Department of Computer
guojun.qi at ucf dot edu
| guojunq at gmail dot com
Phone: (407) 823-2764
FAX: (407) 823-5835
University of Central Florida
Department of Computer Science
4328 Scorpius HEC 318
Orlando, FL 32816
Learning and Pattern Recognition
Vision and Multimedia Computing
Mining and Data Analytics - Knowledge Discovery and Representation
- 2015 Best Paper Runner-up, International ACM Conference on Multimedia
Best Student Paper Award (co-recipent as the mentor of the student
author), IEEE International Conference on Data Mining (ICDM).
- 2013 "Best of ICDE Paper" by IEEE
Transactions on Knowledge and Data Engineering
IBM Fellowship, IBM
Paper Award, The 15th ACM International Conference on Multimedia (ACM
Best Research Intern, Microsoft Research Asia
Microsoft Fellowship, Microsoft
Scholarship, USTC (Top
Scholarship in USTC)
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- We propose a Loss-Sensitive GAN (LS-GAN), along with a generalized version (GLS-GAN) unifying both WGAN and LS-GAN. See more details in [pdf] and the Appendix D. Moreover, you might be interested in taking a look at an incomplete map of GANs in our view [url].
- Dr. Qi will serve as an Area Chair for ICCV 2017.
- Dr. Qi is serving as an Area Chair for ICME 2017.
- A paper on learning compact features that encode dynamics of video and sensor data has been accepted by ACM TOMM.
- A paper on jointly learning label classification and tag recommendation has been accepted by AAAI 2017.
- One paper developing an efficient
ranking-based hashing algorithm has been accepted for the publication
in IEEE Transactions on Pattern Analysis and Machine Intelligence. [pdf] [code]
- One paper
"Tri-Clustered Tensor Completion for Social-Aware Image Tag Refinement"
has been accepted for publication in IEEE Transactions on Pattern
Analysis and Machine Intelligence.
paper has been accepted by IEEE Transactions on Pattern Analysis and
Machine Intelligence for classifying images of rarely seen or unseen
classes with the help of text labels. [pdf][code]
- Two research papers, including an oral presentation "Hierarchically Gated Deep Networks for Segmantic Segmentation", have been accepted for presentation at CVPR 2016, Las Vegas, Nevada. [pdf]
paper has been accepted for plenary presentation at SIGKDD 2016. A fast
detection method for brain disorder based on fMRI was presented. It is
one order of magnitude faster than state-of-the-art methods with even
- Dr. Qi is serving as an Area Chair for ACM Multimedia 2016.
- Dr. Qi will serve as a Senior Program Committee Member for KDD 2016.
- International Conference on MultiMedia Modeling will go to Miami FL, 4-6 January 2016 [link]. Dr. Qi will serve as program co-chair.
- CFP: Special Issue on "Big Media Data: Understanding, Search, and Mining", in IEEE Transactions on Big Data [pdf] (deadline: July 1, 2015).
- CFP: "Deep Learning for Multimedia Computing", in IEEE Transactions on Multimedia [pdf] (The new deadline is April 20, 2015).
- Our full research paper
"Weekly-Shared Deep Transfer Networks for
Heterogeneous-Domain Knowledge Propagation" has been selected as one
of the four best paper
candidates to be presented at ACM MM 2015.
paper is accepted by ICCV
2015. We developed a novel deep LSTM
model for analyzing human actions, where we explore the differential structure over memory states to study the dynamic saliency.
full research paper "Weekly-Shared Deep Transfer Networks for
Heterogeneous-Domain Knowledge Propagation" is accepted by ACM MM 2015.
We developed a
novel cross-modal label transfer deep network, showing competitive
performance on predicting image labels derived from the
alignment with text documents.
- Dr. Qi is serving as an Area Chair for ACM Multimedia 2015.
papers are accepted by KDD
2015. Congratulations to Vivek, Rohit, Shiyu and Wei!
In these papers, (1) we developed deep networks to reveal the
brain neural connectivity by aligning time-series
neuron fires that are marked by calcium influx; (2) we
invented a new paradigm
of dynamic model to select and predict sensors and their readings over
time, as compared with the conventional static strategy; and (3) we
heterogeneous networks to predict the cross-modal relevance between
paper "Temporal-Order Preserving Dynamic Quantization for Human Action
Recognition from Multimodal Sensor Streams" accepted by ICMR 2015.
UTKinect-Action dataset, our best approach has achieved 100% accuracy. Congralulations
to Jun and Kai!
- One paper "Sparse Composite
Quantization" has been accepted by CVPR
2015. Congralutions to Ting!
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