Hanxiao Jiang(Shawn) | 蒋含啸

为天地立心,为生民立命。 为往圣继绝学,为万世开太平。 --- 《横渠语录》
To ordain conscience for Heaven and Earth. To secure life and fortune for the people. To continue lost teachings for past sages. To establish peace for all future generations.

I'm a theis-based master student of computer science at Simon Fraser University, instructed by professor Angel Xuan Chang. Prior to this, I received my Bachelor of Engineer & Bachelor of Science from Zhejiang University and Simon Fraser University. Currently I am also a research assistant in SFU Gruiv Group working with professor Angel Xuan Chang and professor Manolis Savva at Simon Fraser University. My research interests are 3D vision and robotics vision.

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Hanxiao Jiang
shawn_jiang-{at}-sfu-"dot"-ca

Thesis-based Master Student
Sep 2020 - Present
Simon Fraser University
Research Assistant (Gruiv & 3dlg)
Google Scholar

Publications

Motion Annotation Programs: A Scalable Approach to Annotating Kinematic Articulations in Large 3D Shape Collections  

Motion Annotation Programs: A Scalable Approach to Annotating Kinematic Articulations in Large 3D Shape Collections

Xianghao Xu, David Charatan, Sonia Raychaudhuri, Hanxiao Jiang, Mae Heitmann, Vladimir Kim, Siddhartha Chaudhuri, Manolis Savva, Angel X.Chang, Daniel Ritchie
3DV 2020

We present a system that helps individual expert users rapidly annotate kinematic motions in large 3D shape collections. The organizing concept of our system is motion annotation programs: simple, re-usable procedural rules that generate motion for a given input shape.

[Paper] [Project] [Demo]

SAPIEN: A SimulAted Part-based Interactive ENvironment  

SAPIEN: A SimulAted Part-based Interactive ENvironment

Fanbo Xiang*, Yuzhe Qin*, Kaichun Mo, Yikuan Xia, Hao Zhu, Fangchen Liu, Minghua Liu, Hanxiao Jiang, Yifu Yuan, He Wang, Li Yi, Angel X.Chang, Leonidas J. Guibas and Hao Su
CVPR 2020, Oral Presentation

We propose a realistic and physics-rich simulation environment hosting large-scale 3D articulated objects from ShapeNet and PartNet. Our PartNet-Mobility dataset contains 14,068 articulated parts with part motion information for 2,346 object models from 46 common indoor object categories. SAPIEN enables various robotic vision and interaction tasks that require detailed part-level understanding.

[Paper] [Project] [Demo]

Evaluating Colour Constancy on the new MIST dataset of Multi-Illuminant Scenes  

Evaluating Colour Constancy on the new MIST dataset of Multi-Illuminant Scenes

Xiangpeng Hao, Brian Funt, Hanxiao Jiang
CIC 2019, Oral Presentation

A new image test set of synthetically generated, full-spectrum images with pixelwise ground truth has been developed to aid in the evaluation of illumination estimation methods for colour constancy. The performance of 9 illumination methods is reported for this dataset along and compared to the optimal single-illuminant estimate. None of the methods specifically designed to handle multi-illuminant scenes is found to perform any better than the optimal single-illuminant case based on completely uniform illumination.

[Paper]