EP4062375A4 - METHOD AND APPARATUS FOR QUANTIZATION, ADAPTIVE BLOCK PARTITIONING AND CODEBOOK CODING FOR COMPRESSION OF A NEURAL NETWORK MODEL - Google Patents

METHOD AND APPARATUS FOR QUANTIZATION, ADAPTIVE BLOCK PARTITIONING AND CODEBOOK CODING FOR COMPRESSION OF A NEURAL NETWORK MODEL Download PDF

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Publication number
EP4062375A4
EP4062375A4 EP20890921.8A EP20890921A EP4062375A4 EP 4062375 A4 EP4062375 A4 EP 4062375A4 EP 20890921 A EP20890921 A EP 20890921A EP 4062375 A4 EP4062375 A4 EP 4062375A4
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EP
European Patent Office
Prior art keywords
quantization
neural network
network model
block partitioning
model compression
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
EP20890921.8A
Other languages
German (de)
English (en)
French (fr)
Other versions
EP4062375A1 (en
Inventor
Wei Wang
Wei Jiang
Shan Liu
Byeongdoo CHOI
Stephan Wenger
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Tencent America LLC
Original Assignee
Tencent America LLC
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from US17/099,202 external-priority patent/US11245903B2/en
Application filed by Tencent America LLC filed Critical Tencent America LLC
Publication of EP4062375A1 publication Critical patent/EP4062375A1/en
Publication of EP4062375A4 publication Critical patent/EP4062375A4/en
Pending legal-status Critical Current

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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
    • 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
    • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • H04N19/119—Adaptive subdivision aspects, e.g. subdivision of a picture into rectangular or non-rectangular coding blocks
    • 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
    • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • H04N19/124—Quantisation
    • 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
    • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • H04N19/129—Scanning of coding units, e.g. zig-zag scan of transform coefficients or flexible macroblock ordering [FMO]
    • 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
    • H04N19/70—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals characterised by syntax aspects related to video coding, e.g. related to compression standards
    • 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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  • Engineering & Computer Science (AREA)
  • Signal Processing (AREA)
  • Multimedia (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • General Health & Medical Sciences (AREA)
  • Computing Systems (AREA)
  • Computational Linguistics (AREA)
  • Data Mining & Analysis (AREA)
  • Evolutionary Computation (AREA)
  • Biomedical Technology (AREA)
  • Molecular Biology (AREA)
  • Biophysics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
  • Software Systems (AREA)
  • Artificial Intelligence (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Health & Medical Sciences (AREA)
  • Compression Or Coding Systems Of Tv Signals (AREA)
EP20890921.8A 2019-11-22 2020-11-19 METHOD AND APPARATUS FOR QUANTIZATION, ADAPTIVE BLOCK PARTITIONING AND CODEBOOK CODING FOR COMPRESSION OF A NEURAL NETWORK MODEL Pending EP4062375A4 (en)

Applications Claiming Priority (6)

Application Number Priority Date Filing Date Title
US201962939057P 2019-11-22 2019-11-22
US201962939054P 2019-11-22 2019-11-22
US201962939949P 2019-11-25 2019-11-25
US201962947236P 2019-12-12 2019-12-12
US17/099,202 US11245903B2 (en) 2019-11-22 2020-11-16 Method and apparatus for quantization, adaptive block partitioning and codebook coding for neural network model compression
PCT/US2020/061258 WO2021102125A1 (en) 2019-11-22 2020-11-19 Method and apparatus for quantization, adaptive block partitioning and codebook coding for neural network model compression

Publications (2)

Publication Number Publication Date
EP4062375A1 EP4062375A1 (en) 2022-09-28
EP4062375A4 true EP4062375A4 (en) 2022-12-28

Family

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EP20890921.8A Pending EP4062375A4 (en) 2019-11-22 2020-11-19 METHOD AND APPARATUS FOR QUANTIZATION, ADAPTIVE BLOCK PARTITIONING AND CODEBOOK CODING FOR COMPRESSION OF A NEURAL NETWORK MODEL

Country Status (5)

Country Link
EP (1) EP4062375A4 (zh)
JP (1) JP7337950B2 (zh)
KR (1) KR20210136123A (zh)
CN (1) CN113795869B (zh)
WO (1) WO2021102125A1 (zh)

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113766237B (zh) * 2021-09-30 2024-07-02 咪咕文化科技有限公司 一种编码方法、解码方法、装置、设备及可读存储介质
TWI795135B (zh) * 2021-12-22 2023-03-01 財團法人工業技術研究院 神經網路模型的量化方法及深度學習加速器
TWI819627B (zh) * 2022-05-26 2023-10-21 緯創資通股份有限公司 用於深度學習網路的優化方法、運算裝置及電腦可讀取媒體

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20190347550A1 (en) * 2018-05-14 2019-11-14 Samsung Electronics Co., Ltd. Method and apparatus with neural network parameter quantization

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US9565437B2 (en) 2013-04-08 2017-02-07 Qualcomm Incorporated Parameter set designs for video coding extensions
US10223635B2 (en) 2015-01-22 2019-03-05 Qualcomm Incorporated Model compression and fine-tuning
US10515307B2 (en) * 2015-06-05 2019-12-24 Google Llc Compressed recurrent neural network models
US11593632B2 (en) * 2016-12-15 2023-02-28 WaveOne Inc. Deep learning based on image encoding and decoding
EP3564864A4 (en) 2016-12-30 2020-04-15 Shanghai Cambricon Information Technology Co., Ltd DEVICES FOR COMPRESSION / DECOMPRESSION, SYSTEM, CHIP AND ELECTRONIC DEVICE
US11403528B2 (en) 2018-05-31 2022-08-02 Kneron (Taiwan) Co., Ltd. Self-tuning incremental model compression solution in deep neural network with guaranteed accuracy performance
WO2020190772A1 (en) * 2019-03-15 2020-09-24 Futurewei Technologies, Inc. Neural network model compression and optimization
EP3716158A3 (en) * 2019-03-25 2020-11-25 Nokia Technologies Oy Compressing weight updates for decoder-side neural networks
CN110263913A (zh) * 2019-05-23 2019-09-20 深圳先进技术研究院 一种深度神经网络压缩方法及相关设备
CN110276451A (zh) * 2019-06-28 2019-09-24 南京大学 一种基于权重归一化的深度神经网络压缩方法
CN110443359A (zh) * 2019-07-03 2019-11-12 中国石油大学(华东) 基于自适应联合剪枝-量化的神经网络压缩算法
US11671110B2 (en) 2019-11-22 2023-06-06 Tencent America LLC Method and apparatus for neural network model compression/decompression

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20190347550A1 (en) * 2018-05-14 2019-11-14 Samsung Electronics Co., Ltd. Method and apparatus with neural network parameter quantization

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
AL-HAMI MO'TAZ ET AL: "Methodologies of Compressing a Stable Performance Convolutional Neural Networks in Image Classification", NEURAL PROCESSING LETTERS, KLUWER ACADEMIC PUBLISHERS, NORWELL, MA, US, vol. 51, no. 1, 20 July 2019 (2019-07-20), pages 105 - 127, XP037048818, ISSN: 1370-4621, [retrieved on 20190720], DOI: 10.1007/S11063-019-10076-Y *

Also Published As

Publication number Publication date
CN113795869A (zh) 2021-12-14
CN113795869B (zh) 2023-08-18
WO2021102125A1 (en) 2021-05-27
JP7337950B2 (ja) 2023-09-04
EP4062375A1 (en) 2022-09-28
KR20210136123A (ko) 2021-11-16
JP2022533307A (ja) 2022-07-22

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