Assistant Research Professor
Johns Hopkins University
Data Science and AI (DSAI)
2024 - 2026
Embedded Files
IJCV Special Issue
IJCV Special Issue
I am serving as the Guest Editor for a special issue in IJCV on Unconstrained 3D Reconstruction and Rendering! You can find more details of the special issue here. Kindly consider submitting your latest and greatest work here.
Recent Activities
Recent Activities
[2025/10/19] One IEEE JSTSP (IF: 13.7) paper (FusionRF) was accepted, congrats to Michael!
[2025/9/18] One NIPS paper (MS-GS) was accepted, congrats to Deming!
[2025/6/12] Two CVPR papers (SPARS3R, Geometry Splatting) were accepted, congrats to Yutao, Yuxiang, and Kaiwen!
[2025/6/12] Glad to have been selected as CVPR 2025's Outstanding Reviewer!
[2025/4/24] One ICLR paper (Genex) was accepted, congrats to Taiming!
[2025/3/10] Glad to receive the NVIDIA Academic Grant Program Award; thankful for the support from Ming-Yu Liu and Yogesh Balaji. The proposal was written in collaboration with Jieneng Chen and Prof. Alan Yuille.
[2025/2/28] Organized a WACV workshop on Unconstrained Large-scale Three-dimensional Reconstruction and Rendering across Altitutdes (ULTRRA), thankful for Ashwini Deshpande, Zexiang Xu, Noah Snavely, Deva Ramanan, and Yohann Cabon as guest speakers!
[2025/2/28] Two WACV papers (GaitContour, VILLS) were accepetd, congrats to Yuxiang and Siyuan!
[2024/12/16] One NIPS paper (LP-3DGS) was accepted, congrats to Zhaoliang!
[2024/9/29] One ECCV paper (BAGS) was accepted, congrats to myself and Yutao!
[2024/9/15] One IJCB paper (GADER) was accepted with the Best Biometrics Student Paper Award, congrats to Yuxiang!
[2024/7/1] Joined Johns Hopkins University as an Assistant Research Professor :)
Biography
Biography
I am an Assistant Research Professor at Johns Hopkins University, affiliated with the Mathematical Institute for Data Science (MINDS, now under DSAI). I obtained my BS/MS in Electrical Engineering from the University of Maryland, College Park, did some start-up venture for a couple of years, came back and got my PhD at Johns Hopkins with Prof. Rama Chellappa.
I am broadly interested in Computer Vision and its various applications, particularly in 3D/4D. My past work focuses on high quality, high resolution 3D reconstruction from signals in the visible spectrum (Neural Radiance Field, 3D Gaussian Splatting, etc.) and the invisible spectrum (CT, MRI, etc.). I have also done some work on image analysis, e.g. segmentation, detection, re-ID, etc., for human identification and on medical images.
I enjoy a good combination of novel scientific progress and grounded, practical engineering. I also spend a lot of thoughts on how vision algorithms can be implemented and productively applied in the real world.
Service on Workshop/Tutorial/Special Issue
Service on Workshop/Tutorial/Special Issue
For those interested, I am serving as the Guest Editor for a special issue in IJCV on Unconstrained 3D Reconstruction and Rendering. You can find more details of the special issue here. I have organized a workshop on natural image 3D reconstruction in WACV 2025, and a tutorial on 2D-3D modelling in medical imaging in MICCAI 2021.
Current Advising Students
Current Advising Students
Yuxiang Guo
(JHU ECE PhD)
Deming Li
(JHU ECE PhD)
Yutao Tang
(JHU BME PhD)
Zhaoliang Zhang
(JHU ECE PhD)
Siyuan Huang
(JHU ECE PhD)
Zhimin Zhao
(JHU ECE PhD)
Ongoing/past Collaborations
Ongoing/past Collaborations
I am fortunately supported by various agencies and collaborators, particularly by IARPA and ONR MURI.
I am the project manager and a co-PI in WRIVA, a multi-institute IARPA effort focused on robust, image-only 3D site modeling. I am grateful for the opportunity to work with world class researchers like Ravi (UCSD), Hao (UCSD), Manjunath (UCSD), Shiv (UCSB), Matthias (UMD), Abhinav (UMD), Tom (UMD), Ashok (Rice), Guha (Rice), Vishal (JHU), Deliang (ASU), and their amazing students.
I am one of the main research scientists in BRIAR, another large scale IARPA effort at solving long-distance biometric/human identification, working with Vishal (JHU) and STR.
I am also thankful to collaborations with Kevin Zhou (USTC), Daguang Xu (NVIDIA), and Dong Yang (NVIDIA) in the medical imaging domain, particularly during my PhD.
At JHU, I have collaborated with Jieneng Chen and Alan Yuille on Generative World Model, and with Pengfei Guo (now at NVIDIA) on generative MR reconstruction.
Taiming Lu, Tianmin Shu, Junfei Xiao, Luoxin Ye, Jiahao Wang, Cheng Peng, Chen Wei, Daniel Khashabi, Rama Chellappa, Alan L. Yuille, and Jieneng Chen
ICLR 2025
Geometry Field Splatting with Gaussian Surfels
Geometry Field Splatting with Gaussian Surfels
Kaiwen Jiang, Venkataram Sivaram, Cheng Peng, Ravi Ramamoorthi
CVPR 2025
SPARS3R: Semantic Prior Alignment and Regularization for Sparse 3D Reconstruction
SPARS3R: Semantic Prior Alignment and Regularization for Sparse 3D Reconstruction
Yutao Tang* , Yuxiang Guo* , Deming Li , Cheng Peng
CVPR 2025
An Immersive Multi-Elevation Multi-Seasonal Dataset for 3D Reconstruction and Visualization
An Immersive Multi-Elevation Multi-Seasonal Dataset for 3D Reconstruction and Visualization
Xijun Liu, Yifan Zhou, Yuxiang Guo, Rama Chellappa, Cheng Peng
WACV2025 ULTRRA Workshop
Unconstrained Large-scale 3D Reconstruction and Rendering across Altitudes
Unconstrained Large-scale 3D Reconstruction and Rendering across Altitudes
Neil Joshi, Joshua Carney, Nathanael Kuo, Homer Li, Cheng Peng, Myron Brown
WACV2025 ULTRRA Workshop
GaitContour: Efficient Gait Recognition based on a Contour-Pose Representation
GaitContour: Efficient Gait Recognition based on a Contour-Pose Representation
Yuxiang Guo, Anshul Shah, Jiang Liu, Ayush Gupta, Rama Chellappa, Cheng Peng
WACV 2025
VILLS: Video-Image Learning to Learn Semantics for Person Re-Identification
VILLS: Video-Image Learning to Learn Semantics for Person Re-Identification
Siyuan Huang, Ram Prabhakar, Yuxiang Guo, Rama Chellappa, Cheng Peng
WACV 2025
LP-3DGS: Learning to Prune 3D Gaussian Splatting
LP-3DGS: Learning to Prune 3D Gaussian Splatting
Zhaoliang Zhang, Tianchen Song, Yongjae Lee, Li Yang, Cheng Peng, Rama Chellappa, Deliang Fan
NIPS 2024
Cheng Peng*, Yutao Tang*, Yifan Zhou, Nengyu Wang, Xijun Liu, Deming Li, Rama Chellappa
ECCV 2024
Cheng Peng, Rama Chellappa
AAAI 2023
Cheng Peng, Pengfei Guo, S. Kevin Zhou, Vishal Patel, Rama Chellappa
MICCAI 2022 (Oral)
Cheng Peng*, Haofu Liao*, Gina Wong, Jiebo Luo, S. Kevin Zhou, Rama Chellappa
AAAI 2021
Cheng Peng, S. Kevin Zhou, Rama Chellappa
MICCAI 2021
Cheng Peng, Wei-An Lin, Haofu Liao, Rama Chellappa, Shaohua Kevin Zhou
CVPR 2020
Recruitment
Recruitment
I will be joining the University of Virginia in Spring 2026 as an Assistant Professor at the School of Data Science. I am actively recruiting perspective DS students (PhD/Master/Bachelor) for Fall 2026.
If you are already at JHU/UVA, a Spring 2026 start date may be possible.
I mainly work in the Computer Vision and Computational Imaging domain, with many applications in e.g., site construction, robotic surgery, medical imaging, sports, etc. A few specific topics I am working on: 3D/4D Reconstruction, Novel View Synthesis, Generative Modeling. Refer to here, or to the PhD students I am currently working with if you want to know more about working with me.
If you find these topics interesting and would like to join my group, please fill out the form here. The School of Data Science strongly encourages and facilitates cross-disciplinary research; as such, applications from other departments (e.g., CS/ECE/BME) are also possible.
Some fun visual reconstructions from the Hopkins campus:
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