activity
20162023
most citedLearning the image processing pipeline

62 citations · 74 across the 8 of their papers we have counts for

collaborators

9 papers

cs.CV2023

Using simulation to quantify the performance of automotive perception systems

Zhenyi Liu, Devesh Shah, Alireza Rahimpour +3

The design and evaluation of complex systems can benefit from a software simulation - sometimes called a digital twin. The simulation can be used to characterize system performance…

eess.IV2022

Ray-transfer functions for camera simulation of 3D scenes with hidden lens design

Thomas Goossens, Zheng Lyu, Jamyuen Ko +3

Combining image sensor simulation tools (e.g., ISETCam) with physically based ray tracing (e.g., PBRT) offers possibilities for designing and evaluating novel imaging systems as we…

eess.IV2022★ 4 cited

Accurate smartphone camera simulation using 3D scenes

Zheng Lyu, Thomas Goossens, Brian Wandell +1

We assess the accuracy of a smartphone camera simulation. The simulation is an end-to-end analysis that begins with a physical description of a high dynamic range 3D scene and incl…

eess.IV2021

Validation of image systems simulation technology using a Cornell Box

Zheng Lyu, Krithin Kripakaran, Max Furth +3

We describe and experimentally validate an end-to-end simulation of a digital camera. The simulation models the spectral radiance of 3D-scenes, formation of the spectral irradiance…

cs.CV2021★ 1 cited

ISETAuto: Detecting vehicles with depth and radiance information

Zhenyi Liu, Joyce Farrell, Brian Wandell

Autonomous driving applications use two types of sensor systems to identify vehicles - depth sensing LiDAR and radiance sensing cameras. We compare the performance (average precisi…

cs.CV2019★ 4 cited

Neural Network Generalization: The impact of camera parameters

Zhenyi Liu, Trisha Lian, Joyce Farrell +1

We quantify the generalization of a convolutional neural network (CNN) trained to identify cars. First, we perform a series of experiments to train the network using one image data…