Virtual Try-On: Real-Time Interactive Hybrid Network with High-Fidelity


  • Umer Waqas AItheNutrigene
  • Yunwan Jeon AItheNutrigene
  • Donghun Lee AItheNutrigene



Artificial Intelligence, Visual processing


A significant upsurge in the fashion e-commerce industry in recent years has brought considerable attention to image-based virtual fitting. This image-based technology allows users to try on clothes virtually without physically touching them. However, the current techniques have notable limitations in terms of real-world scenarios, noisy results, partial clothing categories and computational cost, thus limiting the real-world applications. To address these critical limitations, we propose a hybrid interactive network that allows actual users to interact with the system to try on clothes virtually. The network is composed of state of art keypoint extraction, appearance flow alteration and wrapping modules. The pro-posed network facilitates real-time application with high-quality noise-free results, a variety of clothing categories and efficient computational cost.




How to Cite

Waqas, U., Jeon, Y., & Lee, D. (2024). Virtual Try-On: Real-Time Interactive Hybrid Network with High-Fidelity. Proceedings of the AAAI Conference on Artificial Intelligence, 38(21), 23847-23849.