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公开(公告)号：US12112427B2
公开(公告)日：2024-10-08
申请号：US17898136
申请日：2022-08-29
Applicant: Snap Inc.
CPC classification number: G06T15/205 , G06T7/55 , G06T15/04 , G06T17/20 , G06T2207/10016 , G06T2207/10024 , G06T2207/10028
Abstract: Images of a scene are received. The images represent viewpoints corresponding to the scene. A pixel map of the scene is computed based on the plurality of images. Multi-plane image (MPI) layers from the pixel map are extracted in real-time. The MPI layers are aggregated. The scene is rendered from a novel viewpoint based on the aggregated MPI layers.
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公开(公告)号：US12106412B2
公开(公告)日：2024-10-01
申请号：US17350954
申请日：2021-06-17
Applicant: Snap Inc.
Inventor： Gurunandan Krishnan Gorumkonda , Shree K. Nayar
CPC classification number: G06T13/205 , G06T13/80 , G10L25/57
Abstract: Methods, devices, media, and other embodiments are described for generating pseudorandom animations matched to audio data on a device. In one embodiment a video is generated and output on a display of the device using a computer animation model. Audio is detected from a microphone of the device, and the audio data is processed to determine a set of audio characteristics for the audio data received at the microphone of the device. A first motion state is randomly selected from the plurality of motion states, one or more motion values of the first motion state are generated using the set of audio characteristics, and the video is updated using the one or more motion values with the computer animation model to create an animated action within the video.
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公开(公告)号：US20240177390A1
公开(公告)日：2024-05-30
申请号：US18525291
申请日：2023-11-30
Applicant: Snap Inc.
Inventor： Gurunandan Krishnan Gorumkonda , Shree K. Nayar
CPC classification number: G06T13/40 , G06T13/205
Abstract: Method of generating a real-time avatar animation starts with a processor receiving acoustic segments of a real-time acoustic signal. For each of the acoustic segments, processor generates using a music analyzer neural network a tempo value and a dance energy category and selects dance tracks based on the tempo value and the dance energy category. Processor generates using the dance tracks dance sequences for avatars, generates real-time animations for the avatars based on the dance sequences and avatar characteristics for the avatars, and causes to be displayed on a first client device the real-time animations of the avatars. Other embodiments are described herein.
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公开(公告)号：US20240086659A1
公开(公告)日：2024-03-14
申请号：US18514725
申请日：2023-11-20
Applicant: Snap Inc.
Inventor： Jian Wang , Karl Bayer , Shree K. Nayar
CPC classification number: G06K7/1417 , G06K7/10722
Abstract: An apparatus to perform fast data access comprises a receiver, a processor, and a memory. The processor receives using the receiver a light signal from a light source. The light signal can be structured to generate a temporal code. The light source is an optical beacon that includes a Light-Emitting Diode (LED). The processor then decodes the light signal to generate a network address, and causes a display of a client device coupled to the apparatus to display information based on the network address. The network address can be a Uniform Resource Locator (URL) address and the information based on the network address includes a webpage associated with the URL. Other embodiments are described herein.
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公开(公告)号：US11825276B2
公开(公告)日：2023-11-21
申请号：US17556811
申请日：2021-12-20
Applicant: Snap Inc.
Inventor： Karl Bayer , Jacob Andreou , Shree K. Nayar
CPC classification number: H04R3/00 , H04R1/1041 , H04R2420/01
Abstract: An apparatus with a selector input device to transmit an audio signal comprises a microphone, a communication interface, and a selector input device. The apparatus can also comprise a processor and a memory having instructions stored thereon, when executed by the processor, causes the processor to perform operations comprising detecting an activation of the selector input device. In response to detecting the activation, the processor captures the audio signal via the microphone and transmits the audio signal via the communication interface to a first client device. Other embodiments are described herein.
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Patent Agency Ranking
公开(公告)号：US11810236B2
公开(公告)日：2023-11-07
申请号：US17350975
申请日：2021-06-17
Applicant: Snap Inc.
Inventor： Gurunandan Krishnan Gorumkonda , Shree K. Nayar
IPC: G06T13/80 , G10L21/055
CPC classification number: G06T13/80 , G10L21/055
Abstract: Methods, devices, media, and other embodiments are described for managing and configuring a pseudorandom animation system and associated computer animation models. One embodiment involves generating image modification data with a computer animation model configured to modify frames of a video image to insert and animate the computer animation model within the frames of the video image, where the computer animation model of the image modification data comprises one or more control points. Motion patterns and speed harmonics are automatically associated with the control points, and motion states are generated based on the associated motions and harmonics. A probability value is then assigned to each motion state. The motion state probabilities can then be used when generating a pseudorandom animation.
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公开(公告)号：US11670027B2
公开(公告)日：2023-06-06
申请号：US17526540
申请日：2021-11-15
Applicant: Snap Inc.
Inventor： Gurunandan Krishnan Gorumkonda , Shree K. Nayar
CPC classification number: G06T13/205 , G06T7/246 , G06T13/40 , G06T13/80
Abstract: Methods, devices, media, and other embodiments are described for generating, modifying, and outputting pseudorandom animations that can be synchronized to audio data. In one embodiment, a computer animation model made up of comprising one or more control points is accessed by one or more processors, which associate motion patterns with a first control point of the one or more control points, and associate one or more speed harmonics with the first control point. A set of motion states is identify with a motion state for the combinations of possibilities, and a probability value is assigned to each motion state of the set of motion states. The probability value can be used to probabilistically determine a particular motion state to be part of displayed animation for the computer animation model.
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公开(公告)号：US20230137950A1
公开(公告)日：2023-05-04
申请号：US18090973
申请日：2022-12-29
Applicant: Snap Inc.
Inventor： Karl Bayer , Prerna Chikersal , Shree K. Nayar , Brian Anthony Smith
IPC: G06F40/103 , H04L51/046 , G06F3/0484
Abstract: A client device processing received emoji messages using emoji-first messaging. Text messaging is automatically converted to emojis by an emoji-first application so that only emojis are communicated from one client device to another client device. Each client device has a library of emojis that are mapped to words, which libraries are customizable and unique to the users of the client devices, such that the users can communicate secretly in code. Upon receipt of a string of emojis, a user can select the emoji string to convert to text if desired, for a predetermined period of time.
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公开(公告)号：US20220405961A1
公开(公告)日：2022-12-22
申请号：US17895519
申请日：2022-08-25
Applicant: Snap Inc.
Inventor： Shree K. Nayar , Jian Wang , Wenzheng Chen
Abstract: Systems and methods are provided for: receiving an image containing a code that has one or more visual qualities that fail to satisfy respective thresholds; applying a trained machine learning model to find a rough location of the code by generating a bounding box and cropping out the portion of the image; applying another trained machine learning model to the portion of the image to estimate key point locations of the code depicted in the portion of the image, aligning the portion of the image that depicts the code based on the estimated key point locations; and decoding, by the other trained machine learning model, the aligned portion of the image that depicts the code.
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公开(公告)号：US11461924B1
公开(公告)日：2022-10-04
申请号：US16948585
申请日：2020-09-24
Applicant: Snap Inc.
Inventor： Shree K. Nayar , Jian Wang , Wenzheng Chen
Abstract: Systems and methods are provided for: receiving an image containing a code that has one or more visual qualities that fail to satisfy respective thresholds; applying a trained machine learning model to find a rough location of the code by generating a bounding box and cropping out the portion of the image; applying another trained machine learning model to the portion of the image to estimate key point locations of the code depicted in the portion of the image, aligning the portion of the image that depicts the code based on the estimated key point locations; and decoding, by the other trained machine learning model, the aligned portion of the image that depicts the code.
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