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Awesome-Try-On-Models
3d-generation

Awesome-Try-On-Models

A repository for organizing papers, codes and other resources related to Virtual Try-on Models

by Zheng-Chong · GitHub
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3d-generationdiffusion-modelsimage-generation
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Access and contribute to resources about virtual clothing try-on technology using AI models.

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2026-07-202026-08-31
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📄 About

A repository for organizing papers, codes and other resources related to Virtual Try-on Models

Awesome-Try-On-Models has 436 stars on GitHub. It has been forked 27 times. It has been in active development since 2024. Its main topics are 3d-generation, diffusion-models, image-generation, sota-model.

Frequently asked questions

What is Awesome-Try-On-Models?

A repository for organizing papers, codes and other resources related to Virtual Try-on Models

Is Awesome-Try-On-Models open source?

Awesome-Try-On-Models is an open-source project.

Is Awesome-Try-On-Models free?

Yes. Awesome-Try-On-Models is free and open source — you can use, modify and self-host it.

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🧬 Shares DNA with🧬 View the DNA map →
sjc
Score Jacobian Chaining: Lifting Pretrained 2D Diffusion Models for 3D Generation (CVPR 2023)
523 · 3d-generation
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sparsefusion
[CVPR 2023] SparseFusion: Distilling View-conditioned Diffusion for 3D Reconstruction
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Magic123
[ICLR'24] Official PyTorch Implementation of Magic123: One Image to High-Quality 3D Object Gene…
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Text2Room generates textured 3D meshes from a given text prompt using 2D text-to-image models (…
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VistaDream
[ICCV 2025] VistaDream: Sampling multiview consistent images for single-view scene reconstructi…
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High-Resolution 3D Assets Generation with Large Scale Hunyuan3D Diffusion Models.
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[CVPR 2025 Highlight] 3DTopia-XL: High-Quality 3D PBR Asset Generation via Primitive Diffusion
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FireRed-Image-Edit is a powerful image editing foundation model achieving open-source state-of-…
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Measured from GitHub topics shared by both projects, weighted by how rare each topic is.