Leheng Li ζδΉζ
Bio: I am a second-year Ph.D. student at The Hong Kong University of Science and Technology (Guangzhou), supervised by Prof. Ying-Cong Chen. My research interests are computer vision and autonomous driving. I received B.Sc in Mathematics from Dalian University of Technology in 2022. Previously, I was fortunate to have interned at MEGVII Technology and NIO.
Publications
Adv3D: Generating 3D Adversarial Examples in Driving Scenarios with NeRF
Leheng Li, Qing Lian, Ying-Cong Chen
arxiv preprint, 2023
We present the first exploration of modeling adversarial examples as NeRFs. Our examples demonstrate satisfactory transferability and physical realizability in driving scenarios.
Paper / Code / Project Page /
Leheng Li, Qing Lian, Ying-Cong Chen
arxiv preprint, 2023
We present the first exploration of modeling adversarial examples as NeRFs. Our examples demonstrate satisfactory transferability and physical realizability in driving scenarios.
Paper / Code / Project Page /
@article{li2023adv3d,
title={Adv3D: Generating 3D Adversarial Examples in Driving Scenarios with NeRF},
author={Li, Leheng and Lian, Qing and Chen, Ying-Cong},
journal={arXiv preprint arXiv:2309.01351},
year={2023}
}
Lift3D: Synthesize 3D Training Data
by Lifting 2D GAN to 3D Generative Radiance Field
Leheng Li, Qing Lian, Luozhou Wang, Ningning Ma, Ying-Cong Chen
Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2023
The first work to use NeRF-generated datasets to benefit downstream tasks. The datasets enjoy both photorealistic synthesis and 3D-control property, improving 3D detection performance in a Real2Sim2Real manner without domain adaptation.
Paper / Code / Project Page /
Leheng Li, Qing Lian, Luozhou Wang, Ningning Ma, Ying-Cong Chen
Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2023
The first work to use NeRF-generated datasets to benefit downstream tasks. The datasets enjoy both photorealistic synthesis and 3D-control property, improving 3D detection performance in a Real2Sim2Real manner without domain adaptation.
Paper / Code / Project Page /
@InProceedings{lift3D2023CVPR,
author = {Leheng Li and Qing Lian and Luozhou Wang and Ningning Ma and Ying-Cong Chen},
title = {Lift3D: Synthesize 3D Training Data by Lifting 2D GAN to 3D Generative Radiance Field},
booktitle = {Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR)},
year = {2023},
}Homepage Template
I really appreciate Michael Niemeyer for providing the source code of the website template.