Jing Shi  

Research Scientist, Adobe Research

jingshi [AT] adobe.com

Bio

I am a research scientist at Adobe Research, San Jose. My primary interests are in visual perception and generation/manipulation with the interaction of language. My recent work has focused on language-based image editing, scene understanding, and content authenticity. I am also interested in the principled way to understand the representation learning.

Before joining Adobe, I obtained my CS PhD at the University of Rochester in 2022, advised by Chenliang Xu, B.E. degree at University of Electronic Science and Technology of China. I have interned at Adobe Research with Ning Xu and Tencent with Jia Xu and Boqing Gong.

Internship advice:
I'm happy to collaborate with enthusiastic and talented PhD in computer science. I will hire multiple research interns in the summer. If you are interested in working with me, e-mail me your CV and a brief description of what you would like to work on during your internship.

News

  • [Sep/2022] I start my new position as a research sicentist at Adobe Research, San Jose, CA.
  • [Sep/2022] Successfully defend my dissertation! Thanks to everyone who supported me and helped me along the way.
  • [Mar/2022] One paper accepted by CVPR2022 about a unified model for color editing that can supports various downstream tasks.
  • [Jul/2021] Three papers accepted by ICCV2021: two about language and scene understanding, one about language driven image editing.
  • [Mar/2021] Our language driven image editing paper is accepted by CVPR2021.
  • [Sep/2020] Our language driven image editing paper is accepted by ACCV2020 Oral.
  • [Feb/2019] Our weakly supervised video grounding paper is accepted by CVPR 2019.

Publications

Most recent publications on Google Scholar.
‡ indicates equal contribution.

InstantBooth: Personalized Text-to-Image Generation without Test-Time Finetuning

Jing Shi‡, Wei Xiong‡, Zhe Lin, Hyun Joon Jung

Arxiv Preprint, 2023

Paper Project

SpaceEdit: Learning a Unified Editing Space for Open-Domain Image Color Editing

Jing Shi, Ning Xu, Haitian Zheng, Alex Smith, Jiebo Luo, Chenliang Xu

Computer Vision and Pattern Recognition (CVPR), 2022

Paper

A Simple Baseline for Weakly-Supervised Scene Graph Generation

Jing Shi, Yiwu Zhong, Ning Xu, Yin Li, Chenliang Xu

International Conference on Computer Vision (ICCV), 2021

Paper

Learning to Generate Scene Graph from Natural Language Supervision

Yiwu Zhong, Jing Shi, Jianwei Yang, Chenliang Xu Yin Li,

International Conference on Computer Vision (ICCV), 2021

Paper Code

Language-Guided Global Image Editing via Cross-Modal Cyclic Mechanism

Wentao Jiang, Ning Xu, Jiayun Wang, Chen Gao, Jing Shi, Zhe Lin, Si Liu ,

International Conference on Computer Vision (ICCV), 2021

Paper

Learning by Planning: Language-Guided Global Image Editing

Jing Shi, Ning Xu, Trung Bui, Franck Dernoncourt, Chenliang Xu

Computer Vision and Pattern Recognition (CVPR), 2021

Paper Project Code

Cubic Spline Smoothing Compensation for Irregularly Sampled Sequences

Jing Shi, Jing Bi, Yingru Liu, Chenliang Xu

Arxiv Preprint

Paper

Learning Continuous-Time Dynamics by Stochastic Differential Networks

Yingru Liu, Yucheng Xing, Xuewen Yang, Xin Wang, Jing Shi, Di Jin, Zhaoyue Chen

International Conference on Neural Information Processing (ICONIP), 2021

Paper

A Benchmark and Baseline for Language-Driven Image Editing

Jing Shi, Ning Xu, Trung Bui, Franck Dernoncourt, Zheng Wen, Chenliang Xu

Asian Conference on Computer Vision (ACCV), 2020

Paper dataset

GAN-EM: GAN Based EM Learning Framework

Wentian Zhao‡, Shaojie Wang‡, Zhihuai Xie, Jing Shi, Chenliang Xu

International Joint Conference on Artificial Intelligence (IJCAI), 2019

Paper Code

Not All Frames Are Equal: Weakly-Supervised Video Groundingwith Contextual Similarity and Visual Clustering Losses

Jing Shi, Jia Xu, Boqing Gong, Chenliang Xu

Computer Vision and Pattern Recognition (CVPR), 2019

Paper Project Code

Audio-Visual Event Localization in Unconstrained Videos

Yapeng Tian, Jing Shi, Bochen Li, Zhiyao Duan, Chenliang Xu

European Conference on Computer Vision (ECCV), 2018

Paper Project Code

Boundary Vibration Control of Variable Length Crane Systems in Two Dimensional Space with Output Constraints

Xiuyu He, Wei He, Jing Shi, Changyin Sun

IEEE/ASME Transactions on Mechatronics (TMech), 2017

Paper

InstantBooth: Personalized Text-to-Image Generation without Test-Time Finetuning

Jing Shi‡, Wei Xiong‡, Zhe Lin, Hyun Joon Jung

Arxiv Preprint, 2023

Paper Project

SpaceEdit: Learning a Unified Editing Space for Open-Domain Image Color Editing

Jing Shi, Ning Xu, Haitian Zheng, Alex Smith, Jiebo Luo, Chenliang Xu

Computer Vision and Pattern Recognition (CVPR), 2022

Paper

A Simple Baseline for Weakly-Supervised Scene Graph Generation

Jing Shi, Yiwu Zhong, Ning Xu, Yin Li, Chenliang Xu

International Conference on Computer Vision (ICCV), 2021

Paper

Learning to Generate Scene Graph from Natural Language Supervision

Yiwu Zhong, Jing Shi, Jianwei Yang, Chenliang Xu Yin Li,

International Conference on Computer Vision (ICCV), 2021

Paper Code

Cubic Spline Smoothing Compensation for Irregularly Sampled Sequences

Jing Shi, Jing Bi, Yingru Liu, Chenliang Xu

Arxiv Preprint

Paper

A Benchmark and Baseline for Language-Driven Image Editing

Jing Shi, Ning Xu, Trung Bui, Franck Dernoncourt, Zheng Wen, Chenliang Xu

Asian Conference on Computer Vision (ACCV), 2020

Paper dataset

Not All Frames Are Equal: Weakly-Supervised Video Groundingwith Contextual Similarity and Visual Clustering Losses

Jing Shi, Jia Xu, Boqing Gong, Chenliang Xu

Computer Vision and Pattern Recognition (CVPR), 2019

Paper Project Code

Audio-Visual Event Localization in Unconstrained Videos

Yapeng Tian, Jing Shi, Bochen Li, Zhiyao Duan, Chenliang Xu

European Conference on Computer Vision (ECCV), 2018

Paper Project Code

Vitæ

Full Resume in PDF.

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Jing Shi
jingshi [AT] adobe.com