Unabridged adjacent modulation for clothing parsing

Zhang, Dong; Zuo, Chengting; Wu, Qianhao; Fu, Liyong; Xiang, Xinguang

doi:10.1016/j.patcog.2022.108594

“…Following the developments in deep learning technology, the successful use of FCNs for general semantic segmentation tasks has attracted the attention of researchers working on fashion parsing. Some researchers have performed clothing parsing by adding subsequent processing steps, such as CRF and additional discriminators, to the FCN architecture [56]. One group of researchers have focused on building an end-to-end fashion parsing framework by incorporating CRF into parsing neural networks [57].…”

Section: Fashion Parsingmentioning

confidence: 99%

Fashion Intelligence in the Metaverse: Promise and Future Prospects

Mu

¹

,

Zhang

²

,

Shi

³

et al. 2023

Preprint

1

0

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With the development of artificial intelligence (AI) and the constraints on offline activities imposed due to the sudden outbreak of the COVID epidemic, the Metaverse has recently attracted significant research attention from both academia and industrial practitioners. Fashion, as an expression of a consumer’s aesthetics and personality, has enormous economic potential in both the real world and the Metaverse. In this research, we provide a comprehensive survey of two of the most important components of fashion in the Metaverse: virtual digital humans, and tasks related to fashion items. We survey state-of-the-art articles from 2007 to the present and provide a new taxonomy of extant research topics based on these articles. We also highlight the applications of these topics in the Metaverse from the perspectives of designers and consumers. Finally, we describe possible scenes involving fashion in the Metaverse. The current challenges and open issues related to the fashion industry in the Metaverse are also discussed in order to provide guidance for fashion practitioners, and to shed some light on the future development of fashion AI in the Metaverse.

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“…With the popularity of clothing e-commerce, clothing segmentation task, clothing recommendation, and other tasks, has naturally become a hot topic of current research. Clothing image has a wide range of sources and complex environmental information, which is also affected by shooting angle and distance, human posture occlusion, and other issues [1] , resulting in low accuracy of clothing segmentation [2] . For these problems, scholars at home and abroad have proposed many methods.…”

Section: Introductionmentioning

confidence: 99%

Garment Segmentation Network Based on Texture and Semantic Decoding Module

Liu

¹

,

Li

²

,

Zhu

³

2023

J. Phys.: Conf. Ser.

0

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With the great development of the apparel e-commerce industry, more and more people are engaged in this field. In reality, clothing is easily affected by background, perspective, occlusion, and other factors, so clothing segmentation is not accurate enough. This paper proposes a clothing segmentation network based on the texture and semantic decoding module of clothing. Based on the swing transformer network, this network proposes a clothing texture analysis module (CTAM) and a clothing semantic decoding module (CSDM). In the coding process, CTAM extracts clothing texture features to enhance spatial information, while CSDM uses mixed attention to enhance image context information during decoding to improve the accuracy of clothing segmentation. The experimental results show that compared with the original model, the average pixel accuracy of the proposed method on the LIP data set is increased by about 2%, and the average crossover ratio is increased by about 1.5%. The segmentation network significantly improves indistinguishable garment boundaries and the accuracy of garment image segmentation.

show abstract

Fashion intelligence in the Metaverse: promise and future prospects

Mu,

Zhang,

Shi

et al. 2024

Artif Intell Rev

4

0

View full text Add to dashboard Cite

With the development of artificial intelligence (AI) and the constraints on offline activities imposed due to the sudden outbreak of the COVID epidemic, the Metaverse has recently attracted significant research attention from both academia and industrial practitioners. Fashion, as an expression of a consumer’s aesthetics and personality, has enormous economic potential in both the real world and the Metaverse. In this research, we provide a comprehensive survey of two of the most important components of fashion in the Metaverse: virtual digital humans, and tasks related to fashion items. We survey state-of-the-art articles from 2007 to the present and provide a new taxonomy of extant research topics based on these articles. We also highlight the applications of these topics in the Metaverse from the perspectives of designers and consumers. Finally, we describe possible scenes involving fashion in the Metaverse. The current challenges and open issues related to the fashion industry in the Metaverse are also discussed in order to provide guidance for fashion practitioners, and to shed some light on the future development of fashion AI in the Metaverse.

show abstract

Unabridged adjacent modulation for clothing parsing

Cited by 8 publications

References 11 publications

Fashion Intelligence in the Metaverse: Promise and Future Prospects

Fashion Intelligence in the Metaverse: Promise and Future Prospects

Garment Segmentation Network Based on Texture and Semantic Decoding Module

Fashion intelligence in the Metaverse: promise and future prospects

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