Kevin W. Zhang
is currently
Intern at Adobe Research, SF
working with Aaron Hertzmann, Jose Echevarria, Stephen DiVerdi,
3rd Year CS PhD Student at University of Maryland, College Park,
working with Christopher Metzler, Jia-Bin Huang,
who applies computer vision and computer graphics techniques to computational imaging/sensing research,
BA in Computer Science and Pure Mathematics (Double Major) at University of California, Berkeley,
collaborated with Michael Kellman, Jon Tamir, Laura Waller, Michael Lustig.
CV, as of 2024-05-03.
Publications (* indicates equal contribution)
A Scalable Training Strategy for Blind Multi-Distribution Noise Removal
Kevin Zhang, Sakshum Kulshrestha, Christopher Metzler
IEEE TIP 2024
[Paper]
[Paper]
Z-Splat: Z-Axis Gaussian Splatting for Camera-Sonar Fusion
Ziyuan Qu, Omkar Vengurlekar, Mohamad Qadri, Kevin Zhang, Michael Kaess, Christopher Metzler, Suren Jayasuriya, Adithya Pediredla
IEEE Transactions on Pattern Analysis and Machine Intelligence (Special Issue of ICCP) 2024
[Paper]
[Paper]
Temporally Consistent Atmospheric Turbulence Mitigation with Neural Representations
Haoming Cai*, Jingxi Chen*, Brandon Y. Feng, Weiyun Jiang, Mingyang Xie, Kevin Zhang, Cornelia Fermuller, Yiannis Aloimonos, Ashok Veeraraghavan, Christopher Metzler
NeurIPS 2024
[Paper] [Website]
[Paper] [Website]
AONeuS: A Neural Rendering Framework for Acoustic-Optical Sensor Fusion
Mohamad Qadri*, Kevin Zhang*, Akshay Hinduja, Michael Kaess, Adithya Pediredla, Christopher Metzler
SIGGRAPH 2024 (conference track full paper)
[Paper] [Website]
[Paper] [Website]
Seeing the World through Your Eyes
Hadi AlZayer*, Kevin Zhang*, Brandon Feng, Christopher Metzler, Jia-bin Huang
CVPR 2024 (Oral, 3.3% of accepted papers)
[Paper] [Website] [Press] [Twitter]
[Paper] [Website] [Press] [Twitter]
PAniC-3D: Stylized Single-view 3D Reconstruction from Portraits of Anime Characters
Shuhong Chen, Kevin Zhang, Yichun Shi, Heng Wang, Yiheng Zhu, Guoxian Song, Sizhe An, Janus Þór Kristjánsson, Xiao Yang, Matthias Zwicker
CVPR 2023
[Paper] [Code]
[Paper] [Code]
MetaDIP: Accelerating Deep Image Prior with Meta Learning
Kevin Zhang, Mingyang Xie, Maharshi Gor, Yi-Ting Chen, Yvonne Zhou, Christopher Metzler
arXiv, 2022
[Paper]
[Paper]
Memory-efficient Learning for High-Dimensional MRI Reconstruction
Ke Wang, Christopher Sandino, Michael Kellman, Kevin Zhang, Shreyas Vasanawala, Jonathan I. Tamir, Stella Yu, Michael Lustig
MICCAI 2021
[Paper] [Code]
[Paper] [Code]
Memory-efficient Learning for Large-scale Computational Imaging
Michael Kellman, Kevin Zhang, Eric Markley, Jonathan I. Tamir, Emrah Bostan, Michael Lustig, Laura Waller
IEEE TCI 2020
[Paper] [Code]
[Paper] [Code]
Memory-Efficient Learning for Unrolled 3D MRI Reconstructions
Kevin Zhang*, Michael Kellman*, Jonathan I. Tamir, Michael Lustig, Laura Waller
ISMRM Workshop on Data Sampling and Reconstruction, 2020
[Paper] [Video]
[Paper] [Video]
3D fluorescence deconvolution with deep priors
Kevin Zhang, Michael Kellman, Emrah Bostan, Laura Waller
SPIE BiOS 2020
[Paper]
[Paper]
Side Projects
I also enjoy building small web apps to visualize algorithmic ideas. The source code for these projects is on my Github.
Site design inspired by Haozhi Qi orderedlist.