✨InstructMix2Mix: Consistent Sparse-View Editing Through Multi-View Model Personalization
📝 Summary:
InstructMix2Mix I-Mix2Mix improves multi-view image editing from sparse inputs, which often lack consistency. It distills a 2D diffusion model into a multi-view diffusion model, leveraging its 3D prior for cross-view coherence. This framework significantly enhances multi-view consistency and per-...
🔹 Publication Date: Published on Nov 18
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.14899
• PDF: https://arxiv.org/pdf/2511.14899
• Project Page: https://danielgilo.github.io/instruct-mix2mix/
• Github: https://danielgilo.github.io/instruct-mix2mix/
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For more data science resources:
✓ https://xn--r1a.website/DataScienceT
#MultiViewEditing #DiffusionModels #ComputerVision #3DVision #ImageSynthesis
📝 Summary:
InstructMix2Mix I-Mix2Mix improves multi-view image editing from sparse inputs, which often lack consistency. It distills a 2D diffusion model into a multi-view diffusion model, leveraging its 3D prior for cross-view coherence. This framework significantly enhances multi-view consistency and per-...
🔹 Publication Date: Published on Nov 18
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.14899
• PDF: https://arxiv.org/pdf/2511.14899
• Project Page: https://danielgilo.github.io/instruct-mix2mix/
• Github: https://danielgilo.github.io/instruct-mix2mix/
==================================
For more data science resources:
✓ https://xn--r1a.website/DataScienceT
#MultiViewEditing #DiffusionModels #ComputerVision #3DVision #ImageSynthesis
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