-
公开(公告)号：US11727280B2
公开(公告)日：2023-08-15
申请号：US17189563
申请日：2021-03-02
Applicant: Snap Inc.
Inventor： Sergey Tulyakov , Sergei Korolev , Aleksei Stoliar , Maksim Gusarov , Sergei Kotcur , Christopher Yale Crutchfield , Andrew Wan
IPC: G06N3/088 , G06N3/08 , G06F18/21 , G06F18/214 , G06N3/045 , G06V10/764 , G06V10/774 , G06V10/778 , G06V10/82
CPC classification number: G06N3/088 , G06F18/2148 , G06F18/2185 , G06N3/045 , G06N3/08 , G06V10/764 , G06V10/7747 , G06V10/7788 , G06V10/82
Abstract: A compact generative neural network can be distilled from a teacher generative neural network using a training network. The compact network can be trained on the input data and output data of the teacher network. The training network train the student network using a discrimination layer and one or more types of losses, such as perception loss and adversarial loss.
-
公开(公告)号：US20230206398A1
公开(公告)日：2023-06-29
申请号：US18116682
申请日：2023-03-02
Applicant: Snap Inc.
Inventor： Sergey Demyanov , Aleksei Podkin , Aleksei Stoliar , Vadim Velicodnii , Fedor Zhdanov
CPC classification number: G06T5/001 , G06T5/10 , G06T2207/20081 , H04L51/10
Abstract: A data item is identified on a device. A neural network that includes an adversarial transformation subnetwork is applied to the data item to generate a modified data item. Output indicative of the modified data item is caused to be presented on the device. The neural network further comprises an encoder and a decoder. The neural network is trained in at least two stages. At least one of the encoder and the decoder is trained in a first stage and the adversarial transformation subnetwork is trained in a second stage.
-
公开(公告)号：US11558325B2
公开(公告)日：2023-01-17
申请号：US17330852
申请日：2021-05-26
Applicant: Snap Inc.
Inventor： Grygoriy Kozhemiak , Oleksandr Pyshchenko , Victor Shaburov , Trevor Stephenson , Aleksei Stoliar
Abstract: Systems and methods are provided for receiving a first media content item associated with a first interactive object of an interactive message, receiving a second media content item associated with a second interactive object of the interactive message, generating a third media content item based on the first media content item and second media content item, wherein the third media content item comprises combined features of the first media content item and the second media content item, and causing display of the generated third media content item.
-
公开(公告)号：US20220292866A1
公开(公告)日：2022-09-15
申请号：US17829644
申请日：2022-06-01
Applicant: Snap Inc.
Inventor： Sergey Tulyakov , Roman Furko , Aleksei Stoliar
Abstract: A landmark detection system can more accurately detect landmarks in images using a detection scheme that penalizes for dispersion parameters, such as variance or scale. The landmark detection system can be trained using both labeled and unlabeled training data in a semi-supervised approach. The landmark detection system can further implement tracking of an object across multiple images using landmark data.
-
公开(公告)号：US11354922B2
公开(公告)日：2022-06-07
申请号：US17138177
申请日：2020-12-30
Applicant: Snap Inc.
Inventor： Sergey Tulyakov , Roman Furko , Aleksei Stoliar
Abstract: A landmark detection system can more accurately detect landmarks in images using a detection scheme that penalizes for dispersion parameters, such as variance or scale. The landmark detection system can be trained using both labeled and unlabeled training data in a semi-supervised approach. The landmark detection system can further implement tracking of an object across multiple images using landmark data.
-
Patent Agency Ranking
公开(公告)号：US20210390745A1
公开(公告)日：2021-12-16
申请号：US16946413
申请日：2020-06-19
Applicant: Snap Inc.
Inventor： Olha Rykhliuk , Jonathan Solichin , Aleksei Stoliar
Abstract: Systems and methods herein describe receiving an image via an image capture device, using a machine learning model, generating an image augmentation decision, accessing an augmentation reality content item, associating the generated image augmentation decision with the augmentation reality content item, modifying the received image using the augmentation reality content item and the associated image augmentation decision, and causing presentation of the modified image on a graphical user interface of a computing device.
-
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.
-
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.
-
公开(公告)号：US20240303902A1
公开(公告)日：2024-09-12
申请号：US18182117
申请日：2023-03-10
Applicant: SNAP INC.
Inventor： Vladislav Shakhrai , Sergey Demyanov , Aleksei Stoliar , Istvan Marton
CPC classification number: G06T15/04 , G06T15/005
Abstract: The subject technology receives an object mesh, information related to a viewpoint for rendering an image of an object having a reflective surface, and a set of maps. The subject technology generates a rasterized RGB (Red Green Blue) image based on the object mesh, the viewpoint, and the set of maps. The subject technology generates, using a neural network model, an output image of the object with the reflective surface based at least in part on the rasterized RGB image and the viewpoint. The subject technology provides for display the output image of the object with the reflective surface on a display of a computer client device.
-
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.
-
-
-
-
-
-
-
-
-
Search Results
45
records
(took 0.018 seconds)
