I'm currently a Software Engineer with the Google Pixel camera team, where I'm deeply involved in creating new camera features and significantly improving image quality through the application of generative AI.
Before joining Google, my experience included research at NEC Labs America in autonomous driving and as a research scientist at Meta focusing on product recognition.
I earned my Ph.D. from Umass Amherst, where I was in the computer vision lab advised by Prof. Subhransu Maji.
My research focus was on learning with limited training data, which is related to domain adaptation, zero-/few-shot learning, semi-/self-supervised learning, transfer learning, etc.
Here is my Resume.
Publications
AutoScape: Geometry-Consistent Long-Horizon Scene Generation
Jiacheng Chen, Ziyu Jiang, Mingfu Liang, Bingbing Zhuang,
Jong-Chyi Su, Sparsh Garg, Ying Wu, Manmohan Chandraker
International Conference on Computer Vision (ICCV), 2025
AIDE: An Automatic Data Engine for Object Detection in Autonomous Driving
Mingfu Liang,
Jong-Chyi Su, Samuel Schulter, Sparsh Garg, Shiyu Zhao, Ying Wu, Manmohan Chandraker
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024
arXiv,
pdf
Tell Me What Happened: Unifying Text-guided Video Completion via Multimodal Masked Video Generation
Tsu-Jui Fu, Licheng Yu, Ning Zhang, Cheng-Yang Fu,
Jong-Chyi Su, William Yang Wang, Sean Bell
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023
arXiv
RoPAWS: Robust Semi-supervised Representation Learning from Uncurated Data
Sangwoo Mo,
Jong-Chyi Su, Kevin Chih-Yao Ma, Mido Assran, Ishan Misra, Licheng Yu, Sean Bell
International Conference on Learning Representations (ICLR), 2023
arXiv
Semi-Supervised Learning with Taxonomic Labels
Jong-Chyi Su, Subhransu Maji
British Machine Vision Conference (BMVC), 2021
arXiv,
Github,
slides
On Equivariant and Invariant Learning of Object Landmark Representations
Zezhou Cheng,
Jong-Chyi Su, Subhransu Maji
International Conference on Computer Vision (ICCV), 2021
arXiv,
project page,
Github
A Realistic Evaluation of Semi-Supervised Learning for Fine-Grained Classification
Jong-Chyi Su, Zezhou Cheng, Subhransu Maji
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (oral), 2021
arXiv,
Github,
poster,
slides
When Does Self-supervision Improve Few-shot Learning?
Jong-Chyi Su, Subhransu Maji, Bharath Hariharan
European Conference on Computer Vision (ECCV), 2020
arXiv,
project page,
Github,
slides
Active Adversarial Domain Adaptation
Jong-Chyi Su, Yi-Hsuan Tsai, Kihyuk Sohn, Buyu Liu, Subhransu Maji, Manmohan Chandraker
Winter Conference on Applications of Computer Vision (WACV), 2020
arXiv
A Deeper Look at 3D Shape Classifiers
Jong-Chyi Su, Matheus Gadelha, Rui Wang, Subhransu Maji
Second Workshop on 3D Reconstruction Meets Semantics at ECCV, 2018
arXiv,
project page/dataset,
pdf,
mvcnn code in PyTorch
Reasoning about Fine-grained Attribute Phrases using Reference Games
Jong-Chyi Su*, Chenyun Wu*, Huaizu Jiang, Subhransu Maji
International Conference on Computer Vision (ICCV), 2017
arXiv,
project page,
pdf,
dataset and code in Tensorflow
Adapting Models to Signal Degradation using Distillation
Jong-Chyi Su, Subhransu Maji
British Machine Vision Conference (BMVC), 2017
arXiv,
project page,
pdf,
code in matconvnet
Depth Estimation and Specular Removal for Glossy Surfaces Using Point and Line Consistency with Light-Field Cameras
Michael Tao,
Jong-Chyi Su, Ting-Chun Wang, Jitendra Malik, and Ravi Ramamoorthi
IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), Volume 38 Issue 6, June 2016
pdf,
code/dataset