Summary of Layoutvlm: Differentiable Optimization Of 3d Layout Via Vision-language Models, by Fan-yun Sun et al.
LayoutVLM: Differentiable Optimization of 3D Layout via Vision-Language Models
by Fan-Yun Sun, Weiyu Liu, Siyi Gu, Dylan Lim, Goutam Bhat, Federico Tombari, Manling Li, Nick Haber, Jiajun Wu
First submitted to arxiv on: 3 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 LayoutVLM, a novel framework and scene layout representation, tackles the challenge of spatial reasoning in 3D environments. While foundation models excel on some benchmarks, they struggle with tasks like arranging objects according to open-ended language instructions, particularly in dense environments. LayoutVLM exploits the semantic knowledge of Vision-Language Models (VLMs) and supports differentiable optimization for physical plausibility. It generates two mutually reinforcing representations from visually marked images and uses a self-consistent decoding process to improve VLM spatial planning. Our experiments demonstrate that LayoutVLM addresses existing limitations, producing physically plausible 3D layouts aligned with input language instructions. Fine-tuning VLMs with the proposed scene layout representation can also enhance their reasoning performance. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper is about helping computers understand and arrange objects in three-dimensional space. Computers are really good at some things, but they struggle to follow instructions that involve arranging objects in a specific way. The researchers created a new system called LayoutVLM that uses computer vision and language models to help computers better understand and follow these instructions. This system can even improve the performance of existing computer systems by teaching them how to better arrange objects in space. |
Keywords
» Artificial intelligence » Fine tuning » Optimization
