CSSNet: Image-based clothing style switch

Shao Pin Huang, Der Lor Way*, Zen-Chung Shih

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review


We propose a framework, the CSSNet to exchange the upper clothes across people with different pose, body shape and clothing. We present an approach consists of three stages. (1) Disentangling the features, such as cloth, body pose and semantic segmentation from source and target person. (2) Synthesizing realistic and high resolution target dressing style images. (3) Transfer the complex logo from source clothing to target wearing. Our proposed end-to-end neural network architecture which can generate the specific person to wear the target clothing. In addition, we also propose a post process method to recover the complex logos on network outputs which are missing or blurring. Our results display more realistic and higher quality than previous methods. Our method can also preserve cloth shape and texture simultaneously.

Original languageAmerican English
Number of pages6
StatePublished - 1 Jun 2020
EventInternational Workshop on Advanced Imaging Technology, IWAIT 2020 - Yogyakarta, Indonesia
Duration: 5 Jan 20207 Jan 2020


ConferenceInternational Workshop on Advanced Imaging Technology, IWAIT 2020


  • Generative adversarial network
  • Human parsing
  • Pose estimation
  • Style transfer
  • Virtual try-on


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