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公开(公告)号:US20250078380A1
公开(公告)日:2025-03-06
申请号:US18241155
申请日:2023-08-31
Applicant: Adobe Inc.
Inventor: Yining CAO , Stefano PETRANGELI , Li-Yi WEI , Rubaiat HABIB , Deepali ANEJA , Balaji Vasan SRINIVASAN , Haijun XIA
IPC: G06T13/80 , G06F40/56 , G06V40/20 , H04N21/2187 , H04N21/431
Abstract: In various examples, a video effect is displayed in a live video stream in response to determining a portion of an audio stream of the live video stream corresponds to a text segment of a script associated with the video effect and detecting performance of a gesture. For example, during presentation of the script, the audio stream is obtained to determine if a portion of the audio stream corresponds to the text segment. In response to the portion of the audio stream corresponding to the text segment, detecting performance of a gestures and causing the video effect to be displayed.
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公开(公告)号:US20240314293A1
公开(公告)日:2024-09-19
申请号:US18669137
申请日:2024-05-20
Applicant: Adobe Inc.
Inventor: Stefano PETRANGELI , Viswanathan SWAMINATHAN , Haoliang WANG
IPC: H04N19/105 , H04N19/176 , H04N19/182 , H04N19/91
CPC classification number: H04N19/105 , H04N19/176 , H04N19/182 , H04N19/91
Abstract: Embodiments are disclosed for lossless image compression using block-based prediction and context adaptive entropy coding. A method of lossless image compression using block-based prediction and context adaptive entropy coding comprises dividing an input image into a plurality of blocks, determining a pixel predictor for each block based on a block strategy, determining a plurality of residual values using the pixel predictor for each block, selecting a subset of features associated with the plurality of residual values, performing context modeling on the plurality of residual values based on the subset of features to identify a plurality of residual clusters, and entropy coding the plurality of residual clusters.
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公开(公告)号:US20240163393A1
公开(公告)日:2024-05-16
申请号:US18055301
申请日:2022-11-14
Applicant: Adobe Inc.
Inventor: Uttaran BHATTACHARYA , Gang WU , Viswanathan SWAMINATHAN , Stefano PETRANGELI
Abstract: Embodiments are disclosed for predicting, using neural networks, editing operations for application to a video sequence based on processing conversational messages by a video editing system. In particular, in one or more embodiments, the disclosed systems and methods comprise receiving an input including a video sequence and text sentences, the text sentences describing a modification to the video sequence, mapping, by a first neural network content of the text sentences describing the modification to the video sequence to a candidate editing operation, processing, by a second neural network, the video sequence to predict parameter values for the candidate editing operation, and generating a modified video sequence by applying the candidate editing operation with the predicted parameter values to the video sequence.
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公开(公告)号:US20220400253A1
公开(公告)日:2022-12-15
申请号:US17891057
申请日:2022-08-18
Applicant: Adobe Inc.
Inventor: Stefano PETRANGELI , Viswanathan SWAMINATHAN , Haoliang WANG
IPC: H04N19/105 , H04N19/182 , H04N19/91 , H04N19/176
Abstract: Embodiments are disclosed for lossless image compression using block-based prediction and context adaptive entropy coding. A method of lossless image compression using block-based prediction and context adaptive entropy coding comprises dividing an input image into a plurality of blocks, determining a pixel predictor for each block based on a block strategy, determining a plurality of residual values using the pixel predictor for each block, selecting a subset of features associated with the plurality of residual values, performing context modeling on the plurality of residual values based on the subset of features to identify a plurality of residual clusters, and entropy coding the plurality of residual clusters.
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公开(公告)号:US20220264084A1
公开(公告)日:2022-08-18
申请号:US17177592
申请日:2021-02-17
Applicant: Adobe Inc.
Inventor: Stefano PETRANGELI , Viswanathan SWAMINATHAN , Haoliang WANG
IPC: H04N19/105 , H04N19/176 , H04N19/91 , H04N19/182
Abstract: Embodiments are disclosed for lossless image compression using block-based prediction and context adaptive entropy coding. A method of lossless image compression using block-based prediction and context adaptive entropy coding comprises dividing an input image into a plurality of blocks, determining a pixel predictor for each block based on a block strategy, determining a plurality of residual values using the pixel predictor for each block, selecting a subset of features associated with the plurality of residual values, performing context modeling on the plurality of residual values based on the subset of features to identify a plurality of residual clusters, and entropy coding the plurality of residual clusters.
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