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UrbanIR: Large-Scale Urban Scene Inverse Rendering from a Single Video

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arxiv 2306.09349 v4 pith:NLAPT6BL submitted 2023-06-15 cs.CV

classification cs.CV
keywords inverserenderingsceneurbanirfree-viewpointgraphicsmethodsmodel
verification ladder T0 review T1 audit T2 compute T3 formal
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We present UrbanIR (Urban Scene Inverse Rendering), a new inverse graphics model that enables realistic, free-viewpoint renderings of scenes under various lighting conditions with a single video. It accurately infers shape, albedo, visibility, and sun and sky illumination from wide-baseline videos, such as those from car-mounted cameras, differing from NeRF's dense view settings. In this context, standard methods often yield subpar geometry and material estimates, such as inaccurate roof representations and numerous 'floaters'. UrbanIR addresses these issues with novel losses that reduce errors in inverse graphics inference and rendering artifacts. Its techniques allow for precise shadow volume estimation in the original scene. The model's outputs support controllable editing, enabling photorealistic free-viewpoint renderings of night simulations, relit scenes, and inserted objects, marking a significant improvement over existing state-of-the-art methods.

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Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. InvRGB+L: Inverse Rendering of Complex Scenes with Unified Color and LiDAR Reflectance Modeling

    cs.CV 2025-07 conditional novelty 6.0 of 10

    InvRGB+L jointly estimates visible and LiDAR albedo with a physics-based specular LiDAR model and cross-modal consistency losses, improving inverse rendering and LiDAR intensity simulation for urban and indoor scenes.

  2. DiffusionRenderer: Neural Inverse and Forward Rendering with Video Diffusion Models

    cs.CV 2025-01 conditional novelty 6.0 of 10

    A single video diffusion system both estimates scene properties from video and renders photorealistic images from those properties, enabling relighting, material editing, and object insertion.

  3. UrbanCAD: Towards Highly Controllable and Photorealistic 3D Vehicles for Urban Scene Simulation

    cs.CV 2024-11 conditional novelty 6.0 of 10

    UrbanCAD retrieves a matching CAD model from a single car image, optimizes its materials, and inserts it into reconstructed urban scenes, showing that perception models degrade when the cars are edited into out-of-dis...

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