Mixed-Density Diffuser achieves new state-of-the-art results on D4RL benchmarks by allowing non-uniform temporal resolution in diffusion planning.
Denoising diffusion probabilistic models
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A feed-forward video latent transformer that predicts time-varying 3D Gaussian primitives from one image to produce controllable 4D scenes with appearance, geometry, and motion.
R3D2 trains a lightweight diffusion model on synthetic placements of 3DGS-generated assets to produce photorealistic insertions with consistent illumination into autonomous driving scenes.
A conditional diffusion model trained on partitioned incomplete samples for physical dynamics achieves asymptotic convergence to the true generative process under mild conditions and outperforms baselines in imputation.
citing papers explorer
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Mixed-Density Diffuser: Efficient Planning with Non-Uniform Temporal Resolution
Mixed-Density Diffuser achieves new state-of-the-art results on D4RL benchmarks by allowing non-uniform temporal resolution in diffusion planning.
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Diff4Splat: Controllable 4D Scene Generation with Latent Dynamic Reconstruction Models
A feed-forward video latent transformer that predicts time-varying 3D Gaussian primitives from one image to produce controllable 4D scenes with appearance, geometry, and motion.
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R3D2: Realistic 3D Asset Insertion via Diffusion for Autonomous Driving Simulation
R3D2 trains a lightweight diffusion model on synthetic placements of 3DGS-generated assets to produce photorealistic insertions with consistent illumination into autonomous driving scenes.
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Incomplete Data, Complete Dynamics: A Diffusion Approach
A conditional diffusion model trained on partitioned incomplete samples for physical dynamics achieves asymptotic convergence to the true generative process under mild conditions and outperforms baselines in imputation.