activity
20152023
most citedNO Need to Worry about Adversarial Examples in Object Detection in Autonomous Vehicles

209 citations · 394 across the 12 of their papers we have counts for

collaborators
Showing 2019Show all

9 papers · 1 filter

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.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…

cs.GR2019★ 12 cited

ConstructAide: Analyzing and Visualizing Construction Sites through Photographs and Building Models

Kevin Karsch, Mani Golparvar-Fard, David Forsyth

We describe a set of tools for analyzing, visualizing, and assessing architectural/construction progress with unordered photo collections and 3D building models. With our interface…

cs.GR2019

Rendering Synthetic Objects into Legacy Photographs

Kevin Karsch, Varsha Hedau, David Forsyth +1

We propose a method to realistically insert synthetic objects into existing photographs without requiring access to the scene or any additional scene measurements. With a single im…

cs.CV2019

Effectively Unbiased FID and Inception Score and where to find them

Min Jin Chong, David Forsyth

This paper shows that two commonly used evaluation metrics for generative models, the Fréchet Inception Distance (FID) and the Inception Score (IS), are biased -- the expected valu…

cs.CV2019

Improving Style Transfer with Calibrated Metrics

Mao-Chuang Yeh, Shuai Tang, Anand Bhattad +2

Style transfer methods produce a transferred image which is a rendering of a content image in the manner of a style image. We seek to understand how to improve style transfer. To d…