Peng Wang

Peng Wang 王朋

I am currently a second-year Ph.D. student at the School of Engineering in the Westlake University, in collaboration with Zhejiang University. My PhD advisor is Prof. Peidong Liu. Before that, I received my Bachelor and Master Degree from Huazhong University of Science and Technology respectively in 2019 and 2022.

I'm interested in 3D vision (e.g. Neural Rendering) and Generative Models.

Publications

Representative papers are highlighted, * denotes equal contribution.

	BAD-Gaussians: Bundle Adjusted Deblur Gaussian Splatting Lingzhe Zhao, Peng Wang, Peidong Liu arXiv, 2024 project page / arXiv / code BAD-Gaussians successfully deblurs severe motion-blurred images, synthesizes higher-quality novel views, and achieves real-time rendering, surpassing previous SOTA implicit deblurring rendering methods.
	USB-NeRF: Unrolling Shutter Bundle Adjusted Neural Radiance Fields Moyang Li, Peng Wang, Lingzhe Zhao, Bangyan Liao, Peidong Liu ICLR, 2024 project page / arXiv / code USB-NeRF can remove rolling shutter effect and recover high-fidelity high frame-rate global shutter video from a sequence of rolling shutter images.
	BAD-NeRF: Bundle Adjusted Deblur Neural Radiance Fields Peng Wang, Lingzhe Zhao, Ruijie Ma, Peidong Liu CVPR, 2023 project page / arXiv / code BAD-NeRF jointly learns the 3D representation and optimizes the camera motion trajectories within exposure time from blurry images and inaccurate initial poses. Nov. 2023 update: we have released the NeRFstudio version BAD-NeRFstudio.
	SCL-VI: Self-supervised Context Learning for Visual Inspection of Industrial Defects Peng Wang, Haiming Yao, Wenyong Yu arXiv, 2023 arXiv / code We address the challenge of detecting object defects through the self-supervised learning approach of solving the jigsaw puzzle problem.