single-jc.php

JACIII Vol.27 No.4 pp. 561-566
doi: 10.20965/jaciii.2023.p0561
(2023)

Research Paper:

Single Human Parsing Based on Visual Attention and Feature Enhancement

Zhi Ma* ORCID Icon, Lei Zhao** ORCID Icon, and Longsheng Wei*,** ORCID Icon

*Zhejiang Engineering Research Center of Intelligent Urban Infrastructure, Hangzhou City University
48 Huzhan Street, Hangzhou, Zhejiang 310015, China

**School of Automation, China University of Geosciences
388 Lumo Road, Hongshan District, Wuhan, Hubei 430074, China

Received:
January 8, 2023
Accepted:
March 6, 2023
Published:
July 20, 2023
Keywords:
human parsing, visual attention, feature enhancement, inherent structure
Abstract

Human parsing is one of the basic tasks in the field of computer vision. It aims at assigning pixel-level semantic labels to each human body part. Single human parsing requires further associating semantic parts with each instance. Aiming at the problem that it is difficult to distinguish the body parts with similar local features, this paper proposes a single human parsing method based on the visual attention mechanism. The proposed algorithm integrates advanced semantic features, global context information, and edge information to obtain accurate results of single human parsing resolution. The proposed algorithm is validated on standard look into part (LIP) dataset, and the results prove the effectiveness of the proposed algorithm.

Single human parsing network

Single human parsing network

Cite this article as:
Z. Ma, L. Zhao, and L. Wei, “Single Human Parsing Based on Visual Attention and Feature Enhancement,” J. Adv. Comput. Intell. Intell. Inform., Vol.27 No.4, pp. 561-566, 2023.
Data files:
References
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Last updated on Apr. 05, 2024