110 citations · 435 across the 31 of their papers we have counts for
6 papers · 1 filter
Automatic Scene Inference for 3D Object Compositing
Kevin Karsch, Kalyan Sunkavalli, Sunil Hadap +4
We present a user-friendly image editing system that supports a drag-and-drop object insertion (where the user merely drags objects into the image, and the system automatically pla…
Basis Prediction Networks for Effective Burst Denoising with Large Kernels
Zhihao Xia, Federico Perazzi, Michaël Gharbi +2
Bursts of images exhibit significant self-similarity across both time and space. This motivates a representation of the kernels as linear combinations of a small set of basis eleme…
Deep Parametric Indoor Lighting Estimation
Marc-André Gardner, Yannick Hold-Geoffroy, Kalyan Sunkavalli +2
We present a method to estimate lighting from a single image of an indoor scene. Previous work has used an environment map representation that does not account for the localized na…
All-Weather Deep Outdoor Lighting Estimation
Jinsong Zhang, Kalyan Sunkavalli, Yannick Hold-Geoffroy +3
We present a neural network that predicts HDR outdoor illumination from a single LDR image. At the heart of our work is a method to accurately learn HDR lighting from LDR panoramas…
Fast Spatially-Varying Indoor Lighting Estimation
Mathieu Garon, Kalyan Sunkavalli, Sunil Hadap +2
We propose a real-time method to estimate spatiallyvarying indoor lighting from a single RGB image. Given an image and a 2D location in that image, our CNN estimates a 5th order sp…
Inverse Rendering for Complex Indoor Scenes: Shape, Spatially-Varying Lighting and SVBRDF from a Single Image
Zhengqin Li, Mohammad Shafiei, Ravi Ramamoorthi +2
We propose a deep inverse rendering framework for indoor scenes. From a single RGB image of an arbitrary indoor scene, we create a complete scene reconstruction, estimating shape,…