Yuyang Zhao

I am currently a Ph.D. candidate in the Computer Vision and Robotic Perception (CVRP) Laboratory at National University of Singapore, under the supervision of A/P Gim Hee Lee. I received my B.E. degree from Tianjin University in 2020.

My research interests lie in building generalizable computer vision systems, especially securing model performance under distribution and category shifts. Currently, I am focusing on generalizable semantic segmentation.

Extension of our ECCV 2022 paper (SHADE). This paper applies SHADE to visual domain generalization tasks, including semantic segmentation with Transformer backbone, image classification, and object detection.

Synthetic-to-Real Domain Generalized Semantic Segmentation for 3D Indoor Point Clouds
Yuyang Zhao, Na Zhao, Gim Hee Lee
Arxiv
PDF / Code (Coming Soon!)

The first work on domain generalized semantic segmentation in 3D indoor scenes.

2022

AdvStyle adversarially changes the channel-wise mean and standard deviation to diversify source samples.

We introduce a dual consistency learning framework for domain generalized semantic segmentation, and propose a style hallucination module to generate pair-wise stylized samples.

The first work focuses on novel class discovery in semantic segmentation. This work addresses the co-occurrence of base, novel and background classes.

2021

Stolen from Jon Barron