LA-VITON: A Network for Looking-Attractive Virtual Try-On
| Autor: | Myounghoon Cho, Rokkyu Lee, Hyug Jae Lee, Minseok Kang, Gunhan Park |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Computer science
business.industry Distortion (optics) 010401 analytical chemistry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 02 engineering and technology Interval (mathematics) Grid 01 natural sciences GeneralLiterature_MISCELLANEOUS 0104 chemical sciences Image (mathematics) Consistency (database systems) Transformation (function) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computer vision Artificial intelligence Image warping business ComputingMethodologies_COMPUTERGRAPHICS |
| Zdroj: | ICCV Workshops |
| DOI: | 10.1109/iccvw.2019.00381 |
| Popis: | In this paper, we propose an image-based virtual try-on network, LA-VITON, which allows the generation of high fidelity try-on images that preserves both the overall appearance and the characteristics of clothing items. The proposed network consists of two modules: Geometric Matching Module (GMM) and Try-On Module (TOM). To warp in-shop clothing item to the desired image of a person with high accuracy in GMM, grid interval consistency loss and an occlusion handling technique are proposed. Grid interval consistency loss regularizes transformation to prevent distortion of patterns in clothes and an occlusion handling technique encourages proper warping despite target bodies are covered by hair or arms. The following TOM synthesizes the final try-on image of the target person seamlessly with the warped clothes from GMM. Extensive experiments on fashion datasets show that the proposed method outperforms the state-of-the-art methods. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|