Virtual Try-on
79 papers with code • 7 benchmarks • 11 datasets
Virtual try-on of clothing or other items such as glasses and makeup. Most recent techniques use Generative Adversarial Networks.
Benchmarks
These leaderboards are used to track progress in Virtual Try-on
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Libraries
Use these libraries to find Virtual Try-on models and implementationsDatasets
DeepFashion
VITON
VITON-HD
Deep Fashion3D
Dress Code
MoVi
STRAT
Latest papers
MV-VTON: Multi-View Virtual Try-On with Diffusion Models
To address this challenge, we introduce Multi-View Virtual Try-ON (MV-VTON), which aims to reconstruct the dressing results of a person from multiple views using the given clothes.
HiLo: Detailed and Robust 3D Clothed Human Reconstruction with High-and Low-Frequency Information of Parametric Models
We empirically find that the high-frequency (HF) and low-frequency (LF) information from a parametric model has the potential to enhance geometry details and improve robustness to noise, respectively.
Texture-Preserving Diffusion Models for High-Fidelity Virtual Try-On
gal4way/tpd
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Second, we propose a novel diffusion-based method that predicts a precise inpainting mask based on the person and reference garment images, further enhancing the reliability of the try-on results.
TryOn-Adapter: Efficient Fine-Grained Clothing Identity Adaptation for High-Fidelity Virtual Try-On
jiazheng-xing/tryon-adapter
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However, the clothing identity uncontrollability and training inefficiency of existing diffusion-based methods, which struggle to maintain the identity even with full parameter training, are significant limitations that hinder the widespread applications.
Multimodal-Conditioned Latent Diffusion Models for Fashion Image Editing
aimagelab/multimodal-garment-designer
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Fashion illustration is a crucial medium for designers to convey their creative vision and transform design concepts into tangible representations that showcase the interplay between clothing and the human body.
Improving Diffusion Models for Virtual Try-on
yisol/IDM-VTON
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Finally, we present a customization method using a pair of person-garment images, which significantly improves fidelity and authenticity.
OOTDiffusion: Outfitting Fusion based Latent Diffusion for Controllable Virtual Try-on
We present OOTDiffusion, a novel network architecture for realistic and controllable image-based virtual try-on (VTON).
Towards Squeezing-Averse Virtual Try-On via Sequential Deformation
In this paper, we first investigate a visual quality degradation problem observed in recent high-resolution virtual try-on approach.
StableVITON: Learning Semantic Correspondence with Latent Diffusion Model for Virtual Try-On
Given a clothing image and a person image, an image-based virtual try-on aims to generate a customized image that appears natural and accurately reflects the characteristics of the clothing image.
CAT-DM: Controllable Accelerated Virtual Try-on with Diffusion Model
Generative Adversarial Networks (GANs) dominate the research field in image-based virtual try-on, but have not resolved problems such as unnatural deformation of garments and the blurry generation quality.
