Ms. Jiaqi Chen Profile

Jiaqi Chen

at Fuzhou Univ

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Proceedings Article | 16 February 2022 Paper

Layout-aware bidirectional transfer network for fashion landmark detection

Huosheng Xie, Jiaqi Chen

Proceedings Volume 12083, 120831W (2022) https://doi.org/10.1117/12.2623435

KEYWORDS: Convolution, Visualization, Visual analytics, Neural networks, Feature extraction, Data processing, Analytical research, Performance modeling

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As a pivotal technique of fashion visual analysis, fashion landmark detection has attracted extensive attention in recent years. However, prior works often ignore the importance of structural layout information for fashion landmark detection, which leads to ambiguous detection results of hard landmarks. In this paper, we propose a Layout-Aware Bidirectional Transfer Network(LBTNet) which first combines the layout features learning with a powerful human pose estimation backbone - HRNet. The LBTNet can learn the layout information by our proposed Group-wise Layout Embedded Module(GLEM) which can model the dependency among fashion landmarks on the convolutional layer and perform information passing among the adjacent landmarks. We also design a novel head structure called Bidirectional Transfer Module(BTM) to capture global semantic information of fashion landmarks through a bidirectional transmission path. Therefore, the LBTNet can accurately detect these hard landmarks (e.g. occluded landmarks and invisible landmarks). And the experimental results on two large-scale fashion datasets show that our LBTNet outperforms the state-of-the-art methods by a large margin.

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