I am a software engineer at Google pixel camera team. Before joining Google, I was a researcher at NEC Labs America, and was a research scientist at Meta. I received my Ph.D. at 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. Recently, I have been working on an efficient data engine for training ML models, and generative models for autonomous driving, and using them to improve training. You can find my Resume here.

Publications

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

Preprints

The Semi-Supervised iNaturalist Challenge at the FGVC8 Workshop

Jong-Chyi Su, Subhransu Maji
arXiv, 06/2021
arXiv

The Semi-Supervised iNaturalist-Aves Challenge at FGVC7 Workshop

Jong-Chyi Su, Subhransu Maji
arXiv, 03/2021
arXiv

Challenges

Second Semi-Supervised Challenge at FGVC 8 workshop at CVPR 2021 (Semi-iNat)

Kaggle, Github page

First Semi-Supervised Challenge at FGVC 7 workshop at CVPR 2020 (Semi-Aves)

Kaggle, Github page

Misc

Music that I play