AIParsing: Anchor-Free Instance-Level Human Parsing-Reference-Cited by-同舟云学术

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AIParsing: Anchor-Free Instance-Level Human Parsing

Published:2022 Issue: Volume:31 Page:5599-5612
ISSN:1057-7149
Container-title:IEEE Transactions on Image Processing
language:
Short-container-title:IEEE Trans. on Image Process.

Author:

Zhang Sanyi¹^ORCID,Cao Xiaochun²^ORCID,Qi Guo-Jun³^ORCID,Song Zhanjie⁴^ORCID,Zhou Jie⁵^ORCID

Affiliation:

1. State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China

2. School of Cyber Science and Technology, Shenzhen Campus, Sun Yat-sen University, Shenzhen, China

3. Futurewei Technologies, Seattle, WA, USA

4. Georgia Tech Shenzhen Institute, Tianjin University, Shenzhen, China

5. Department of Automation, Tsinghua University, Beijing, China

Funder

Shenzhen Sustainable Development Project

National Natural Science Foundation of China

Open Project Program of State Key Laboratory of Virtual Reality Technology and Systems, Beihang University

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Graphics and Computer-Aided Design,Software

Link

http://xplorestaging.ieee.org/ielx7/83/9626658/09866618.pdf?arnumber=9866618

Reference74 articles.

1. Deep hierarchical semantic segmentation;li;Proc IEEE Conf CVPR,2022

2. Pyramid Scene Parsing Network

3. Flow-Guided Feature Aggregation for Video Object Detection

4. Deep Feature Flow for Video Recognition

5. Learning Compositional Neural Information Fusion for Human Parsing

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3. Edge devices friendly multi-human parsing with lightweight encoding and multi-scale self-attention based decoding;Multimedia Tools and Applications;2024-08-27

4. WNet: A dual‐encoded multi‐human parsing network;IET Image Processing;2024-07-10

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