Weijie Kong - 孔伟杰

Master Student - Computer Applications Technology

school Institution: Digital Media R&D Center, School of Electronic and Computer Engineering, Peking Univerity

home Office: B201, Peking University Campus, University Town, Xili, Nanshan District, Shenzhen, China, 518055

email Email: weijie.kong@pku.edu.cn

Interests
  • fiber_manual_recordComputer Vision
  • fiber_manual_recordVideo Understanding
  • fiber_manual_recordHuman Action Detection
  • fiber_manual_recordObject Detection
  • fiber_manual_recordPedestrain Detection
  • fiber_manual_recordMachine Learning
Education
  • school MSc in Computer Applications Technology, 2020
    Peking Univerity, Shenzhen, China
  • school BA in Software Engineering, 2017
    Northeastern University, Shenyang, China

About Me

I’m a second-year graduate student in Digital Media R&D Center, Peking Univerity, advised by Prof. Ge Li.

Before starting my M.S., I received my B.S. in Software Engineering from Northeastern University in 2017.

Currently, my main research insterests are in video understanding and human activity detection. In general, I'm interested in computer vision and machine learning.

News

Publications

Graph Convolutional Label Noise Cleaner: Train a Plug-and-play Action Classifier for Anomaly Detection
Jia-Xing Zhong, Nannan Li, Weijie Kong, Shan Liu, Thomas H. Li, Ge Li
Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
BLP - BOUNDARY LIKELIHOOD PINPOINTING NETWORKS FOR ACCURATE TEMPORAL ACTION LOCALIZATION
Weijie Kong, Nannan Li, Shan Liu, Thomas H. Li, Ge Li
International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2019.
Step-by-step Erasion, One-by-one Collection: A Weakly Supervised Temporal Action Detector
Jia-Xing Zhong, Nannan Li, Weijie Kong, Tao Zhang, Thomas H. Li, Ge Li
ACM International Conference on Multimedia (ACMMM), 2018.
Deep Pedestrian Detection Using Contextual Information and Multi-level Features
Weijie Kong, Nannan Li, Thomas H. Li, and Ge Li.
International Conference on Multimedia Modeling (MMM), 2018. (Oral presentation)