EISNet: A Multi-Modal Fusion Network for Semantic Segmentation With Events and Images-Reference-Cited by-同舟云学术

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EISNet: A Multi-Modal Fusion Network for Semantic Segmentation With Events and Images

Published:2024 Issue: Volume:26 Page:8639-8650
ISSN:1520-9210
Container-title:IEEE Transactions on Multimedia
language:
Short-container-title:IEEE Trans. Multimedia

Author:

Xie Bochen¹^ORCID,Deng Yongjian²^ORCID,Shao Zhanpeng³^ORCID,Li Youfu¹^ORCID

Affiliation:

1. Department of Mechanical Engineering, City University of Hong Kong, Hong Kong SAR, China

2. College of Computer Science, Beijing University of Technology, Beijing, China

3. College of Information Science and Engineering, Hunan Normal University, Changsha, China

Funder

Research Grants Council of Hong Kong

National Natural Science Foundation of China

R&D Program of Beijing Municipal Education Commission

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6046/10384483/10477577.pdf?arnumber=10477577

Reference49 articles.

1. Image Segmentation Using Deep Learning: A Survey

2. Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers

3. SegFormer: Simple and efficient design for semantic segmentation with transformers;Xie,2021

4. SegNeXt: Rethinking convolutional attention design for semantic segmentation;Guo,2022

5. Event-Based Vision: A Survey

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