33 citations · 46 across the 3 of their papers we have counts for
3 papers
cs.CV2024★ 4 cited
Neural Product Importance Sampling via Warp Composition
Joey Litalien, Miloš Hašan, Fujun Luan +2
Achieving high efficiency in modern photorealistic rendering hinges on using Monte Carlo sampling distributions that closely approximate the illumination integral estimated for eve…
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★ 33 cited
Neural Geometric Level of Detail: Real-time Rendering with Implicit 3D Shapes
Towaki Takikawa, Joey Litalien, Kangxue Yin +6
Neural signed distance functions (SDFs) are emerging as an effective representation for 3D shapes. State-of-the-art methods typically encode the SDF with a large, fixed-size neural…