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公开(公告)号：US12205207B2
公开(公告)日：2025-01-21
申请号：US18176971
申请日：2023-03-01
Applicant: Snap Inc.
Inventor： Sergey Smetanin , Arnab Ghosh , Pavel Savchenkov , Jian Ren , Sergey Tulyakov , Ivan Babanin , Timur Zakirov , Roman Golobokov , Aleksandr Zakharov , Dor Ayalon , Nikita Demidov , Vladimir Gordienko , Daniel Moreno , Nikita Belosludtcev , Sofya Savinova
IPC: G06F3/0482 , G06T11/60
Abstract: Examples disclosed herein describe techniques related to automated image generation in an interaction system. An image generation request is received from a first user device associated with a first user of an interaction system. The image generation request comprises a text prompt. Responsive to receiving the image generation request, an image is automatically generated by an automated text-to-image generator, based on the text prompt. The image is caused to be presented on the first user device. An indication of user input to select the image is received from the user device. Responsive to receiving the indication of the user input to select the image, the image is associated with the first user within the interaction system, and a second user of the interaction system is enabled to be presented with the image.
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公开(公告)号：US20240395028A1
公开(公告)日：2024-11-28
申请号：US18400677
申请日：2023-12-29
Applicant: Snap Inc.
Inventor： Pavlo Chemerys , Colin Eles , Ju Hu , Qing Jin , Yanyu Li , Ergeta Muca , Jian Ren , Dhritiman Sagar , Aleksei Stoliar , Sergey Tulyakov , Huan Wang
IPC: G06V10/82 , G06N3/0455
Abstract: Described is a system for improving machine learning models. In some cases, the system improves such models by identifying an autoencoder for a latent diffusion machine learning model, the latent diffusion machine learning model is trained to receive text as input and output an image based on the received text. The system identifies a number of channels in a decoder of the autoencoder, the decoder being configured to receive latent features as input and output images. The system further identifies a performance characteristic of the decoder and changes the node topology of the decoder based on the performance characteristic to generate an updated decoder. The system retrains the latent diffusion machine learning model using the updated decoder by inputting latent features to the updated decoder, receiving an outputted image from the updated decoder, and updating one or more weights of the decoder based on an assessment of the outputted image.
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公开(公告)号：US20240394932A1
公开(公告)日：2024-11-28
申请号：US18400873
申请日：2023-12-29
Applicant: Snap Inc.
Inventor： Pavlo Chemerys , Colin Eles , Ju Hu , Qing Jin , Yanyu Li , Ergeta Muca , Jian Ren , Dhgritiman Sagar , Aleksei Stoliar , Sergey Tulyakov , Huan Wang
Abstract: Described is a system for improving machine learning models. In some cases, the system improves such models by identifying a performance characteristic for machine learning model blocks in an iterative denoising process of a machine learning model, connecting a prior machine learning model block with a subsequent machine learning model block of the machine learning model blocks within the machine learning model based on the identified performance characteristic, identifying a prompt of a user, the prompt indicative of an intent of the user for generative images, and analyzing data corresponding to the prompt using the machine learning model to generate one or more images, the machine learning model trained to generate images based on data corresponding to prompts.
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公开(公告)号：US12081794B2
公开(公告)日：2024-09-03
申请号：US18230511
申请日：2023-08-04
Applicant: Snap Inc.
Inventor： Sergey Demyanov , Andrew Cheng-min Lin , Walton Lin , Aleksei Podkin , Aleksei Stoliar , Sergey Tulyakov
IPC: H04N19/54 , G06N3/045 , H04L65/70 , H04N19/137 , H04N19/149 , H04N19/172
CPC classification number: H04N19/54 , G06N3/045 , H04L65/70 , H04N19/137 , H04N19/149 , H04N19/172
Abstract: Systems and methods herein describe a video compression system. The described systems and methods accesses a sequence of image frames from a first computing device, the sequence of image frames comprising a first image frame and a second image frame, detects a first set of keypoints for the first image frame, transmits the first image frame and the first set of keypoints to a second computing device, detects a second set of keypoints for the second image frame, transmits the second set of keypoints to the second computing device, causes an animated image to be displayed on the second computing device.
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公开(公告)号：US12056792B2
公开(公告)日：2024-08-06
申请号：US17557834
申请日：2021-12-21
Applicant: Snap Inc.
Inventor： Jian Ren , Menglei Chai , Oliver Woodford , Kyle Olszewski , Sergey Tulyakov
CPC classification number: G06T11/00 , G06N3/045 , G06T3/60 , G06T7/194 , G06V40/10 , G06T2207/20084 , G06T2207/30196
Abstract: Systems and methods herein describe a motion retargeting system. The motion retargeting system accesses a plurality of two-dimensional images comprising a person performing a plurality of body poses, extracts a plurality of implicit volumetric representations from the plurality of body poses, generates a three-dimensional warping field, the three-dimensional warping field configured to warp the plurality of implicit volumetric representations from a canonical pose to a target pose, and based on the three-dimensional warping field, generates a two-dimensional image of an artificial person performing the target pose.
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Patent Agency Ranking
公开(公告)号：US20230384918A1
公开(公告)日：2023-11-30
申请号：US18232146
申请日：2023-08-09
Applicant: Snap Inc.
Inventor： Theresa Barton , Yanping Chen , Jaewook Chung , Christopher Crutchfield , Aymeric Damien , Sergei Kotcur , Igor Kudriashov , Sergey Tulyakov , Andrew Wan , Emre Yamangil
IPC: G06F3/04845 , G06F3/0482 , G06T7/11 , H04N5/265 , H04N5/262 , G06V20/40 , G06V40/16
CPC classification number: G06F3/04845 , G06F3/0482 , G06T7/11 , H04N5/265 , H04N5/2628 , G06V20/40 , G06V40/161 , G06F3/04817
Abstract: A system of machine learning schemes can be configured to efficiently perform image processing tasks on a user device, such as a mobile phone. The system can selectively detect and transform individual regions within each frame of a live streaming video. The system can selectively partition and toggle image effects within the live streaming video.
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公开(公告)号：US20230379491A1
公开(公告)日：2023-11-23
申请号：US18230511
申请日：2023-08-04
Applicant: Snap Inc.
Inventor： Sergey Demyanov , Andrew Cheng-min Lin , Walton Lin , Aleksei Podkin , Aleksei Stoliar , Sergey Tulyakov
IPC: H04N19/54 , H04N19/137 , H04N19/149 , H04N19/172 , H04L65/70 , G06N3/045
CPC classification number: H04N19/54 , H04N19/137 , H04N19/149 , H04N19/172 , H04L65/70 , G06N3/045
Abstract: Systems and methods herein describe a video compression system. The described systems and methods accesses a sequence of image frames from a first computing device, the sequence of image frames comprising a first image frame and a second image frame, detects a first set of keypoints for the first image frame, transmits the first image frame and the first set of keypoints to a second computing device, detects a second set of keypoints for the second image frame, transmits the second set of keypoints to the second computing device, causes an animated image to be displayed on the second computing device.
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公开(公告)号：US20230306675A1
公开(公告)日：2023-09-28
申请号：US17656778
申请日：2022-03-28
Applicant: Snap Inc.
Inventor： Zeng Huang , Jian Ren , Sergey Tulyakov , Menglei Chai , Kyle Olszewski , Huan Wang
CPC classification number: G06T15/06 , G06T7/97 , G06T2207/20081 , G06T2207/20084
Abstract: Methods and systems are disclosed for performing operations for generating a 3D model of a scene. The operations include: receiving a set of two-dimensional (2D) images representing a first view of a real-world environment; applying a machine learning model comprising a neural light field network to the set of 2D images to predict pixel values of a target image representing a second view of the real-world environment, the machine learning model being trained to map a ray origin and direction directly to a given pixel value; and generating a three-dimensional (3D) model of the real-world environment based on the set of 2D images and the predicted target image.
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公开(公告)号：US20230079136A1
公开(公告)日：2023-03-16
申请号：US17987285
申请日：2022-11-15
Applicant: Snap Inc.
Inventor： Artem Bondich , Menglei Chai , Oleksandr Pyshchenko , Jian Ren , Sergey Tulyakov
Abstract: A messaging system performs neural network hair rendering for images provided by users of the messaging system. A method of neural network hair rendering includes processing a three-dimensional (3D) model of fake hair and a first real hair image depicting a first person to generate a fake hair structure, and encoding, using a fake hair encoder neural subnetwork, the fake hair structure to generate a coded fake hair structure. The method further includes processing, using a cross-domain structure embedding neural subnetwork, the coded fake hair structure to generate a fake and real hair structure, and encoding, using an appearance encoder neural subnetwork, a second real hair image depicting a second person having a second head to generate an appearance map. The method further includes processing, using a real appearance renderer neural subnetwork, the appearance map and the fake and real hair structure to generate a synthesized real image.
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公开(公告)号：US11521362B2
公开(公告)日：2022-12-06
申请号：US17445549
申请日：2021-08-20
Applicant: Snap Inc.
Inventor： Artem Bondich , Menglei Chai , Oleksandr Pyshchenko , Jian Ren , Sergey Tulyakov
Abstract: A messaging system performs neural network hair rendering for images provided by users of the messaging system. A method of neural network hair rendering includes processing a three-dimensional (3D) model of fake hair and a first real hair image depicting a first person to generate a fake hair structure, and encoding, using a fake hair encoder neural subnetwork, the fake hair structure to generate a coded fake hair structure. The method further includes processing, using a cross-domain structure embedding neural subnetwork, the coded fake hair structure to generate a fake and real hair structure, and encoding, using an appearance encoder neural subnetwork, a second real hair image depicting a second person having a second head to generate an appearance map. The method further includes processing, using a real appearance renderer neural subnetwork, the appearance map and the fake and real hair structure to generate a synthesized real image.
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