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๐ Thrilled to share our #CVPR2025 accepted work:
Progressive Rendering Distillation: Adapting Stable Diffusion for Instant Text-to-Mesh Generation without 3D Data (2503.21694)
๐ฅ โKey Innovations:
1๏ธโฃ First to adapt SD for โdirect textured mesh generation (1-2s inference)
2๏ธโฃ Novel teacher-student framework leveraging multi-view diffusion models ([MVDream](https://arxiv.org/abs/2308.16512) & [RichDreamer](https://arxiv.org/abs/2311.16918))
3๏ธโฃ โParameter-efficient tuning - โonly +2.6% params over base SD
4๏ธโฃ โ3D data-free training liberates model from dataset constraints
๐ก Why matters?
โ A novel โ3D-Data-Free paradigm
โ Outperforms data-driven methods on creative concept generation
โ Unlocks web-scale text corpus for 3D content creation
๐ Project: https://theericma.github.io/TriplaneTurbo/
๐ฎ Demo: ZhiyuanthePony/TriplaneTurbo
๐ป Code: https://github.com/theEricMa/TriplaneTurbo
Progressive Rendering Distillation: Adapting Stable Diffusion for Instant Text-to-Mesh Generation without 3D Data (2503.21694)
๐ฅ โKey Innovations:
1๏ธโฃ First to adapt SD for โdirect textured mesh generation (1-2s inference)
2๏ธโฃ Novel teacher-student framework leveraging multi-view diffusion models ([MVDream](https://arxiv.org/abs/2308.16512) & [RichDreamer](https://arxiv.org/abs/2311.16918))
3๏ธโฃ โParameter-efficient tuning - โonly +2.6% params over base SD
4๏ธโฃ โ3D data-free training liberates model from dataset constraints
๐ก Why matters?
โ A novel โ3D-Data-Free paradigm
โ Outperforms data-driven methods on creative concept generation
โ Unlocks web-scale text corpus for 3D content creation
๐ Project: https://theericma.github.io/TriplaneTurbo/
๐ฎ Demo: ZhiyuanthePony/TriplaneTurbo
๐ป Code: https://github.com/theEricMa/TriplaneTurbo
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