation
Inventor： Pavlo Molchanov , Shalini Gupta , Kihwan Kim , Kari Pulli
IPC: G06F3/01 , G01S13/42 , G01S7/35 , G01S7/41 , G01S13/58 , B60R11/04 , G06K9/00 , G06K9/62 , G06K9/78 , G06N3/04 , G06N3/08
Abstract: An apparatus and method for gesture detection and recognition. The apparatus includes a processing element, a radar sensor, a depth sensor, and an optical sensor. The radar sensor, the depth sensor, and the optical sensor are coupled to the processing element, and the radar sensor, the depth sensor, and the optical sensor are configured for short range gesture detection and recognition. The processing element is further configured to detect and recognize a hand gesture based on data acquired with the radar sensor, the depth sensor, and the optical sensor.
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