2021
DIB-R++: Learning to Predict Lighting and Material with a Hybrid Differentiable Renderer
NeurIPS 2021poster
We consider the challenging problem of predicting intrinsic object properties from a single image by exploiting differentiable renderers. Many previous learning-based approaches for inverse graphics adopt rasterization-based renderers and assume naive lighting and material models, which often fail t…