Ruiheng Chang (常瑞恒)

Hi, my name is Ruiheng Chang(常瑞恒), a senior undergraduate student from Department of Computer Science, Shanghai Jiao Tong University. I am also a member of Zhiyuan Honor's Program of Engineering.

I am a member of Machine Vision and Inteligence Group directed by Prof. Cewu Lu. My reserach interests lie in the field of computer vision and deep learning.

Email  /  CV /  GitHub  /  LinkedIn


Education

Shanghai Jiao Tong University, China

  • B.Sc., Department of Computer Science & Zhiyuan College
  • Sept. 2015 to June. 2019 (Expected)

Publications

Annotation-Free and One-Shot Learning for Instance Segmentation of Homogeneous Object Clusters
Zheng Wu, Ruiheng Chang, Jiaxu Ma, Cewu Lu, Chi Keung Tang
In the proceedings of IJCAI 2018, the Twenty-Seventh International Joint Conference on Artificial Intelligence

  • We propose an efficient framework for instance segmentation of homogeneous object cluster (HOC). Our proposed method significantly reduces the cost of data collection and labeling.
  • We propose an efficient method to generate realistic synthetic training data which significantly improves instance segmentation performance.
  • We build a dataset consisting of pixel-level annotated images of HOC.


Scholarships
  • National Scholarship, highest honor for undergraduates in China, top 0.2% nationwide  
  • Academic Excellence Scholarship (A-Class), awarded to top 1% students in SJTU  
  • Zhiyuan College Honored Scholarship, awarded to members of Zhiyuan Honors Program, top 5%  
  • Excellent Undergraduate Scholarship of Yang Yuanqing Education Fund, awarded to 4 students in CS department of SJTU  
  • SenseTime Scholarship, awarded to 24 students nationwide  
  • Huawei Scholarship, awarded to top 5% students in School of Electronic Information and Electrical Engineering  

Honors and Awards
  • Outstanding Winner & Vilfredo Pareto Award of Interdisciplinary Contest In Modeling (ICM), top 0.1% worldwide  
  • 6th place in Microsoft COCO Keypoints Challenge 2017, ICCV 2017 workshop, core developer  
  • 1th place in ICRA Tidy Up My Room Challenge, ICRA 2018 competition, core developer  
  • National 2nd Prize in Chinese Undergraduate Mathematical Contest in Modelling, top 2% nationwide  
  • 10th place in AI Challenger Human Skeletal System Keypoints Detection competition track, core developer  
  • Most Commercial Award in Microsoft Penta Hackathon, top 5 of all teams  
  • Rank 13/1198 in Microsoft Beauty of Programming  
  • National 3rd Prize in Chinese Undergraduate Mathematics Competition  
  • 2nd Prize in Chinese Undergraduate Physics Competition  
  • Merit Student of Shanghai Jiao Tong University  
  • 1st Prize in China Physics Olympiads at province level  

Selected Projects
pose

Alpha Pose, an Accurate Multi-person Pose Estimation System

Alpha Pose is an accurate multi-person pose estimation system.

  • It is the first open-sourced system that can achieve 70+ mAP (72.3 mAP) on COCO dataset and 80+ mAP (82.1 mAP) on MPII dataset.
  • To associate poses that indicates the same person across frames, we also provide an efficient online pose tracker called Pose Flow. It is also the first open-sourced online pose tracker that can both satisfy 60+ mAP (66.5 mAP) and 50+ MOTA (58.3 MOTA) on PoseTrack Challenge dataset.
  • View it on github:

sjtubot

SJTU Bot, a Question Answer System

The project was completed for Beauty Of Programming 2017 Competition.

  • We propose a sequence to sequence approach to judge the Matching Degree of question-answer pair.
  • We propose a algorithm to answer a question based on seqtoseq approach and information distilling technique.
  • We develop a bot service based on Microsoft Azure for answering questions of everything about SJTU.
  • The project rank 13/1198 in Microsoft Beauty of Programming 2017.
  • View it on github:

d++

Didi Plus Plus, an Extension for Didi Taxi

  • Propose a new idea for Didi Taxi. Based on big data mining, we generate individual ID card for each taxi driver. When customer choose the taxi, the system will sort the taxi driver based on the preference of the customer.
  • The project won the Most Commercial Award in the 2nd Penta Hackathon.