Virtual Try-on (VTON) refers to the technology that allows users to try on clothing or accessories in a virtual environment, typically using generative models in AI. This technology digitally simulates how clothes, shoes, or accessories will look on a user without them physically wearing the items.
This repository primarily focuses on image, video, and 3D-based try-on models published after 2023, aiming to provide insights into the latest technological trends.
The project is ongoing, and we welcome contributions in any forms to help improve and expand it.
If you're interested in VTON or find this repo helpful, please 🌟star and 👀 watch it !
- [2024-12-22] PromptDresser: Improving the Quality and Controllability of Virtual Try-On via Generative Textual Prompt and Prompt-aware Mask (arXiv)
- [2024-12-11] Leffa: Learning Flow Fields in Attention for Controllable Person Image Generation (arXiv)
- [2024-11-22] FitDiT: Advancing the Authentic Garment Details for High-fidelity Virtual Try-on (arXiv)
- [2024-09-12] GarDiff: Improving Virtual Try-On with Garment-focused Diffusion Models (arXiv)
- [2024-08-26] MV-VTON: Multi-View Virtual Try-On with Diffusion Models (AAAI 2025)
- [2024-08-22] OutfitAnyone: Ultra-high Quality Virtual Try-On for Any Clothing and Any Person (arXiv)
- [2024-08-12] BooW-VTON: Boosting In-the-Wild Virtual Try-On via Mask-Free Pseudo Data Training (arXiv)
- [2024-07-21] CatVTON: Concatenation Is All You Need for Virtual Try-On with Diffusion Models (ICLR 2025)
- [2024-07-17] IMAGDressing-v1: Customizable Virtual Dressing (AAAI 2025)
- [2024-06-21] MaX4Zero: Masked Extended Attention for Zero-Shot Virtual Try-On In The Wild (arXiv)
- [2024-05-28] AnyFit: Controllable Virtual Try-on for Any Combination of Attire Across Any Scenario (arXiv)
- [2024-05-04] MMTryon: Multi-Modal Multi-Reference Control for High-Quality Fashion Generation (arXiv)
- [2024-05-01] FLDM-VTON: Faithful Latent Diffusion Model for Virtual Try-on (IJCAI 2024)
- [2024-04-01] Texture-Preserving Diffusion Models for High-Fidelity Virtual Try-On (CVPR 2024)
- [2024-03-19] IDM-VTON: Improving Diffusion Models for Virtual Try-on (ECCV 2024)
- [2024-03-07] OOTDiffusion: Outfitting Fusion based Latent Diffusion for Controllable Virtual Try-on (arXiv)
- [2024-03-01] Exploring Warping-Guided Features via Adaptive Latent Diffusion Model for Virtual Try-On (ICME 2024)
- [2023-12-06] WarpDiffusion: Efficient Diffusion Model for High-Fidelity Virtual Try-on (arXiv)
- [2023-12-04] StableVITON: Learning Semantic Correspondence with Latent Diffusion Model for Virtual Try-On (CVPR 2024)
- [2023-11-27] Street TryOn: Learning In-the-Wild Virtual Try-On from Unpaired Person Images (WACV 2025)
- [2023-08-11] DCI-VTON: Taming the Power of Diffusion Models for High-Quality Virtual Try-On with Appearance Flow (ACMMM 2023)
- [2023-08-03] LaDI-VTON: Latent Diffusion Textual-Inversion Enhanced Virtual Try-On (ACMMM 2023)
- [2023-06-14] TryOnDiffusion: A Tale of Two UNets (CVPR 2023)
- [2023-03-24] GP-VTON: Towards General Purpose Virtual Try-On via Collaborative Local-Flow Global-Parsing Learning (CVPR 2023)
- [2024-12-05] PEMF-VVTO: Point-Enhanced Video Virtual Try-on via Mask-free Paradigm (arXiv)
- [2024-11-04] Fashion-VDM: Video Diffusion Model for Virtual Try-On (SIGGRAPH Asia 2024)
- [2024-07-15] WildVidFit: Video Virtual Try-On in the Wild via Image-Based Controlled Diffusion Models (arXiv)
- [2024-06-07] VITON-DiT: Learning In-the-Wild Video Try-On from Human Dance Videos via Diffusion Transformers (arXiv)
- [2024-05-20] ViViD: Video Virtual Try-on using Diffusion Models (arXiv)
- [2024-04-26] Tunnel Try-on: Excavating Spatial-temporal Tunnels for High-quality Virtual Try-on in Videos (arXiv)
- [2024-10-07] GS-VTON: Controllable 3D Virtual Try-on with Gaussian Splatting (arXiv)
- [2024-07-23] DreamVTON: Customizing 3D Virtual Try-on with Personalized Diffusion Models (ACMMM 2024)
- [2024-05-13] GaussianVTON: 3D Human Virtual Try-ON via Multi-Stage Gaussian Splatting Editing with Image Prompting (arXiv)
