no code implementations • 25 Mar 2024 • Yiming Xie, Henglu Wei, Zhenyi Liu, Xiaoyu Wang, Xiangyang Ji
To advance research in learning-based defogging algorithms, various synthetic fog datasets have been developed.
no code implementations • 14 Dec 2023 • Haiyang Tang, Zhenyi Liu, Dongping Chen, Qingzhao Chu
We employed prompt engineering to incorporate external knowledge databases, thus enriching the LLM with up-to-date and reliable information.
no code implementations • 2 Mar 2023 • Zhenyi Liu, Devesh Shah, Alireza Rahimpour, Devesh Upadhyay, Joyce Farrell, Brian A Wandell
The simulation can be used to characterize system performance or to test its performance under conditions that are difficult to measure (e. g., nighttime for automotive perception systems).
no code implementations • 6 Jan 2021 • Zhenyi Liu, Joyce Farrell, Brian Wandell
(1) When the spatial sampling resolution of the depth map and radiance image are equal to typical camera resolutions, a ResNet detects vehicles at higher average precision from depth than radiance.
no code implementations • 30 Nov 2020 • Xiaochen Zhao, Zerong Zheng, Chaonan Ji, Zhenyi Liu, Siyou Lin, Tao Yu, Jinli Suo, Yebin Liu
We introduce VERTEX, an effective solution to recover 3D shape and intrinsic texture of vehicles from uncalibrated monocular input in real-world street environments.
no code implementations • 8 Dec 2019 • Zhenyi Liu, Trisha Lian, Joyce Farrell, Brian Wandell
We quantify the generalization of a convolutional neural network (CNN) trained to identify cars.
1 code implementation • 24 Oct 2019 • Zhenyi Liu, Trisha Lian, Joyce Farrell, Brian Wandell
It is better to evaluate camera designs for CNN applications using soft prototyping with task-specific metrics rather than consumer photography metrics.
no code implementations • 12 Feb 2019 • Zhenyi Liu, Minghao Shen, Jia-Qi Zhang, Shuangting Liu, Henryk Blasinski, Trisha Lian, Brian Wandell
We describe an open-source simulator that creates sensor irradiance and sensor images of typical automotive scenes in urban settings.