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UrbanIR
UrbanIR: Large-Scale Urban Scene
UrbanIR: Large-Scale Urban Scene
Inverse Rendering from a Single Video
3DV 2025
- Chih-Hao Lin1
- Bohan Liu1
- Yi-Ting Chen2
- Kuan-Sheng Chen1
- David Forsyth1
- Jia-Bin Huang2
- Anand Bhattad1
- Shenlong Wang1
- 1University of Illinois at Urbana-Champaign
- 2University of Maryland, College Park
Abstract
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.
Relighting: Timelapse Simulation
* By changing sunlight direction explicitly, UrbanIR simulates sharp and geometry-aware shadow.
* Left: input image, Right: Timelapse Simulation