About me

I am an applied scientist working with Dr. Mu Li and Dr. Alex Smola in Amazon AI. Before joining Amazon, I received my PhD at UC Merced under the supervision of Prof. Shawn Newsam. My research interests mainly focus on video understanding, representation learning, semantic segmentation, and flow/depth estimation.

We have several intern positions for Spring, Summer and Fall 2022, please contact me if you are interested in contributing to open source projects and doing research in video self-supervised learning, multimodality learning and transformer for vision.

News

09/2021: Two NeurIPS 2021 papers are accepted, on anti-aliasing for vision transformer and 3D object detection.

07/2021: Three ICCV 2021 papers are accepted, on video transformer, model robustness and multi-modal video representations.

06/2021: Three workshops to be organized at ICCV 2021, video scene parsing, airborne object tracking and multi-modality learning beyond video.

03/2021: One CVPR 2021 paper on universal domain adaptation is accepted.

02/2021: I will organize the 2nd A comprehensive tutorial on video modeling in CVPR 2021. Stay tuned.

12/2020: One survey paper on video action recognition is released together with GluonCV 0.9.0.

08/2020: One WACV 2021 paper on semantic segmentation domain adaptation is accepted.

07/2020: One ECCV 2020 paper on video adversarial attack is accepted.

02/2020: I will organize a tutorial A comprehensive tutorial on video modeling in CVPR 2020.

01/2020: One JMLR 2020 paper on GluonCV and GluonNLP is accepted. Welcome to use our toolkits.

12/2019: One WACV 2020 paper on overhead image geolocalization is accepted.

07/2019: One BMVC 2019 paper on video anomaly detection is accepted.

05/2019: Successfully passed dissertation defense. Thank you, Shawn, Trevor and Ming-Hsuan. My full dissertation on video understanding can be found at here.

02/2019: One CVPR 2019 paper on street scene segmentation is accepted as Oral presentation.

12/2018: One TMM 2019 paper on large-scale land use classification is accepted.

09/2018: Three ACCV 2018 papers are accepted, on fast video classification, video tempo learning and transfer learning.

07/2018: Our work on generating ground level views from satellite imagery is covered by MIT technology review, Internet of Business, GIS Lounge, DeepTech. We also had an interview with This Week in Machine Learning & AI and the Youtube link can be found here.

04/2018: Two ICIP 2018 papers are accepted on optical flow estimation.

02/2018: One CVPR 2018 paper on zero-shot action recognition is accepted.