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Summary of Editsplat: Multi-view Fusion and Attention-guided Optimization For View-consistent 3d Scene Editing with 3d Gaussian Splatting, by Dong in Lee et al.


EditSplat: Multi-View Fusion and Attention-Guided Optimization for View-Consistent 3D Scene Editing with 3D Gaussian Splatting

by Dong In Lee, Hyeongcheol Park, Jiyoung Seo, Eunbyung Park, Hyunje Park, Ha Dam Baek, Shin Sangheon, Sangmin kim, Sangpil Kim

First submitted to arxiv on: 16 Dec 2024

Categories

  • Main: Computer Vision and Pattern Recognition (cs.CV)
  • Secondary: Artificial Intelligence (cs.AI)

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Summary difficulty Written by Summary
High Paper authors High Difficulty Summary
Read the original abstract here
Medium GrooveSquid.com (original content) Medium Difficulty Summary
A novel text-driven method for real-time, user-friendly AR/VR applications is proposed in this paper. The approach, called EditSplat, integrates Multi-view Fusion Guidance (MFG) and Attention-Guided Trimming (AGT) to address limitations in current 3D editing methods, such as inefficient optimization and multi-view inconsistency. MFG ensures consistency by incorporating essential multi-view information into the diffusion process, while AGT selectively prunes and optimizes 3D Gaussians for enhanced efficiency and precise local edits. The proposed framework achieves superior results compared to existing methods, with significant improvements in both qualitative and quantitative evaluations.
Low GrooveSquid.com (original content) Low Difficulty Summary
EditSplat is a new way to edit 3D images using text. It’s like having a superpower that lets you change things in your virtual world just by typing what you want. Right now, it’s hard to make changes because computers get stuck trying to figure out what you mean. EditSplat makes it easier and faster by combining two special techniques: one helps with different views of the same object, and the other trims down extra information so the computer can work better. This means you can make more detailed changes to your 3D world.

Keywords

» Artificial intelligence  » Attention  » Diffusion  » Optimization