Kiss3DGen: Repurposing Image Diffusion Models for 3D Asset Generation
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Zhiyuan Ma PRO
ZhiyuanthePony
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3D Generation
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Kiss3DGen: Repurposing Image Diffusion Models for 3D Asset Generation
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🎉 Thrilled to share our #CVPR2025 accepted work:
https://huggingface.co/papers/2503.21694
🔥 Key Innovations:
1️⃣ First to adapt SD for direct textured mesh generation (1-2s inference)
2️⃣ Novel teacher-student framework leveraging multi-view diffusion models ([MVDream](https://arxiv.org/abs/2308.16512) & [RichDreamer](https://arxiv.org/abs/2311.16918))
3️⃣ Parameter-efficient tuning - only +2.6% params over base SD
4️⃣ 3D data-free training liberates model from dataset constraints
💡 Why matters?
→ A novel 3D-Data-Free paradigm
→ Outperforms data-driven methods on creative concept generation
→ Unlocks web-scale text corpus for 3D content creation
🌐 Project: https://theericma.github.io/TriplaneTurbo/
🎮 Demo: https://huggingface.co/spaces/ZhiyuanthePony/TriplaneTurbo
💻 Code: https://github.com/theEricMa/TriplaneTurbo
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🎉 Thrilled to share our #CVPR2025 accepted work:
Progressive Rendering Distillation: Adapting Stable Diffusion for Instant Text-to-Mesh Generation without 3D Data (2503.21694)
🔥 Key Innovations:
1️⃣ First to adapt SD for direct textured mesh generation (1-2s inference)
2️⃣ Novel teacher-student framework leveraging multi-view diffusion models ([MVDream](https://arxiv.org/abs/2308.16512) & [RichDreamer](https://arxiv.org/abs/2311.16918))
3️⃣ Parameter-efficient tuning - only +2.6% params over base SD
4️⃣ 3D data-free training liberates model from dataset constraints
💡 Why matters?
→ A novel 3D-Data-Free paradigm
→ Outperforms data-driven methods on creative concept generation
→ Unlocks web-scale text corpus for 3D content creation
🌐 Project: https://theericma.github.io/TriplaneTurbo/
🎮 Demo: ZhiyuanthePony/TriplaneTurbo
💻 Code: https://github.com/theEricMa/TriplaneTurbo
Progressive Rendering Distillation: Adapting Stable Diffusion for Instant Text-to-Mesh Generation without 3D Data (2503.21694)
🔥 Key Innovations:
1️⃣ First to adapt SD for direct textured mesh generation (1-2s inference)
2️⃣ Novel teacher-student framework leveraging multi-view diffusion models ([MVDream](https://arxiv.org/abs/2308.16512) & [RichDreamer](https://arxiv.org/abs/2311.16918))
3️⃣ Parameter-efficient tuning - only +2.6% params over base SD
4️⃣ 3D data-free training liberates model from dataset constraints
💡 Why matters?
→ A novel 3D-Data-Free paradigm
→ Outperforms data-driven methods on creative concept generation
→ Unlocks web-scale text corpus for 3D content creation
🌐 Project: https://theericma.github.io/TriplaneTurbo/
🎮 Demo: ZhiyuanthePony/TriplaneTurbo
💻 Code: https://github.com/theEricMa/TriplaneTurbo
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