BR112022016793A2 - Compressão de vídeo usando sistemas de aprendizado de máquina de base recorrente - Google Patents
Compressão de vídeo usando sistemas de aprendizado de máquina de base recorrenteInfo
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- BR112022016793A2 BR112022016793A2 BR112022016793A BR112022016793A BR112022016793A2 BR 112022016793 A2 BR112022016793 A2 BR 112022016793A2 BR 112022016793 A BR112022016793 A BR 112022016793A BR 112022016793 A BR112022016793 A BR 112022016793A BR 112022016793 A2 BR112022016793 A2 BR 112022016793A2
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/42—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals characterised by implementation details or hardware specially adapted for video compression or decompression, e.g. dedicated software implementation
- H04N19/436—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals characterised by implementation details or hardware specially adapted for video compression or decompression, e.g. dedicated software implementation using parallelised computational arrangements
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/46—Embedding additional information in the video signal during the compression process
- H04N19/463—Embedding additional information in the video signal during the compression process by compressing encoding parameters before transmission
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/044—Recurrent networks, e.g. Hopfield networks
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/045—Combinations of networks
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
- G06N3/084—Backpropagation, e.g. using gradient descent
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
- H04N19/134—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
- H04N19/136—Incoming video signal characteristics or properties
- H04N19/137—Motion inside a coding unit, e.g. average field, frame or block difference
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
- H04N19/169—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
- H04N19/17—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object
- H04N19/172—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object the region being a picture, frame or field
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/42—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals characterised by implementation details or hardware specially adapted for video compression or decompression, e.g. dedicated software implementation
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/50—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding
- H04N19/503—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding involving temporal prediction
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/85—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using pre-processing or post-processing specially adapted for video compression
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Signal Processing (AREA)
- Multimedia (AREA)
- Computing Systems (AREA)
- General Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Mathematical Physics (AREA)
- Software Systems (AREA)
- General Health & Medical Sciences (AREA)
- Molecular Biology (AREA)
- Biomedical Technology (AREA)
- General Engineering & Computer Science (AREA)
- Biophysics (AREA)
- Computational Linguistics (AREA)
- Evolutionary Computation (AREA)
- Artificial Intelligence (AREA)
- Life Sciences & Earth Sciences (AREA)
- Health & Medical Sciences (AREA)
- Image Analysis (AREA)
- Processing Or Creating Images (AREA)
- Compression Or Coding Systems Of Tv Signals (AREA)
- Studio Devices (AREA)
Abstract
COMPRESSÃO DE VÍDEO USANDO SISTEMAS DE APRENDIZADO DE MÁQUINA DE BASE RECORRENTE. A presente invenção refere-se a técnicas que são descritas neste documento para codificar conteúdo de vídeo usando ferramentas de aprendizado de máquina de base recorrente. Um dispositivo pode incluir um sistema de rede neural incluindo porções do codificador e do decodificado. A porção do codificador pode gerar dados de saída para a etapa de tempo atual de operação do sistema de rede neural com base em um quadro de vídeo de entrada para uma etapa de tempo atual de operação do sistema de rede neural, dados de estimação de movimento reconstruídos a partir de uma etapa de tempo anterior de operação, dados residuais reconstruídos a partir da etapa de tempo de operação anterior e dados de estado recorrente a partir de pelo menos uma camada recorrente de uma porção do decodificador do sistema de rede neural a partir da etapa de tempo de operação anterior. Uma porção do decodificador do sistema de rede neural pode gerar, com base nos dados de saída e dados de estado recorrentes a partir da etapa de tempo anterior de operação, um quadro de vídeo reconstruído para a etapa de tempo atual de operação.
Applications Claiming Priority (3)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US202062984673P | 2020-03-03 | 2020-03-03 | |
US17/091,570 US11405626B2 (en) | 2020-03-03 | 2020-11-06 | Video compression using recurrent-based machine learning systems |
PCT/US2021/013599 WO2021178050A1 (en) | 2020-03-03 | 2021-01-15 | Video compression using recurrent-based machine learning systems |
Publications (1)
Publication Number | Publication Date |
---|---|
BR112022016793A2 true BR112022016793A2 (pt) | 2022-10-11 |
Family
ID=77554929
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
BR112022016793A BR112022016793A2 (pt) | 2020-03-03 | 2021-01-15 | Compressão de vídeo usando sistemas de aprendizado de máquina de base recorrente |
Country Status (8)
Country | Link |
---|---|
US (1) | US11405626B2 (pt) |
EP (1) | EP4115617A1 (pt) |
JP (1) | JP2023517846A (pt) |
KR (1) | KR20220150298A (pt) |
CN (1) | CN115211115A (pt) |
BR (1) | BR112022016793A2 (pt) |
TW (1) | TW202135529A (pt) |
WO (1) | WO2021178050A1 (pt) |
Families Citing this family (24)
Publication number | Priority date | Publication date | Assignee | Title |
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CN110677649B (zh) * | 2019-10-16 | 2021-09-28 | 腾讯科技(深圳)有限公司 | 基于机器学习的去伪影方法、去伪影模型训练方法及装置 |
US20210192681A1 (en) * | 2019-12-18 | 2021-06-24 | Ati Technologies Ulc | Frame reprojection for virtual reality and augmented reality |
WO2021220008A1 (en) * | 2020-04-29 | 2021-11-04 | Deep Render Ltd | Image compression and decoding, video compression and decoding: methods and systems |
US11425402B2 (en) * | 2020-07-20 | 2022-08-23 | Meta Platforms, Inc. | Cross-codec encoding optimizations for video transcoding |
US11551090B2 (en) * | 2020-08-28 | 2023-01-10 | Alibaba Group Holding Limited | System and method for compressing images for remote processing |
US11490078B2 (en) | 2020-12-29 | 2022-11-01 | Tencent America LLC | Method and apparatus for deep neural network based inter-frame prediction in video coding |
US11570465B2 (en) * | 2021-01-13 | 2023-01-31 | WaveOne Inc. | Machine-learned in-loop predictor for video compression |
TWI804181B (zh) * | 2021-02-02 | 2023-06-01 | 聯詠科技股份有限公司 | 影像編碼方法及其影像編碼器 |
US11399198B1 (en) * | 2021-03-01 | 2022-07-26 | Qualcomm Incorporated | Learned B-frame compression |
US11831909B2 (en) * | 2021-03-11 | 2023-11-28 | Qualcomm Incorporated | Learned B-frame coding using P-frame coding system |
WO2023069337A1 (en) * | 2021-10-18 | 2023-04-27 | Op Solutions, Llc | Systems and methods for optimizing a loss function for video coding for machines |
US11546614B1 (en) * | 2021-10-25 | 2023-01-03 | Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V. | Encoder and decoder for encoding and decoding images |
CN116112673A (zh) * | 2021-11-10 | 2023-05-12 | 华为技术有限公司 | 编解码方法及电子设备 |
WO2023092388A1 (zh) * | 2021-11-25 | 2023-06-01 | Oppo广东移动通信有限公司 | 解码方法、编码方法、解码器、编码器和编解码系统 |
US20230214630A1 (en) * | 2021-12-30 | 2023-07-06 | Cron Ai Ltd. (Uk) | Convolutional neural network system, method for dynamically defining weights, and computer-implemented method thereof |
WO2023138687A1 (en) * | 2022-01-21 | 2023-07-27 | Beijing Bytedance Network Technology Co., Ltd. | Method, apparatus, and medium for data processing |
WO2023167502A1 (ko) * | 2022-03-02 | 2023-09-07 | 엘지전자 주식회사 | 피쳐 부호화/복호화 방법, 장치, 비트스트림을 저장한 기록 매체 및 비트스트림 전송 방법 |
WO2023165596A1 (en) * | 2022-03-03 | 2023-09-07 | Beijing Bytedance Network Technology Co., Ltd. | Method, apparatus, and medium for visual data processing |
WO2024015638A2 (en) * | 2022-07-15 | 2024-01-18 | Bytedance Inc. | A neural network-based image and video compression method with conditional coding |
WO2024020112A1 (en) * | 2022-07-19 | 2024-01-25 | Bytedance Inc. | A neural network-based adaptive image and video compression method with variable rate |
TWI832406B (zh) * | 2022-09-01 | 2024-02-11 | 國立陽明交通大學 | 反向傳播訓練方法和非暫態電腦可讀取媒體 |
CN115294224B (zh) * | 2022-09-30 | 2022-12-16 | 南通市通州区华凯机械有限公司 | 用于驾驶模拟器的图像数据快速载入方法 |
WO2024073080A1 (en) * | 2022-09-30 | 2024-04-04 | Tesla, Inc. | A file format for efficient storage and access of data |
TWI824861B (zh) * | 2022-11-30 | 2023-12-01 | 國立陽明交通大學 | 機器學習裝置及其訓練方法 |
Family Cites Families (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US10706351B2 (en) * | 2016-08-30 | 2020-07-07 | American Software Safety Reliability Company | Recurrent encoder and decoder |
-
2020
- 2020-11-06 US US17/091,570 patent/US11405626B2/en active Active
-
2021
- 2021-01-15 TW TW110101726A patent/TW202135529A/zh unknown
- 2021-01-15 JP JP2022551741A patent/JP2023517846A/ja active Pending
- 2021-01-15 KR KR1020227029923A patent/KR20220150298A/ko unknown
- 2021-01-15 BR BR112022016793A patent/BR112022016793A2/pt unknown
- 2021-01-15 EP EP21703343.0A patent/EP4115617A1/en active Pending
- 2021-01-15 WO PCT/US2021/013599 patent/WO2021178050A1/en unknown
- 2021-01-15 CN CN202180017106.0A patent/CN115211115A/zh active Pending
Also Published As
Publication number | Publication date |
---|---|
JP2023517846A (ja) | 2023-04-27 |
EP4115617A1 (en) | 2023-01-11 |
US11405626B2 (en) | 2022-08-02 |
KR20220150298A (ko) | 2022-11-10 |
CN115211115A (zh) | 2022-10-18 |
WO2021178050A1 (en) | 2021-09-10 |
TW202135529A (zh) | 2021-09-16 |
US20210281867A1 (en) | 2021-09-09 |
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