187 citations · 197 across the 3 of their papers we have counts for
3 papers
cs.CV2022★ 187 cited
GET3D: A Generative Model of High Quality 3D Textured Shapes Learned from Images
Jun Gao, Tianchang Shen, Zian Wang +6
As several industries are moving towards modeling massive 3D virtual worlds, the need for content creation tools that can scale in terms of the quantity, quality, and diversity of…
cs.CV2021★ 9 cited
DIB-R++: Learning to Predict Lighting and Material with a Hybrid Differentiable Renderer
Wenzheng Chen, Joey Litalien, Jun Gao +5
We consider the challenging problem of predicting intrinsic object properties from a single image by exploiting differentiable renderers. Many previous learning-based approaches fo…
cs.CV2021★ 1 cited
Learning Indoor Inverse Rendering with 3D Spatially-Varying Lighting
Zian Wang, Jonah Philion, Sanja Fidler +1
In this work, we address the problem of jointly estimating albedo, normals, depth and 3D spatially-varying lighting from a single image. Most existing methods formulate the task as…