BlenderFusion: 3D-Grounded Visual Editing and Generative Compositing

Jiacheng Chen, Ramin Mehran, Xuhui Jia, Saining Xie, Sanghyun Woo
6/20/2025
cs.CVcs.GR

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Abstract

We present BlenderFusion, a generative visual compositing framework that synthesizes new scenes by recomposing objects, camera, and background. It follows a layering-editing-compositing pipeline: (i) segmenting and converting visual inputs into editable 3D entities (layering), (ii) editing them in Blender with 3D-grounded control (editing), and (iii) fusing them into a coherent scene using a generative compositor (compositing). Our generative compositor extends a pre-trained diffusion model to process both the original (source) and edited (target) scenes in parallel. It is fine-tuned on video frames with two key training strategies: (i) source masking, enabling flexible modifications like background replacement; (ii) simulated object jittering, facilitating disentangled control over objects and camera. BlenderFusion significantly outperforms prior methods in complex compositional scene editing tasks.

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Cite this paper

@article{chen2025blenderfusion,
  title  = {BlenderFusion: 3D-Grounded Visual Editing and Generative Compositing},
  author = {Jiacheng Chen and Ramin Mehran and Xuhui Jia and Saining Xie and Sanghyun Woo},
  year   = {2025},
  eprint = {2506.17450},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2506.17450v2}
}

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