1 citations · 2 across the 5 of their papers we have counts for
5 papers
Revisiting Shape from Polarization in the Era of Vision Foundation Models
Chenhao Li, Taishi Ono, Takeshi Uemori +1
We show that, with polarization cues, a lightweight model trained on a small dataset can outperform RGB-only vision foundation models (VFMs) in single-shot object-level surface nor…
NeISF++: Neural Incident Stokes Field for Polarized Inverse Rendering of Conductors and Dielectrics
Chenhao Li, Taishi Ono, Takeshi Uemori +5
Recent inverse rendering methods have greatly improved shape, material, and illumination reconstruction by utilizing polarization cues. However, existing methods only support diele…
Deep Polarization Cues for Single-shot Shape and Subsurface Scattering Estimation
Chenhao Li, Trung Thanh Ngo, Hajime Nagahara
In this work, we propose a novel learning-based method to jointly estimate the shape and subsurface scattering (SSS) parameters of translucent objects by utilizing polarization cue…
NeISF: Neural Incident Stokes Field for Geometry and Material Estimation
Chenhao Li, Taishi Ono, Takeshi Uemori +4
Multi-view inverse rendering is the problem of estimating the scene parameters such as shapes, materials, or illuminations from a sequence of images captured under different viewpo…
Inverse Rendering of Translucent Objects using Physical and Neural Renderers
Chenhao Li, Trung Thanh Ngo, Hajime Nagahara
In this work, we propose an inverse rendering model that estimates 3D shape, spatially-varying reflectance, homogeneous subsurface scattering parameters, and an environment illumin…