SceneOrchestra trains an orchestrator to generate full tool-call trajectories for 3D scene synthesis and uses a discriminator during training to select high-quality plans, yielding state-of-the-art results with lower runtime.
In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition
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Procedural rules with NURBS generate MVS training data that outperforms same-scale manual curation and matches or exceeds larger manual datasets.
citing papers explorer
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SceneOrchestra: Efficient Agentic 3D Scene Synthesis via Full Tool-Call Trajectory Generation
SceneOrchestra trains an orchestrator to generate full tool-call trajectories for 3D scene synthesis and uses a discriminator during training to select high-quality plans, yielding state-of-the-art results with lower runtime.
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SimpleProc: Fully Procedural Synthetic Data from Simple Rules for Multi-View Stereo
Procedural rules with NURBS generate MVS training data that outperforms same-scale manual curation and matches or exceeds larger manual datasets.