Yifan Jiang

Yifan Jiang

Ph.D student at University of Texas at Austin
Email: yifanjiang97 At utexas Dot edu

Hi, I am Yifan Jiang (江亦凡), a fourth-year Ph.D student at University of Texas at Austin, VITA Group, supervised by Prof. Zhangyang (Atlas) Wang. Before that I spent one year at Texas A&M University. I received my bachelor's degree from Huazhong University of Science and Technology, Wuhan, China. I've interned at Adobe (Marc Levoy's team), Google Research (GCam), Adobe (Applied Research Team), and Bytedance AI Lab (US CV Lab).

The central goal of my research is to build intelligent machines that are capable of recreating our visual world. I strive to achieve this by establishing a connection between the visual contents from physical world and from virtual scenes. My research helps people better restore our visual world in the digital format and render artistic effects more easily. Especially, I study three main topics:

  • Generative Model: Generative Adversarial Networks, Diffusion Model, Variational Autoencoder
  • Neural Rendering: Differentiable Rendering, Image-based Rendering, Neural Radiance Fields
  • Computational Phtography: Novel-view Synthesis, Inverse Problem, 2D/3D Editing and Manipulation

News: I'm a recipient of Apple Scholars in AI/ML PhD fellowship 2023.

( show selected / show all by date / show all by topic )

Topics: Generative Model / Neural Rendering / Computational Photography / Others / (*: indicates equal contribution.)

Vidit Goel*, Elia Peruzzo*, Yifan Jiang, Dejia Xu, Nicu Sebe, Trevor Darrell, Zhangyang Wang, Humphrey Shi
[Paper] [Code]
Yifan Jiang, Peter Hedman, Ben Mildenhall, Dejia Xu, Jonathan T. Barron, Zhangyang Wang, Tianfan Xue
[Paper] [Project Page]
Dejia Xu*, Peihao Wang*, Yifan Jiang, Zhiwen Fan, Zhangyang Wang
[Paper] [Project Page] [Code]
Dejia Xu, Hayk Poghosyan, Shant Navasardyan, Yifan Jiang, Humphrey Shi, Zhangyang Wang
[Paper] [Code]
Qiucheng Wu*, Yifan Jiang*, Junru Wu*, Kai Wang, Gong Zhang, Huphery Shi, Zhangyang Wang, Shiyu Chang
[Paper] [Project Page] [Code]
Yifan Jiang*, Zhiwen Fan*, Peihao Wang*, Xinyu Gong, Dejia Xu, Zhangyang Wang
[Paper] [Project Page] [Code]
Yifan Jiang*, Dejia Xu*, Peihao Wang, Zhiwen Fan, Humphery Shi, Zhangyang Wang
[Paper] [Project Page] [Code]
Mengshu Sun, Haoyu Ma, Guoliang Kang, Yifan Jiang, Tianlong Chen, Xiaolong Ma, Zhangyang Wang, Yanzhi Wang
Yifan Jiang, Bartlomiej Wronski, Ben Mildenhall, Jonathan T. Barron, Zhangyang Wang, Tianfan Xue
[Paper] [Project]
Yifan Jiang*, Xinyu Gong*, Junru Wu, Humphery Shi, Zhicheng Yan, Zhangyang Wang
Bowen Pan, Rameswar Panda, Yifan Jiang, Zhangyang Wang, Rogerio Feris, Aude Oliva
Yifan Jiang, He Zhang, Jianming Zhang, Yilin Wang, Zhe Lin, Kalyan Sunkavalli, Simon Chen, Sohrab Amirghodsi, Sarah Kong, Zhangyang Wang
[Paper] [Code]
Yonggan Fu, Zhongzhi Yu, Yongan Zhang, Yifan Jiang, Chaojian Li, Yongyuan Liang, Mingchao Jiang, Zhangyang Wang, Yingyan Lin
[Paper] [Code]
Tianjian Meng*, Xiaohan Chen*, Yifan Jiang, Zhangyang Wang
[Paper] [Code]

Click to show [Full Publications]

  • Reviewer or program committee member for CVPR'2021-2023, ICCV'2021-2023, ECCV'2022, ICML'2022-2023, NeurIPS'2022-2023, ICLR'2023, Siggraph'2022, Siggraph Aisa'2022, WACV'2022, IJCAI'2023, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), IEEE Transaction on Image Processing (TIP), IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), International Journal of Computer Vision (IJCV), NeuroComputing, IEEE Transactions on Computational Imaging (TCI).
  • Workshop Organizer for ECCV RLQ-TOD Workshop 2020
  • Invited Talk
  • [Jan 2023] "Learning to Enhance Low-light Images without Paired Supervision" at [IEEE SPS Webinar], after my TIP work EnlightenGAN was hilighted as one of SPS's top-25 most downloaded articles on IEEE Xplore®, 2021-2022
  • [Jan 2022] "Fast and High Quality Image Denoising via Malleable Convolution" at Adobe, NextCam.
  • [July 2021] "Vision Transformer for Image Generation, Editing, and Processing" at Google Research, GCam.
  • [Mar 2021] "TransGAN: Two Transformers Can Make One Strong GAN, and That Can Scale Up." at [机器之心], [智源社区], [cai-workshop], University of Oregon

  • The website template was originally borrowed from [1], then further optimized from [2],[3]. Thanks to these guys!