公开(公告)号：US20250103649A1

公开(公告)日：2025-03-27

申请号：US18473045

申请日：2023-09-22

Applicant: Adobe Inc.

Inventor： Ritwik SINHA ,  Viswanathan SWAMINATHAN ,  Simon JENNI ,  Md Mehrab TANJIM ,  John COLLOMOSSE

IPC: G06F16/732 ,  G06F16/738 ,  G06F16/75

Abstract: Embodiments are disclosed for performing content authentication. A method of content authentication may include dividing a query video into a plurality of chunks. A feature vector may be generated, using a fingerprinting model, for each chunk from the plurality of chunks. Similar video chunks are identified from a trusted chunk database based on the feature vectors using a multi-chunk search policy. One or more original videos corresponding to the query video are then returned.

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.

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

IPC: H04N7/00 ,  G06T11/60

CPC classification number: H04N7/002 ,  G06T11/60

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.

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.

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.