activity
20152020
most citedDepthTransfer: Depth Extraction from Video Using Non-parametric Sampling

501 citations · 888 across the 12 of their papers we have counts for

collaborators

14 papers

cs.CV2020274 cited

Depth Extraction from Video Using Non-parametric Sampling

Kevin Karsch, Ce Liu, Sing Bing Kang

We describe a technique that automatically generates plausible depth maps from videos using non-parametric depth sampling. We demonstrate our technique in cases where past methods…

cs.CV20191 cited

Inverse Rendering Techniques for Physically Grounded Image Editing

Kevin Karsch

From a single picture of a scene, people can typically grasp the spatial layout immediately and even make good guesses at materials properties and where light is coming from to ill…

cs.GR20192 cited

Lightform: Procedural Effects for Projected AR

Brittany Factura, Laura LaPerche, Phil Reyneri +2

Projected augmented reality, also called projection mapping or video mapping, is a form of augmented reality that uses projected light to directly augment 3D surfaces, as opposed t…

cs.GR2019

Blind Recovery of Spatially Varying Reflectance from a Single Image

Kevin Karsch, David Forsyth

We propose a new technique for estimating spatially varying parametric materials from a single image of an object with unknown shape in unknown illumination. Our method uses a low-…

cs.CV2019501 cited

DepthTransfer: Depth Extraction from Video Using Non-parametric Sampling

Kevin Karsch, Ce Liu, Sing Bing Kang

We describe a technique that automatically generates plausible depth maps from videos using non-parametric depth sampling. We demonstrate our technique in cases where past methods…

cs.GR2019

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…