Patents by Inventor Arun Mohanray Mallya
Arun Mohanray Mallya has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Publication number: 20240095989Abstract: Apparatuses, systems, and techniques to generate a video using two or more images comprising objects to be included in the video. In at least one embodiment, objects are identified in two or more images using one or more neural networks, to generate a video to include the objects in the video.Type: ApplicationFiled: September 15, 2022Publication date: March 21, 2024Inventors: Arun Mohanray Mallya, Ting-Chun Wang, Ming-Yu Liu
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Patent number: 11775829Abstract: A latent code defined in an input space is processed by the mapping neural network to produce an intermediate latent code defined in an intermediate latent space. The intermediate latent code may be used as appearance vector that is processed by the synthesis neural network to generate an image. The appearance vector is a compressed encoding of data, such as video frames including a person's face, audio, and other data. Captured images may be converted into appearance vectors at a local device and transmitted to a remote device using much less bandwidth compared with transmitting the captured images. A synthesis neural network at the remote device reconstructs the images for display.Type: GrantFiled: December 12, 2022Date of Patent: October 3, 2023Assignee: NVIDIA CorporationInventors: Tero Tapani Karras, Samuli Matias Laine, David Patrick Luebke, Jaakko T. Lehtinen, Miika Samuli Aittala, Timo Oskari Aila, Ming-Yu Liu, Arun Mohanray Mallya, Ting-Chun Wang
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Publication number: 20230110206Abstract: A latent code defined in an input space is processed by the mapping neural network to produce an intermediate latent code defined in an intermediate latent space. The intermediate latent code may be used as appearance vector that is processed by the synthesis neural network to generate an image. The appearance vector is a compressed encoding of data, such as video frames including a person's face, audio, and other data. Captured images may be converted into appearance vectors at a local device and transmitted to a remote device using much less bandwidth compared with transmitting the captured images. A synthesis neural network at the remote device reconstructs the images for display.Type: ApplicationFiled: December 12, 2022Publication date: April 13, 2023Inventors: Tero Tapani Karras, Samuli Matias Laine, David Patrick Luebke, Jaakko T. Lehtinen, Miika Samuli Aittala, Timo Oskari Aila, Ming-Yu Liu, Arun Mohanray Mallya, Ting-Chun Wang
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Patent number: 11625613Abstract: A latent code defined in an input space is processed by the mapping neural network to produce an intermediate latent code defined in an intermediate latent space. The intermediate latent code may be used as appearance vector that is processed by the synthesis neural network to generate an image. The appearance vector is a compressed encoding of data, such as video frames including a person's face, audio, and other data. Captured images may be converted into appearance vectors at a local device and transmitted to a remote device using much less bandwidth compared with transmitting the captured images. A synthesis neural network at the remote device reconstructs the images for display.Type: GrantFiled: January 7, 2021Date of Patent: April 11, 2023Assignee: NVIDIA CorporationInventors: Tero Tapani Karras, Samuli Matias Laine, David Patrick Luebke, Jaakko T. Lehtinen, Miika Samuli Aittala, Timo Oskari Aila, Ming-Yu Liu, Arun Mohanray Mallya, Ting-Chun Wang
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Patent number: 11610435Abstract: A latent code defined in an input space is processed by the mapping neural network to produce an intermediate latent code defined in an intermediate latent space. The intermediate latent code may be used as appearance vector that is processed by the synthesis neural network to generate an image. The appearance vector is a compressed encoding of data, such as video frames including a person's face, audio, and other data. Captured images may be converted into appearance vectors at a local device and transmitted to a remote device using much less bandwidth compared with transmitting the captured images. A synthesis neural network at the remote device reconstructs the images for display.Type: GrantFiled: October 13, 2020Date of Patent: March 21, 2023Assignee: NVIDIA CorporationInventors: Tero Tapani Karras, Samuli Matias Laine, David Patrick Luebke, Jaakko T. Lehtinen, Miika Samuli Aittala, Timo Oskari Aila, Ming-Yu Liu, Arun Mohanray Mallya, Ting-Chun Wang
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Patent number: 11610122Abstract: A latent code defined in an input space is processed by the mapping neural network to produce an intermediate latent code defined in an intermediate latent space. The intermediate latent code may be used as appearance vector that is processed by the synthesis neural network to generate an image. The appearance vector is a compressed encoding of data, such as video frames including a person's face, audio, and other data. Captured images may be converted into appearance vectors at a local device and transmitted to a remote device using much less bandwidth compared with transmitting the captured images. A synthesis neural network at the remote device reconstructs the images for display.Type: GrantFiled: January 7, 2021Date of Patent: March 21, 2023Assignee: NVIDIA CorporationInventors: Tero Tapani Karras, Samuli Matias Laine, David Patrick Luebke, Jaakko T. Lehtinen, Miika Samuli Aittala, Timo Oskari Aila, Ming-Yu Liu, Arun Mohanray Mallya, Ting-Chun Wang
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Patent number: 11580395Abstract: A latent code defined in an input space is processed by the mapping neural network to produce an intermediate latent code defined in an intermediate latent space. The intermediate latent code may be used as appearance vector that is processed by the synthesis neural network to generate an image. The appearance vector is a compressed encoding of data, such as video frames including a person's face, audio, and other data. Captured images may be converted into appearance vectors at a local device and transmitted to a remote device using much less bandwidth compared with transmitting the captured images. A synthesis neural network at the remote device reconstructs the images for display.Type: GrantFiled: October 13, 2020Date of Patent: February 14, 2023Assignee: NVIDIA CorporationInventors: Tero Tapani Karras, Samuli Matias Laine, David Patrick Luebke, Jaakko T. Lehtinen, Miika Samuli Aittala, Timo Oskari Aila, Ming-Yu Liu, Arun Mohanray Mallya, Ting-Chun Wang
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Publication number: 20220180602Abstract: Apparatuses, systems, and techniques are presented to generate images. In at least one embodiment, one or more neural networks are used to generate one or more images based, at least in part, upon one or more semantic features projected from a three-dimensional environment.Type: ApplicationFiled: December 3, 2020Publication date: June 9, 2022Inventors: Zekun Hao, Ming-Yu Liu, Arun Mohanray Mallya
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Publication number: 20210329306Abstract: Apparatuses, systems, and techniques to perform compression of video data using neural networks to facilitate video streaming, such as video conferencing. In at least one embodiment, a sender transmits to a receiver a key frame from video data and one or more keypoints identified by a neural network from said video data, and a receiver reconstructs video data using said key frame and one or more received keypoints.Type: ApplicationFiled: October 13, 2020Publication date: October 21, 2021Inventors: Ming-Yu Liu, Ting-Chun Wang, Arun Mohanray Mallya, Tero Tapani Karras, Samuli Matias Laine, David Patrick Luebke, Jaakko Lehtinen, Miika Samuli Aittala, Timo Oskari Aila
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Publication number: 20210150354Abstract: A latent code defined in an input space is processed by the mapping neural network to produce an intermediate latent code defined in an intermediate latent space. The intermediate latent code may be used as appearance vector that is processed by the synthesis neural network to generate an image. The appearance vector is a compressed encoding of data, such as video frames including a person's face, audio, and other data. Captured images may be converted into appearance vectors at a local device and transmitted to a remote device using much less bandwidth compared with transmitting the captured images. A synthesis neural network at the remote device reconstructs the images for display.Type: ApplicationFiled: January 7, 2021Publication date: May 20, 2021Inventors: Tero Tapani Karras, Samuli Matias Laine, David Patrick Luebke, Jaakko T. Lehtinen, Miika Samuli Aittala, Timo Oskari Aila, Ming-Yu Liu, Arun Mohanray Mallya, Ting-Chun Wang
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Publication number: 20210150187Abstract: A latent code defined in an input space is processed by the mapping neural network to produce an intermediate latent code defined in an intermediate latent space. The intermediate latent code may be used as appearance vector that is processed by the synthesis neural network to generate an image. The appearance vector is a compressed encoding of data, such as video frames including a person's face, audio, and other data. Captured images may be converted into appearance vectors at a local device and transmitted to a remote device using much less bandwidth compared with transmitting the captured images. A synthesis neural network at the remote device reconstructs the images for display.Type: ApplicationFiled: January 7, 2021Publication date: May 20, 2021Inventors: Tero Tapani Karras, Samuli Matias Laine, David Patrick Luebke, Jaakko T. Lehtinen, Miika Samuli Aittala, Timo Oskari Aila, Ming-Yu Liu, Arun Mohanray Mallya, Ting-Chun Wang
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Publication number: 20210073612Abstract: In at least one embodiment, differentiable neural architecture search and reinforcement learning are combined under one framework to discover network architectures with desired properties such as high accuracy, low latency, or both. In at least one embodiment, an objective function for search based on generalization error prevents the selection of architectures prone to overfitting.Type: ApplicationFiled: September 10, 2019Publication date: March 11, 2021Inventors: Arash Vahdat, Arun Mohanray Mallya, Ming-Yu Liu, Jan Kautz
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Publication number: 20210049468Abstract: A latent code defined in an input space is processed by the mapping neural network to produce an intermediate latent code defined in an intermediate latent space. The intermediate latent code may be used as appearance vector that is processed by the synthesis neural network to generate an image. The appearance vector is a compressed encoding of data, such as video frames including a person's face, audio, and other data. Captured images may be converted into appearance vectors at a local device and transmitted to a remote device using much less bandwidth compared with transmitting the captured images. A synthesis neural network at the remote device reconstructs the images for display.Type: ApplicationFiled: October 13, 2020Publication date: February 18, 2021Inventors: Tero Tapani Karras, Samuli Matias Laine, David Patrick Luebke, Jaakko T. Lehtinen, Miika Samuli Aittala, Timo Oskari Aila, Ming-Yu Liu, Arun Mohanray Mallya, Ting-Chun Wang
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Publication number: 20210042503Abstract: A latent code defined in an input space is processed by the mapping neural network to produce an intermediate latent code defined in an intermediate latent space. The intermediate latent code may be used as appearance vector that is processed by the synthesis neural network to generate an image. The appearance vector is a compressed encoding of data, such as video frames including a person's face, audio, and other data. Captured images may be converted into appearance vectors at a local device and transmitted to a remote device using much less bandwidth compared with transmitting the captured images. A synthesis neural network at the remote device reconstructs the images for display.Type: ApplicationFiled: October 13, 2020Publication date: February 11, 2021Inventors: Tero Tapani Karras, Samuli Matias Laine, David Patrick Luebke, Jaakko T. Lehtinen, Miika Samuli Aittala, Timo Oskari Aila, Ming-Yu Liu, Arun Mohanray Mallya, Ting-Chun Wang