VITON: An Image-based Virtual Try-on Network
arXiv:1711.08447
Abstract
We present an image-based VIirtual Try-On Network (VITON) without using 3D information in any form, which seamlessly transfers a desired clothing item onto the corresponding region of a person using a coarse-to-fine strategy. Conditioned upon a new clothing-agnostic yet descriptive person representation, our framework first generates a coarse synthesized image with the target clothing item overlaid on that same person in the same pose. We further enhance the initial blurry clothing area with a refinement network. The network is trained to learn how much detail to utilize from the target clothing item, and where to apply to the person in order to synthesize a photo-realistic image in which the target item deforms naturally with clear visual patterns. Experiments on our newly collected Zalando dataset demonstrate its promise in the image-based virtual try-on task over state-of-the-art generative models.
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Cited by in corpus (5)
- Fashion-Gen: The Generative Fashion Dataset and Challenge
- Progressive Pose Attention Transfer for Person Image Generation
- Soft-Gated Warping-GAN for Pose-Guided Person Image Synthesis
- Toward Characteristic-Preserving Image-based Virtual Try-On Network
- Fashion is Taking Shape: Understanding Clothing Preference Based on Body Shape From Online Sources