SceneMotifCoder: Example-driven Visual Program Learning for Generating 3D Object Arrangements

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發表在:arXiv.org (Aug 5, 2024), p. n/a
主要作者: Hou In Ivan Tam
其他作者: Hou In Derek Pun, Wang, Austin T, Chang, Angel X, Savva, Manolis
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Cornell University Library, arXiv.org
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100 1 |a Hou In Ivan Tam 
245 1 |a SceneMotifCoder: Example-driven Visual Program Learning for Generating 3D Object Arrangements 
260 |b Cornell University Library, arXiv.org  |c Aug 5, 2024 
513 |a Working Paper 
520 3 |a Despite advances in text-to-3D generation methods, generation of multi-object arrangements remains challenging. Current methods exhibit failures in generating physically plausible arrangements that respect the provided text description. We present SceneMotifCoder (SMC), an example-driven framework for generating 3D object arrangements through visual program learning. SMC leverages large language models (LLMs) and program synthesis to overcome these challenges by learning visual programs from example arrangements. These programs are generalized into compact, editable meta-programs. When combined with 3D object retrieval and geometry-aware optimization, they can be used to create object arrangements varying in arrangement structure and contained objects. Our experiments show that SMC generates high-quality arrangements using meta-programs learned from few examples. Evaluation results demonstrates that object arrangements generated by SMC better conform to user-specified text descriptions and are more physically plausible when compared with state-of-the-art text-to-3D generation and layout methods. 
653 |a Large language models 
653 |a State-of-the-art reviews 
700 1 |a Hou In Derek Pun 
700 1 |a Wang, Austin T 
700 1 |a Chang, Angel X 
700 1 |a Savva, Manolis 
773 0 |t arXiv.org  |g (Aug 5, 2024), p. n/a 
786 0 |d ProQuest  |t Engineering Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3089689635/abstract/embedded/H09TXR3UUZB2ISDL?source=fedsrch 
856 4 0 |3 Full text outside of ProQuest  |u http://arxiv.org/abs/2408.02211