Virtual Try-on
80 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
Most implemented papers
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.
Fill in Fabrics: Body-Aware Self-Supervised Inpainting for Image-Based Virtual Try-On
Previous virtual try-on methods usually focus on aligning a clothing item with a person, limiting their ability to exploit the complex pose, shape and skin color of the person, as well as the overall structure of the clothing, which is vital to photo-realistic virtual try-on.
C-VTON: Context-Driven Image-Based Virtual Try-On Network
At the core of the C-VTON pipeline are: (i) a geometric matching procedure that efficiently aligns the target clothing with the pose of the person in the input images, and (ii) a powerful image generator that utilizes various types of contextual information when synthesizing the final try-on result.
OccluMix: Towards De-Occlusion Virtual Try-on by Semantically-Guided Mixup
Image Virtual try-on aims at replacing the cloth on a personal image with a garment image (in-shop clothes), which has attracted increasing attention from the multimedia and computer vision communities.
AnyDoor: Zero-shot Object-level Image Customization
This work presents AnyDoor, a diffusion-based image generator with the power to teleport target objects to new scenes at user-specified locations in a harmonious way.
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).
Multimodal-Conditioned Latent Diffusion Models for Fashion Image Editing
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.
Detailed, accurate, human shape estimation from clothed 3D scan sequences
We address the problem of estimating human pose and body shape from 3D scans over time.
Video Based Reconstruction of 3D People Models
This paper describes how to obtain accurate 3D body models and texture of arbitrary people from a single, monocular video in which a person is moving.
SwapNet: Garment Transfer in Single View Images
andrewjong/SwapNet
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ECCV 2018
Garment transfer is a challenging task that requires (i) disentangling the features of the clothing from the body pose and shape and (ii) realistic synthesis of the garment texture on the new body.
