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.
Advances in Neural Information Processing Systems36, 18225–18250 (2023)
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SynCity 3000 generates large, coherent 3D scenes from text by fine-tuning an image-to-3D diffusion model to operate convolutionally on overlapping windows, trained on procedurally generated synthetic scene data.
A training-free method with time-dependent attention gating and trajectory pruning enhances object-background balance in diffusion-based image synthesis.
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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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SynCity 3000: Bootstrapping Scene-Scale 3D Diffusion
SynCity 3000 generates large, coherent 3D scenes from text by fine-tuning an image-to-3D diffusion model to operate convolutionally on overlapping windows, trained on procedurally generated synthetic scene data.
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Training-Free Object-Background Compositional T2I via Dynamic Spatial Guidance and Multi-Path Pruning
A training-free method with time-dependent attention gating and trajectory pruning enhances object-background balance in diffusion-based image synthesis.