Small Object-Aware Video Coding for Machines via Feature-Motion Synergy-Reference-Cited by-同舟云学术

Small Object-Aware Video Coding for Machines via Feature-Motion Synergy

Published:2024 Issue: Volume:21 Page:1-5
ISSN:1545-598X
Container-title:IEEE Geoscience and Remote Sensing Letters
language:
Short-container-title:IEEE Geosci. Remote Sensing Lett.

Author:

Xu Qihan¹^ORCID,Xi Bobo²^ORCID,Xu Haitao¹,Huang Yun¹,Li Yunsong²^ORCID,Chanussot Jocelyn³^ORCID

Affiliation:

1. Key Laboratory of Electronics and Information Technology for Space Systems, National Space Science Center, Chinese Academy of Sciences, Beijing, China

2. State Key Laboratory of Integrated Service Networks, School of Telecommunications Engineering, Xidian University, Xi’an, China

3. GIPSA-Laboratory, CNRS, Grenoble INP, Université Grenoble Alpes, Grenoble, France

Funder

Key Research Program of the Chinese Academy of Sciences

General Financial Grant from the China Postdoctoral Science Foundation

Youth Open Project of National Space Science Data Center

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Geotechnical Engineering and Engineering Geology

Link

http://xplorestaging.ieee.org/ielx7/8859/10365397/10368029.pdf?arnumber=10368029

Reference18 articles.

1. Dense Nested Attention Network for Infrared Small Target Detection

2. Video Coding for Machines: A Paradigm of Collaborative Compression and Intelligent Analytics

3. A Joint Compression Scheme of Video Feature Descriptors and Visual Content

4. Efficient Partition Decision Based on Visual Perception and Machine Learning for H.266/Versatile Video Coding

5. An Emerging Coding Paradigm Vcm: A Scalable Coding Approach Beyond Feature And Signal