Shuai Liao

I obtained my Ph.D. from University of Amsterdam, the Netherlands, focusing on computer vision and deep learning.

I did internship at Qualcomm AI Research, Netherlands in 2020. I was a visiting research intern at the University of Queensland, Australia in 2014.

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Research Interests

I am interested in 3D computer vision and video understanding. I have a good understanding of multiple view geometry and I am passionate about Autonomous driving and AR/VR. In particular, I have experience with:

3D computer vision:
Viewpoint estimation; 6DOF pose estimation; 3D object detection;
3D rotation estimation; Surface normal estimation; Depth estimation.
Image classification:
Multi-label classification; Zero-shot learning; Adversarial attacks and defenses; Credible classification/confidence calibration.
Video understanding:
Optical flow estimation; Video object segmentation/detection.

News

[Sep. 22, 2021] I have recently defended my doctorate of philosophy. 🎉

Publications [Full list]
	Quasibinary Classifier for Images with Zero and Multiple Labels Shuai Liao, Efstratios Gavves, ChangYong Oh, Cees G. M. Snoek ICPR, 2020 poster / bibtex It is well-known that one-vs.-rest classification and multi-label classification need to be handled by the right classifier, i.e. softmax classifier vs. sigmoid classifiers. Could it be simpler? Yes. Quasibinary classifier might be the only classifier you need. And even better, Quasibinary classifier yields well-calibrated probabilities that are critical to tasks such as autonomous driving and clinical diagnosis.
	Spherical Regression: Learning Viewpoints, Surface Normals and 3D Rotations on n-Spheres Shuai Liao, Efstratios Gavves, Cees G. M. Snoek CVPR, 2019 project page / bibtex / arXiv / supplemental materials Regression problems have always been tricky for deep neural networks to learn, mainly due to unstable gradient. To resolve this, we proposal spherical regression, a plugin module that boosts the performance for three regression tasks in computer vision at the same time. We also present a 3D rotation estimation dataset called ModelNet10-SO3.
	Searching and Matching Texture-free 3D Shapes in Images Shuai Liao, Efstratios Gavves, Cees G. M. Snoek ICMR, 2018 poster / bibtex We present a pipeline that automatically selects and aligns textureless 3D shapes (e.g. CAD models) onto 2D images. This is particular useful for collecting training data for autonomous driving.
	Tag Features for Geo-Aware Image Classification Shuai Liao, Xirong Li, Heng Tao Shen Yang Yang Xiaoyong Du IEEE Transactions on Multimedia (TMM), 2015 bibtex
	Zero-shot Image Tagging by Hierarchical Semantic Embedding Xirong Li, Shuai Liao, Weiyu Lan, Xiaoyong Du, Gang Yang SIGIR, 2015 project page / bibtex
	Building geo-aware tag features for image classification Shuai Liao, Xirong Li, Xiaoxu Wang, Xiaoyong Du IEEE International Conference on Multimedia and Expo (ICME), 2014 bibtex