  We present Progressively Deblurring Radiance Field (PDRF), a novel approach
to efficiently reconstruct high quality radiance fields from blurry images.
While current State-of-The-Art (SoTA) scene reconstruction methods achieve
photo-realistic rendering results from clean source views, their performances
suffer when the source views are affected by blur, which is commonly observed
for images in the wild. Previous deblurring methods either do not account for
3D geometry, or are computationally intense. To addresses these issues, PDRF, a
progressively deblurring scheme in radiance field modeling, accurately models
blur by incorporating 3D scene context. PDRF further uses an efficient
importance sampling scheme, which results in fast scene optimization.
Specifically, PDRF proposes a Coarse Ray Renderer to quickly estimate voxel
density and feature; a Fine Voxel Renderer is then used to achieve high quality
ray tracing. We perform extensive experiments and show that PDRF is 15X faster
than previous SoTA while achieving better performance on both synthetic and
real scenes.
