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公开(公告)号：US20210132688A1
公开(公告)日：2021-05-06
申请号：US16669863
申请日：2019-10-31
Applicant: Nvidia Corporation
Inventor： Joohwan Kim , Josef Spjut , Iuri Frosio , Orazio Gallo , Ekta Prashnani
Abstract: Apparatuses, systems, and techniques are presented to modify media content using inferred attention. In at least one embodiment, a network is trained to predict a gaze of one or more users on one or more image features based, at least in part, on one or more prior gazes of the one or more users, wherein the prediction is to be used to modify at least one of the one or more image features.
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公开(公告)号：US10311589B2
公开(公告)日：2019-06-04
申请号：US15823370
申请日：2017-11-27
Applicant: NVIDIA Corporation
Inventor： Gregory P. Meyer , Shalini Gupta , Iuri Frosio , Nagilla Dikpal Reddy , Jan Kautz
Abstract: One embodiment of the present invention sets forth a technique for estimating a head pose of a user. The technique includes acquiring depth data associated with a head of the user and initializing each particle included in a set of particles with a different candidate head pose. The technique further includes performing one or more optimization passes that include performing at least one iterative closest point (ICP) iteration for each particle and performing at least one particle swarm optimization (PSO) iteration. Each ICP iteration includes rendering the three-dimensional reference model based on the candidate head pose associated with the particle and comparing the three-dimensional reference model to the depth data. Each PSO iteration comprises updating a global best head pose associated with the set of particles and modifying at least one candidate head pose. The technique further includes modifying a shape of the three-dimensional reference model based on depth data.
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Patent Agency Ranking
公开(公告)号：US10192525B2
公开(公告)日：2019-01-29
申请号：US15421364
申请日：2017-01-31
Applicant: NVIDIA Corporation
Inventor： Iuri Frosio , Jan Kautz
Abstract: A system, method and computer program product are provided for generating one or more values for a signal patch using neighboring patches collected based on a distance dynamically computed from a noise distribution of the signal patch. In use, a reference patch is identified from a signal, and a reference distance is computed based on a noise distribution in the reference patch. Neighbor patches are then collected from the signal based on the computed reference distance from the reference patch. Further, the collected neighbor patches are processed with the reference patch to generate one or more values for the reference patch.
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公开(公告)号：US11989642B2
公开(公告)日：2024-05-21
申请号：US17952866
申请日：2022-09-26
Applicant: NVIDIA Corporation
Inventor： Ruben Villegas , Alejandro Troccoli , Iuri Frosio , Stephen Tyree , Wonmin Byeon , Jan Kautz
Abstract: In various examples, historical trajectory information of objects in an environment may be tracked by an ego-vehicle and encoded into a state feature. The encoded state features for each of the objects observed by the ego-vehicle may be used—e.g., by a bi-directional long short-term memory (LSTM) network—to encode a spatial feature. The encoded spatial feature and the encoded state feature for an object may be used to predict lateral and/or longitudinal maneuvers for the object, and the combination of this information may be used to determine future locations of the object. The future locations may be used by the ego-vehicle to determine a path through the environment, or may be used by a simulation system to control virtual objects—according to trajectories determined from the future locations—through a simulation environment.
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公开(公告)号：US20220180173A1
公开(公告)日：2022-06-09
申请号：US17114144
申请日：2020-12-07
Applicant: NVIDIA Corporation
Inventor： Aditya Jonnalagadda , Iuri Frosio , Joohwan Kim , Seth Schneider
Abstract: Apparatuses, systems, and techniques to detect cheating in a computer game. In at least one embodiment, one or more circuits use one or more neural networks to detect cheating by one or more users of a computer game based, at least in part, on one or more images generated by the computer game.
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公开(公告)号：US20210124353A1
公开(公告)日：2021-04-29
申请号：US17140738
申请日：2021-01-04
Applicant: Nvidia Corporation
Inventor： Bill Dally , Stephen Tyree , Iuri Frosio , Alejandro Troccoli
Abstract: Sensors measure information about actors or other objects near an object, such as a vehicle or robot, to be maneuvered. Sensor data is used to determine a sequence of possible actions for the maneuverable object to achieve a determined goal. For each possible action to be considered, one or more probable reactions of the nearby actors or objects are determined. This can take the form of a decision tree in some embodiments, with alternative levels of nodes corresponding to possible actions of the present object and probable reactive actions of one or more other vehicles or actors. Machine learning can be used to determine the probabilities, as well as to project out the options along the paths of the decision tree including the sequences. A value function is used to generate a value for each considered sequence, or path, and a path having a highest value is selected for use in determining how to navigate the object.
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公开(公告)号：US20200082248A1
公开(公告)日：2020-03-12
申请号：US16564978
申请日：2019-09-09
Applicant: NVIDIA Corporation
Inventor： Ruben Villegas , Alejandro Troccoli , Iuri Frosio , Stephen Tyree , Wonmin Byeon , Jan Kautz
Abstract: In various examples, historical trajectory information of objects in an environment may be tracked by an ego-vehicle and encoded into a state feature. The encoded state features for each of the objects observed by the ego-vehicle may be used—e.g., by a bi-directional long short-term memory (LSTM) network—to encode a spatial feature. The encoded spatial feature and the encoded state feature for an object may be used to predict lateral and/or longitudinal maneuvers for the object, and the combination of this information may be used to determine future locations of the object. The future locations may be used by the ego-vehicle to determine a path through the environment, or may be used by a simulation system to control virtual objects—according to trajectories determined from the future locations—through a simulation environment.
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