5 papers · 1 filter
PureLight: Learning Complex Luminaires with Light Tracing
Pedro Figueiredo, Zixuan Li, Beibei Wang +2
We propose a neural formulation for estimating the appearance of complex luminaires. We focus on challenging luminaires with complex light transport (e.g., small emitters enclosed…
F-RNG: Feed-Forward Relightable Neural Gaussians
Guangming Fu, Jiahui Fan, Jian Yang +2
Capturing relightable 3D assets from real-world objects is a widely researched problem. Several per-scene optimization-based methods, based on 3D Gaussian splatting (3DGS), support…
8DNA: 8D Neural Asset Light Transport by Distribution Learning
Liwen Wu, Haolin Lu, Bing Xu +2
High-fidelity 3D assets exhibit intriguing global illumination effects like subsurface scattering, glossy interreflections, and fine-scale fiber scatterings, which often involve lo…
PureSample: Neural Materials Learned by Sampling Microgeometry
Zixuan Li, Zixiong Wang, Jian Yang +2
Traditional physically-based material models rely on analytically derived bidirectional reflectance distribution functions (BRDFs), typically by considering statistics of micro-pri…
Fiber-level Woven Fabric Capture from a Single Photo
Zixuan Li, Pengfei Shen, Hanxiao Sun +7
Accurately rendering the appearance of fabrics is challenging, due to their complex 3D microstructures and specialized optical properties. If we model the geometry and optics of fa…