Virtual Try-on
57 papers with code • 5 benchmarks • 10 datasets
Virtual try-on of clothing or other items such as glasses and makeup. Most recent techniques use Generative Adversarial Networks.
Datasets
DeepFashion
VITON
VITON-HD
Deep Fashion3D
MoVi
Dress Code
STRAT
Most implemented papers
VITON: An Image-based Virtual Try-on Network
xthan/VITON
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CVPR 2018
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.
Toward Characteristic-Preserving Image-based Virtual Try-On Network
sergeywong/cp-vton
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ECCV 2018
Second, to alleviate boundary artifacts of warped clothes and make the results more realistic, we employ a Try-On Module that learns a composition mask to integrate the warped clothes and the rendered image to ensure smoothness.
VITON-GAN: Virtual Try-on Image Generator Trained with Adversarial Loss
Generating a virtual try-on image from in-shop clothing images and a model person's snapshot is a challenging task because the human body and clothes have high flexibility in their shapes.
Towards Photo-Realistic Virtual Try-On by Adaptively Generating$\leftrightarrow$Preserving Image Content
switchablenorms/DeepFashion_Try_On
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First, a semantic layout generation module utilizes semantic segmentation of the reference image to progressively predict the desired semantic layout after try-on.
Style-Based Global Appearance Flow for Virtual Try-On
senhe/flow-style-vton
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CVPR 2022
To achieve this, a key step is garment warping which spatially aligns the target garment with the corresponding body parts in the person image.
Real-time deep hair matting on mobile devices
jtiger958/hair-segmentation-pytorch
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Augmented reality is an emerging technology in many application domains.
Deep Fashion3D: A Dataset and Benchmark for 3D Garment Reconstruction from Single Images
ZhengZerong/DeepHuman
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ECCV 2020
High-fidelity clothing reconstruction is the key to achieving photorealism in a wide range of applications including human digitization, virtual try-on, etc.
CP-VTON+: Clothing Shape and Texture Preserving Image-Based Virtual Try-On
minar09/cp-vton-plus
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CVPRW 2020
Recently proposed Image-based virtual try-on (VTON) approaches have several challenges regarding diverse human poses and cloth styles.
Parser-Free Virtual Try-on via Distilling Appearance Flows
A recent pioneering work employed knowledge distillation to reduce the dependency of human parsing, where the try-on images produced by a parser-based method are used as supervisions to train a "student" network without relying on segmentation, making the student mimic the try-on ability of the parser-based model.
RMGN: A Regional Mask Guided Network for Parser-free Virtual Try-on
Virtual try-on(VTON) aims at fitting target clothes to reference person images, which is widely adopted in e-commerce. Existing VTON approaches can be narrowly categorized into Parser-Based(PB) and Parser-Free(PF) by whether relying on the parser information to mask the persons' clothes and synthesize try-on images.
