I am a PhD student in Computer Science at UCLA, working in the Center for Vision, Cognition, Learning, and Autonomy advised by Professor Song-Chun Zhu.
My research interests include Computer Vision, Artificial Intelligence, and Machine Learning.
University of California, Los Angeles hangqi (at) cs.ucla.edu
Restricted Visual Turing Test
Joint work with Tianfu Wu, Mun-Wai Lee, and Song-Chun Zhu
This project features a restricted visual Turing test (VTT) which evaluates computer vision systems' understanding of scenes and events in videos by story-line based queries. We collected a long-term and multi-camera captured video dataset. To perform the test, we built an integrated system consisting of a well-designed architecture, various vision modules, a knowledge base, and a query engine.Project Website
Paleo: A Performance Model for Deep Neural Networks
Joint work with Evan R. Sparks and Ameet Talwalkar
Paleo is an analytical model to estimate the scalability and performance of deep learning systems. It can be used for efficiently exploring the space of scalable deep learning systems and quickly diagnosing their effectiveness for a given problem instances. Paleo is robust to the choice of network architecture, hardware, software, communication schemes, and parallelization strategies.
Runner-up price for best real-world application at Southern California Machine Learning Symposium 2016.
Topic Discovery and Story Segmentation for Broadcast News
Joint work with Weixin Li, Jungseock Joo, and Song-Chun Zhu
Topic discovery and story segmentation provides fundamental methods for automatically organizing, analyzing, searching, and visualizing the vast amount of news videos available online. In this project, we present a topic discovery and story segmentation framework based on Swendsen-Wang Cuts, aiming at dividing news videos into stories and generating a topic hierarchy to organize these stories.Project Page
Scene-centric Joint Parsing of Cross-view Videos.
Hang Qi*, Yuanlu Xu*, Tao Yuan*, Tianfu Wu, and Song-Chun Zhu.
AAAI Conference on Artificial Intelligence (AAAI), 2018 (Oral). [pdf]
Learning with Imprinted Weights.
Hang Qi, Matthew Brown, and David G. Lowe.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018. [pdf]
Paleo: A Performance Model for Deep Neural Networks.
Hang Qi, Evan R. Sparks, and Ameet Talwalkar.
International Conference on Learning Representations (ICLR), 2017. [pdf]
Joint Image-Text News Topic Detection and Tracking by Multimodal Topic And-Or Graph.
Weixin Li, Jungseock Joo, Hang Qi, and Song-Chun Zhu.
IEEE Transactions on Multimedia (TMM), Volume 19 Issue 2, February 2017. [pdf]
A Restricted Visual Turing Test for Deep Scene and Event Understanding.
Hang Qi*, Tianfu Wu*, Mun Wai Lee, and Song-Chun Zhu.
arXiv:1512.01715. 2015. [pdf]
Fall 2015: TA for CS 161 Fundamentals of Artificial IntelligenceI hosted weekly discussion sections covering LISP, search algorithms, propositional logic, first-order logic, Bayesian networks, etc.
MISC & Open-Source
A light-weight Graph library where each vertex and edge can be associated with arbitrarily typed properties.
Notes on Statistical Programming
Python implementations of Statistic and Machine Learning algorithms, including linear regression, logistic regression, neural networks, AdaBoost, SVM, LASSO, Monte Carlo, etc.