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Slimmable Multi-Task Image Compression for Human and Machine Vision

  • Published:2023 Issue: Volume:11 Page:29946-29958
  • ISSN:2169-3536
  • Container-title:IEEE Access
  • language:
  • Short-container-title:IEEE Access

Author:

Cao Jiangzhong1,Yao Ximei1ORCID,Zhang Huan1ORCID,Jin Jian2ORCID,Zhang Yun3,Ling Bingo Wing-Kuen1ORCID

Affiliation:

1. School of Information Engineering, Guangdong University of Technology, Guangzhou, China

2. Alibaba-NTU Singapore Joint Research Institute, Nanyang Technological University, Jurong West, Singapore

3. School of Electronics and Communication Engineering, Sun Yat-sen University, Shenzhen, China

Funder

Joint Fund of the National Natural Science Foundation of China and Guangdong Province

Guangdong Provincial Key Laboratory of Intellectual Property and Big Data

Basic and Applied Basic Research Foundation of Guangdong Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Reference37 articles.

1. Towards image understanding from deep compression without decoding;torfason;arXiv 1803 06131,2018

2. YOLOv3: An incremental improvement;redmon;arXiv 1804 02767,2018

3. Semantic-Preserving Image Compression

4. Semantically Scalable Image Coding With Compression of Feature Maps

5. Towards Coding for Human and Machine Vision: Scalable Face Image Coding

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