Full PUBLICATION LIST

(The list is up to 2023. For the complete list, please check DBLP.)

Book Chapters

  • Shen-Fu Tsai, Guo-Jun Qi, Shiyu Chang, Min-Hsuan Tsai, and Thomas Huang, Clustering Multimedia Data, in Data Classification: Algorithms and Applications (edited by Charu Aggarwal), Chapman and Hall/CRC, 2013.
  • Guo-Jun Qi and Hong-Jiang Zhang. Large-Scale Online Multi-Labeled Annotation for Multimedia Search and Mining,  in Internet Multimedia Search and Mining (Edited by X.-S. Hua, M. Worrying and T.-S. Chua), Bentham Science Publishers, 2010.
  • Liangliang Cao, Guo-Jun Qi, Shen-Fu Tsai, Min-Hsuan Tsai, Andrey Del Pozo, Thomas S. Huang, Suk Hwan Lim and Xumei Zhang.  Multimedia Information Networks in Social Media, in Social Network Data Analytics (edited by Charu Aggarwal), Springer, 2010
  • Guo-Jun Qi et al. Correlative Multi-Label Video Annotation, in Innovation Together: Microsoft Research Asia Academic Research Collaboration (Edited by L. Song), Springer, 2008.
  • Meng Wang, Xian-Sheng Hua, Jinhui Tang and Guo-Jun Qi. Active Video Annotation: To Minimize Human Effort, to appear in Semantic Mining Technologies for Multimedia Databases (Edited by D. Tao, D. Xu and X. Li), Idea Group Inc, 2008.  

 

Refereed Journal papers

  • Xiao Wang, Yuhang Huang, Dan Zeng, Guo-Jun Qi. CaCo: Both Positive and Negative Samples are Directly Learnable via Cooperative-adversarial Contrastive Learning,  in IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), March, 2023. 
  • Guangwei Gao, Zixiang Xu, Juncheng Li, Jian Yang, Tieyong Zeng, Guo-Jun Qi. CTCNet: A CNN-Transformer Cooperation Network for Face Image Super-Resolution, in IEEE Transactions on Image Processing (T-IP), March, 2023.
  • Zechao Li, Hao Tang, Zhimao Peng, Guo-Jun Qi, Jinhui Tang. Knowledge-Guided Semantic Transfer Network for Few-Shot Image Recognition, in IEEE Transactions on Neural Networks and Learning Systems (T-NNLS), January, 2023.
  • Xiao Wang, Guo-Jun Qi. Contrastive Learning with Stronger Augmentations, in IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), August, 2022.
  • Sanyi Zhang§, Xiaochun Cao, Guo-Jun Qi, Zhanjie Song, and Jie Zhou. AIParsing: Anchor-free Instance-level Human Parsing, in IEEE Transactions on Image Processing (T-IP), 2022. 
  • Ruin Wang§, Zuxuan Wu, Zejia Weng, Jingjing Chen, Guo-Jun Qi, Yu-Gang Jiang. Cross-domain Contrastive Learning for Unsupervised Domain Adaptation, in IEEE Transactions on Multimedia (T-MM), 2022. 
  • Xiang Gao, Wei Hu, and Guo-Jun Qi. Self-Supervised Graph Representation Learning via Topology Transformations, in IEEE Transactions on Knowledge and Data Engineering (T-KDE), 2021.
  • Haohang Xu, Hongkai Xiong, Guo-Jun Qi. K-Shot Contrastive Learning of Visual Features with Multiple Instance Augmentations, in IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2021.
  • Yuhui Xu, Lingxi Xie, Wenrui Dai, Xiaopeng Zhang, Xin Chen, Guo-Jun Qi, Hongkai Xiong, Qi Tian. Partially-Connected Neural Architecture Search for Reduced Computational Redundancy, in IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2021.
  • Xiangbo Shu, Liyan Zhang, Guo-Jun Qi, Wei Liu, Jinhui Tang. Spatiotemporal Co-attention Recurrent Neural Networks for Human-Skeleton Motion Prediction, in IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2021.
  • Guangwei Gao, Yi Yu, Jian Yang, Yujie Li, Guo-Jun Qi. Hierarchical Deep CNN Feature Set-Based Representation Learning for Robust Cross-Resolution Face Recognition, in IEEE Transactions on Circuits and Systems for Video Technology (CSVT), 2020. 
  • Sanyi Zhang, Guo-Jun Qi, Xiaochun Cao, Zhanjie Song, Jie Zhou. Human Parsing with Pyramidical Gather-Excite Context, in IEEE Transactions on Circuits and Systems for Video Technology (CSVT), April, 2020.
  • Mohsen Joneidi, Alireza Zaeemzadeh, Behzad Shahrasbi, Guo-Jun Qi, Nazanin Rahnavard, E-Optimal Sensor Selection for Compressive Sensing-Based Purposes, in IEEE Transactions on Big Data, Volumn 6, Issue 1, March 2020.  (featured in IEEE Computer's "Spotlight on Transactions" Column)
  • Xiao Wang, Daisuke Kihara, Jiebo Luo, Guo-Jun Qi. EnAET: A Self-Trained Framework for Semi-Supervised and Supervised Learning with Ensemble Transformations, in IEEE Transactions on Image Processing (T-IP), November, 2020.
  • Guo-Jun Qi, Jiebo Luo. Small Data Challenges in Big Data Era: A Survey of Recent Progress on Unsupervised and Semi-Supervised Methods, in IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2020. 
  • Guo-Jun Qi, Liheng Zhang, Feng Lin, Xiao Wang. Learning Generalized Transformation Equivariant Representations via Autoencoding Transformations, in IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2020. 
  • Guo-Jun Qi, Loss-Sensitive Generative Adversarial Networks on Lipschitz Densities, to appear in International Journal of Computer Vision (IJCV), 2019.
  • Xiangbo Shu, Jinhui Tang, Guo-Jun Qi, Wei Liu, Jian Yang. Hierarchical Long Short-Term Concurrent Memory for Human Interaction Recognition, to appear in IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2019. 
  • Xiangyu Zhu, Hao Liu, Zhen Lei, Hailin Shi, Fan Yang, Dong Yi, Guo-Jun Qi, Stan Z. Li. Large-scale Bisample Learning on ID Versus Spot Face Recognition,  in International Journal of Computer Vision (IJCV), Volume 127, Number 6-7, June 2019.  
  • Lu Jin§, Xiangbo Shu, Kai Li, Zechao Li, Guo-Jun Qi, Jinhui Tang. Deep Ordinal Hashing With Spatial Attention, in IEEE Transactions on Image Processing (T-IP), Volume 5, Issue 5, 2019.
  • Lu Jin, Kai Li, Zechao Li, Fu Xiao, Guo-Jun Qi, Jinhui Tang. Deep Semantic-Preserving Ordinal Hashing for Cross-Modal Similarity Search, in IEEE Transactions on Neural Networks and Learning Systems (T-NNLS), Volume 30, Number 5, 2019. 
  • Naifan Zhuang, Guo-Jun Qi, The Duc Kieu, Kien A. Hua. Rethinking the Combined and Individual Orders of Derivative of States for Differential Recurrent Neural Networks: Deep Differential Recurrent Neural Networks, in ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), Volume 15, Issue 3, Article No. 83, September, 2019. 
  • Chen Shen, Zhongming Jin, Wenqing Chu, Rongxin Jiang, Yaowu Chen, Guo-Jun Qi, Xian-Sheng Hua, Multi-level Similarity Perception Network for Person Re-identification, in ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), Volume 15, Issue 2, 2019. 
  • Jun Ye§, Guo-Jun Qi*, Naifan Zhuang§, Hao Hu§, Kien A. Hua. Learning Compact Features for Human Activity Recognition via Probabilistic First-Take-All, appear in IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), October 2018.
  •  Lu Jin§, Kai Li§, Hao Hu§, Guo-Jun Qi, Jinhui Tang. Semantic Neighbor Graph Hashing for Multimodal Retrieval, in IEEE Transactions on Image Processing (T-IP), Volume 27, Issue 3, pages 1405-1417, March 2018.
  • Jinhui Tang, Shiyu Chang, Guo-Jun Qi, Qi Tian, Yong Rui, Thomas S. Huang. LEMO-MM: Learning Structured Model by Probabilistic Logic Ontology Tree for Multimedia, IEEE Transactions on Image Processing (T-IP), Volume 26, Issue 1, page 196-207, 2017. 
  • Alireza Zaeemzadeh, Mohsen Joneidi, Nazanin Rahnavard, Guo-Jun Qi. Co-SpOT: Cooperative spectrum opportunity detection using bayesian clustering in spectrum-heterogeneous cognitive radio networks, in IEEE Transactions on Cognitive Communications and Networking (T-CCN), Volume 4, Issue 2, page 206-219, December 2017.
  • Jun Ye§, Hao Hu§, Guo-Jun Qi*, Kien Hua. A Temporal Order Modeling Approach to Human Action Recognition from Multimodal Sensor Data, to appear in ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), December 2016.
  • Guo-Jun Qi, Wei Liu, Charu Aggarwal, and Thomas Huang. Joint Intermodal and Intramodal Label Transfers for Extremely Rare or Unseen Classes, to appear in IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), June 2016.
  • Kai Li, Guo-Jun Qi*, Jun Ye, Kien Hua. Linear Subspace Ranking Hashing for Cross-modal Retrieval, to appear in IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), September 2016.
  • Jinhui Tang, Xiangbo Shu, Guo-Jun Qi, Zechao Li, Meng Wang, Shuicheng Yan, and Ramesh Jain. Tri-clustered Tensor Completion for Social-Aware Tag Refinement, to appear in IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), September 2016.
  • Guo-Jun Qi, Charu Aggarwal, and Thomas Huang. Breaking the Barrier to Transferring Link Information across Networks, in IEEE Transactions on Knowledge and Data Engineering, Volume 27, Issue 7, pp. 1741 - 1753, July 2015. (“Best of ICDE 2013 Paper” by IEEE Transactions on KDE)
  • Fuming Sun, Jinhui Tang, Haojie Li, Guo-Jun Qi, Thomas S. Huang. Multi-Label Image Categorization with Sparse Factor Representation, in IEEE Transactions on Image Processing (T-IP), Volume 23, Number 3, pp. 1028-1037, March 2014.
  •  Jinhui Tang, Guo-Jun Qi, Liyan Zhang, Changsheng Xu. Cross-Space Affinity Learning with Its Application to Movie Recommendation, in IEEE Transactions on Knowledge and Data Engineering (T-KDE), Volume 25, Number 7, pp. 1510-1519, July 2013.
  • Guo-Jun Qi, Min-Hsuan Tsai , Shen-Fu Tsai , Liangliang Cao , Thomas Huang. Web-Scale Multimedia Information Networks, in Proceedings of the IEEE, Volume 100, Issue 9, 2012. 
  • Guo-Jun Qi, Xian-Sheng Hua, Yong Rui, Jinhui Tang, Hong-Jiang Zhang.  Image Classification with Kernelized Spatial-Context, in IEEE Transactions on Multimedia, Issue 4, Volume 12, page 278 - 287, June 2010.
  • Jinhui Tang, Richang Hong, Shuicheng Yan, Tat-Seng Chua, Guo-Jun Qi, and Ramesh Jain.  Image Annotation by kNN-Sparse Graph-based Label Propagation over Noisily-Tagged Web Images.  ACM Transactions on Intelligent Systems and Technology, 2010. Invited Paper.
  • Jinhui Tang, Haojie, Li, Guo-Jun Qi, Tat-Seng Chua. Image Annotation by Graph-based Inference with Integrated Multiple/Single Instance Representations, to appear in IEEE Transactions on Multimedia, 2009.
  • Meng Wang, Xian-Sheng Hua, Richang Hong, Jinhui Tang, Guo-Jun Qi, Yan Song. "Unified Video Annotation via Multi-Graph Learning," in IEEE Transactions on Circuits and Systems for Video Technology, vol. 19, no. 5, 2009.
  • Jinhui Tang,  Xian-Sheng Hua, Meng Wang, Zhiwei Gu, Guo-Jun Qi, Xiuqing Wu. Correlative Linear Neighborhood Propagation for Video Annotation,  in IEEE Transactions on Systems, Man, and Cybernetics, Part B, vol. 39, no. 2, 2009.
  • Meng Wang, Xian-Sheng Hua, Tao Mei, Richang Hong, Guo-Jun Qi, Yan Song, Li-Rong Dai. Semi-Supervised Kernel Density Estimation for Video Annotation,  in Computer Vision and Image Understanding, vol. 113, no. 3, 2009.
  • Jinhui Tang, Xian-Sheng Hua, Guo-Jun Qi, Yan Song and Xiuqing Wu.Video Annotation Based on Kernel Linear Neighborhood Propagation, in IEEE Transactions on Multimedia (T-MM), Vol.10, Issue 4, 2008. 
  • Jinhui Tang, Xian-Sheng, Hua, Tao Mei, Guo-Jun Qi and Xiuqing Wu. Video Annotation Based on Temporally Consistent Gaussian Random Field, in Electronics Letters, Vol. 43, Issue 8, 2007.
  • Meng Wang, Xian-Sheng Hua, Tao Mei, Jinhui Tang, Guo-Jun Qi, Yan Song and Li-Rong Dai. Interactive Video Annotation by Multi-Concept Multi-Modality Active Learning, in International Journal Semantic Computing vol. 1, Issue 4, pp. 459-477, 2007.

 

Refereed Conference papers

  • Weijian Luo, Zemin Huang, Zhengyang Geng, J Zico Kolter, Guo-Jun Qi. One-Step Diffusion Distillation through Score Implicit Matching, in Proceedings of The Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024),  December 9 - December 15, Vancouver, Canada, 2024.

  • Liyuan Ma, Xueji Fang, Guo-Jun Qi. Equilibrated Diffusion: Frequency-aware Textual Embedding for Equilibrated Image Customization, in Proceedings of ACM International Conference on Multimedia (ACM MM 2024), 28 October - 1 November 2024, Melbourne, Australia, 2024.    

  • Mengyi Shan, Lu Dong, Yutao Han, Yuan Yao, Tao Liu, Ifeoma Nwogu, Guo-Jun Qi and Mitchell Hill. Towards Open Domain Text-Driven Synthesis of Multi-Person Motions, in Proceedings of European Conference on Computer Vision (ECCV 2024), September 29 – October 4, MiCo Milano, 2024.

  • Bingwen Zhu, Fanyi Wang, Tianyi Lu, Peng Liu, Jingwen Su, Jinxiu Liu, Yanhao Zhang, Zuxuan Wu, Yu-Gang Jiang, Guo-Jun Qi. PoseAnimate: Zero-shot high fidelity pose controllable character animation, The 33rd International Joint Conference on Artificial Intelligence (IJCAI-24), Jeju, August 3-9, 2024.

  • Mingyuan Zhou, Rakib Hyder, Ziwei Xuan, Guo-Jun Qi. UltrAvatar: A Realistic Animatable 3D Avatar Diffusion Model with Authenticity Guided Textures, in Proceedings of IEEE/CVF Conferences on Computer Vision and Pattern Recognition (CVPR 2024), Seattle, USA, June 19-21, 2024.

  • Zhangsihao Yang, Mingyuan Zhou, Mengyi Shan, Bingbing Wen, Ziwei Xuan, Mitch Hill, Junjie Bai, Guo-Jun Qi. OmniMotionGPT: Animal Motion Generation with Limited Data, in Proceedings of IEEE/CVF Conferences on Computer Vision and Pattern Recognition (CVPR 2024), Seattle, USA, June 19-21, 2024.  

  • Yuming Qiao, Fanyi Wang, Jingwen Su, Yanhao Zhang, Yunjie Yu, Siyu Wu, Guo-Jun Qi. BARET : Balanced Attention based Real image Editing driven by Target-text Inversion, in Proceedings of The 38th Annual AAAI Conference on Artificial Intelligence (AAAI 2024), Vancouver, Canada, February 20-27, 2024.

  • Tingting Liao, Xiaomei Zhang, Yuliang Xiu, Hongwei Yi, Xudong Liu, Guo-Jun Qi, Yong Zhang, Xuan Wang, Xiangyu Zhu, Zhen Lei. High-fidelity Clothed Avatar Reconstruction from a Single Image,  in Proceedings of IEEE/CVF Conferences on Computer Vision and Pattern Recognition (CVPR 2023), Vancouver, Canada, June 18-22, 2023. 

  • Zhiyuan Ma , Xiangyu Zhu, Guo-Jun Qi, Zhen Lei, Lei Zhang. OTAvatar: One-shot Talking Face Avatar with Controllable Tri-plane Rendering, in Proceedings of IEEE/CVF Conferences on Computer Vision and Pattern Recognition (CVPR 2023), Vancouver, Canada, June 18-22, 2023.

  • Ce Zheng, Xianpeng Liu, Guo-Jun Qi, Chen Chen. POTTER: Pooling Attention Transformer for Efficient Human Mesh Recovery,  in Proceedings of IEEE/CVF Conferences on Computer Vision and Pattern Recognition (CVPR 2023), Vancouver, Canada, June 18-22, 2023. 

  • Ce Zheng, Matias Mendieta, Taojiannan Yang, Guo-Jun Qi, Chen Chen. FeatER: An Efficient Network for Human Reconstruction via Feature Map-Based TransformER, in Proceedings of IEEE/CVF Conferences on Computer Vision and Pattern Recognition (CVPR 2023), Vancouver, Canada, June 18-22, 2023. 

  • Yutao Han, Youya Xia, Guo-Jun Qi, Mark Campbell. Planning Paths through Occlusions in Urban Environments, in Proceedings of Conference on Robot Learning (CoRL 2022), Auckland, New Zealand, December 14-18, 2022.
  • Ziteng Cui, Yingying Zhu, Lin Gu, Guo-Jun Qi, Xiaoxiao Li, Renrui Zhang, Zenghui Zhang, Tatsuya Harada. Exploring Resolution and Degradation Clues as Self-supervised Signal for Low Quality Object Detection, in Proceedings of European Conference on Computer Vision (ECCV 2022), Tel-Aviv, Isreal, October 23-27, 2022.
  • Ziteng Cui, Guo-Jun Qi, Lin Gu, Shaodi You, Zenghui Zhang, Tatsuya Harada. Multitask AET with Orthogonal Tangent Regularity for Dark Object Detection, in Proceedings of IEEE/CVF Conferences on Computer Vision (ICCV 2021), Virtual, October 11 - October 17, 2021.  
  • Si Chen, Ruoxi Jia, Guo-Jun Qi, Mostafa Kahla. Knowledge-Enriched Distributional Model Inversion Attacks, in Proceedings of IEEE/CVF Conferences on Computer Vision (ICCV 2021), Virtual, October 11 - October 17, 2021.
  • Qianjiang Hu, Xiao Wang, Wei Hu, Guo-Jun Qi*. AdCo: Adversarial Contrast for Efficient Learning of Unsupervised Representations from Self-Trained Negative Adversaries, in Proceedings of IEEE/CVF Conferences on Computer Vision and Pattern Recognition (CVPR 2021), Virtual, June 19th - June 25th, 2021.
  • Xu Yang, Hanwang Zhang, Guo-Jun Qi, Jianfei Cai. Causal Attention, in Proceedings of IEEE/CVF Conferences on Computer Vision and Pattern Recognition (CVPR 2021), Virtual, June 19th - June 25th, 2021.
  • Tianyi Li, Guo-Jun Qi. Taxi Utilization Rate Maximization by Dynamic Demand Prediction: A Case Study in the Chicago, in Transportation Research Board (TRB) 2021 Annual Meeting, January 2021.
  • Feng Lin, Haohang Xu, Houqiang Li, Hongkai Xiong, Guo-Jun Qi. Auto-Encoding Transformations in Reparameterized Lie Groups for Unsupervised Learning, in Proceedings of AAAI Conference on Artificial Intelligence (AAAI), Vancouver, Canada, Feburary, 2021.
  • Xuesong Chen, Canmiao Fu, Feng Zheng, Yong Zhao, Hongsheng Li, Ping Luo, Guo-Jun Qi. A Unified Multi-Scenario Attacking Network for Visual Object Tracking, in Proceedings of AAAI Conference on Artificial Intelligence (AAAI), Vancouver, Canada, Feburary, 2021.
  • Liheng Zhang, Guo-Jun Qi. WCP: Worst-Case Perturbations for Semi-Supervised Deep Learning, in Proceedings of IEEE/CVF Conferences on Computer Vision and Pattern Recognition (CVPR 2020), Seattle, WA, June 14th - June 19th, 2020.
  • Xiang Gao, Wei Hu, Guo-Jun Qi. GraphTER: Unsupervised Learning of Graph Transformation Equivariant Representations via Auto-Encoding Node-wise Transformations, in Proceedings of IEEE/CVF Conferences on Computer Vision and Pattern Recognition (CVPR 2020), Seattle, WA, June 14th - June 19th, 2020.
  • Jiayu Wang, Wengang Zhou, Guo-Jun Qi, Zhongqian Fu, Qi Tian, Houqiang Li. Transformation GAN for Unsupervised Image Synthesis and Representation Learning,  in Proceedings of IEEE/CVF Conferences on Computer Vision and Pattern Recognition (CVPR 2020), Seattle, WA, June 14th - June 19th, 2020.
  • Qin Yang, Chenglin Li, Wenrui Dai, Junni Zou, Guo-Jun Qi, Hongkai Xiong. Rotation Equivariant Graph Convolutional Network for Spherical Image Classification, in Proceedings of IEEE/CVF Conferences on Computer Vision and Pattern Recognition (CVPR 2020), Seattle, WA, June 14th - June 19th, 2020. 
  • Yuhui Xu, Lingxi Xie, Xiaopeng Zhang, Xin Chen, Guo-Jun Qi, Qi Tian, Hongkai Xiong, PC-DARTS: Partial Channel Connections for Memory-Efficient Architecture Search, in Proceedings of International Conference on Learning Representations (ICLR 2020), Addis Ababa, Ethiopia, April 26 - 30, 2020.
  • Ning Wang, Wengang Zhou, Guo-Jun Qi, and Houqiang Li. POST: POlicy-based Switch Tracking, Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2020), New York, New York, February 7-12, 2020.
  • Guo-Jun Qi, Liheng Zhang, Chang Wen Chen, Qi Tian. AVT: Unsupervised Learning of Transformation Equivariant Representations by Autoencoding Variational Transformations, in Proceedings of International Conference in Computer Vision (ICCV 2019), Seoul, Kore, Oct. 27 – Nov. 2, 2019.
  • Zhimao Peng, Zechao Li, Junge Zhang, Yan Li, Guo-Jun Qi, Jinhui Tang. Few-Shot Image Recognition with Knowledge Transfer, in Proceedings of International Conference in Computer Vision (ICCV 2019), Seoul, Kore, Oct. 27 – Nov. 2, 2019.
  • Hao Hu, Liqiang Wang, Guo-Jun Qi. Learning to Adaptively Scale Recurrent Neural Networks, IN AAAI Conference on Artificial Intelligence (AAAI 2019), Honolulu, Hawaii, January 27-February 1, 2019.
  • Bin Wang, Guo-Jun Qi, Sheng Tang, Tianzhu Zhang, Yunchao Wei, Linghui Li, Yongdong Zhang. Boundary Perception Guidance: A Scribble-Supervised Semantic Segmentation Approach, International Joint Conference on Artificial Intelligence (IJCAI 2019), Macao, China, August 10-16, 2019.
  • Liheng Zhang§, Guo-Jun Qi*, Liqiang Wang, Jiebo Luo. AET vs. AED: Unsupervised Representation Learning by Auto-Encoding Transformations rather than Data,  in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2019), Long Beach, CA, June 16th - June 20th, 2019. [pdf]  
  • Muhammad Abdullah Jamal§, Guo-Jun Qi*. Task Agnostic Meta-Learning for Few-Shot Learning, in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2019), Long Beach, CA, June 16th - June 20th, 2019. [pdf]
  • Marzieh Edraki§, Guo-Jun Qi*. Generalized Loss-Sensitive Adversarial Learning with Manifold Margins, in Proceedings of European Conference on Computer Vision (ECCV 2018), Munich, Germany, September 8 – 14, 2018.  
  • Yiru Zhao§, Zhongming Jin, Guo-Jun Qi, Hongtao Lu and Xian-Sheng Hua. A Principled Approach to Hard Triplet Generation via Adversarial Nets, in Proceedings of European Conference on Computer Vision (ECCV 2018), Munich, Germany, September 8 – 14, 2018.  
  • Zhihang Fu§, Zhongming Jin, Guo-Jun Qi, Chen Shen, Rongxin Jiang, Yaowu Chen, Xian-Sheng Hua. Previewer for Multiple-Scale Object Detector, in Proceedings of ACM International Conference on Multimedia (ACM MM 2018), Seoul, Korea, October 22-26, 2018
  • Bin Wang§,  Guo-Jun Qi, Liheng Zhang§, Lixi Deng, Yongdong Zhang.  High sensitivity with tiny candidates for Pulmonary Nodule Detection, in Proceedings of International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2018), Granada, Spain, September 16-20, 2018.
  • Guo-Jun Qi, Liheng Zhang§, Hao Hu§, Marzieh Edraki§, Jingdong Wang, Xian-Sheng Hua.   Global versus Localized Generative Adversarial Nets, in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2018), Salt Lake City, Utah, June 18th - June 22nd, 2018. [pdf]
  • Guotian Xie, Jingdong Wang, Ting Zhang, Jian-Huang Lai, Richang Hong, Guo-Jun Qi. Interleaved Structured Sparse Convolutional Neural Networks, in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2018), Salt Lake City, Utah, June 18th - June 22nd, 2018.
  • Ting Zhang, Guo-Jun Qi, Bin Xiao, Jingdong Wang. Interleaved Group Convolutions for Deep Neural Networks, in Proceedings of International Conference on Computer Vision (ICCV 2017), Venice, Italy, October 22-29, 2017. [pdf]
  • Hao Hu§, Guo-Jun Qi*. State-Frequency Memory Recurrent Neural Networks, in Proceedings of International Conference on Machine Learning (ICML 2017), Sydney, Australia, August 6-11, 2017. 
  • Guo-Jun Qi, Jiliang Tang, Jingdong Wang, Jiebo Luo. Mixture Factorized Ornstein-Uhlenbeck Processes for Time-Series Forecasting, in Proceedings of ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2017), Halifax, Nova Scotia, Canada, August 13-17, 2017. 
  • Liheng Zhang§, Charu Aggarwal, Guo-Jun Qi*, Stock Price Prediction via Discovering Multi-Frequency Trading Patterns, in Proceedings of ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2017), Halifax, Nova Scotia, Canada, August 13-17, 2017.
  • Yilin  Wang,  Suhang  Wang,  Jiliang  Tang,  Guojun  Qi,  Huan  Liu  and  Baoxin  Li. CLARE:  A  Joint  Approach  to  Label  Classification  and  Tag  Recommendation, in AAAI Conference on Artificial Intelligence (AAAI 2017), San Francisco, California, CA, February 4-9, 2017.
  • Junjun Jiang, Yi Yu, Suhua Tang, Jiayi Ma, Guo-Jun Qi, Akiko Aizawa, Context-patch based face hallucination via thresholding locality-constrained representation and reproducing learning, in Proceedings of IEEE International Conference on Multimedia and Expo (ICME 2017), Hong Kong, China, 2017. (Finalist of the World’s First 10K Best Paper Award)
  • Guo-Jun Qi. Hierarchically Gated Deep Networks for Semantic Segmentation, in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2016), Las Vegas, Nevada, USA, June 26-July 1, 2015. (Oral Presentation, 3.9% acceptance rate)
  • Xiaojuan Wang, Ting Zhang, Guo-Jun Qi, Jinhui Tang and Jingdong Wang. Supervised Quantization for Similarity Search, in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2016), Las Vegas, Nevada, USA, June 26-July 1, 2016. 
  • Hao Hu§, Joey  Velez-Ginorio§, Guo-Jun Qi*. Temporal Order-based First-Take-All Hashing for Fast Attention-Deficit-Hyperactive-Disorder Detection, in Proceedings of ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2016), San Francisco, USA, August 13-17, 2016.
  • Xiaojuan Wang, Ting Zhang, Guo-Jun Qi, Jinhui Tang and Jingdong Wang. Supervised Quantization for Similarity Search, in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2016), Las Vegas, Nevada, USA, June 26-July 1, 20156
  • Vivek Veeriah§, Naifan Zhuang§, and Guo-Jun Qi*. Differential Recurrent Neural Networks for Action Recognition, in Proceedings of International Conference on Computer Vision (ICCV 2015), Santiago, Chile, December 13-16, 2015.
  • Guo-Jun Qi, Charu Aggarwal, Deepak Turaga, Daby Sow and Phil Anno, State-Driven Dynamic Sensor Selection and Prediction with State-Stacked Sparseness, in Proceedings of ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2015), Sydney, Australia, August 10-13, 2015. 
  • Vivek Veeriah§, Rohit Durvasula§, and Guo-Jun Qi*. Deep Learning Architecture with Dynamically Programmed Layers for Brain Connectome Prediction, in Proceedings of ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2015), Sydney, Australia, August 10-13, 2015.
  • Shiyu Chang§, Wei Han, Jiliang Tang, Guo-Jun Qi, Charu Aggarwal, and Thomas Huang. Heterogeneous Network Embedding via Deep Architectures, in Proceedings of ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2015), Sydney, Australia, August 10-13, 2015. 
  • Xiangbo Shu§, Guo-Jun Qi, Jinhui Tang, Jingdong Wang. Weakly-Shared Deep Transfer Networks for Heterogeneous-Domain Knowledge Propagation, in Proceedings of ACM International Conference on Multimedia (MM 2015), Brisbane, Australia, 26-30 Oct 2015. (Full Research Paper)
  •  Jun Ye§, Kai Li§, Guo-Jun Qi, Kien Hua. Temporal-Order Preserved Dynamic Quantization for Human Action Recognition from Multimodal Sensor Streams, in Proceedings of the Annual ACM International Conference on Multimedia Retrieval (ICMR 2015), June 23-26, Shanghai, China. (Full Paper)
  • Ting Zhang§, Guo-Jun Qi, Jingdong Wang, Sparse Composite Quantization, in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2015), Boston, Massachusetts, USA, June 7-12.
  • Shiyu Chang§, Guo-Jun Qi, Charu Aggarwal, Jiayu Zhou, Meng Wang and Thomas Huang. Factorized Similarity Learning in Networks, in Proceedings of International Conference on Data Mining (ICDM 2014), Shenzhen, China, December 14-17, 2014. (Best Student Paper)
  • Shiyu Chang§, Guo-Jun Qi, Jinhui Tang, Qi Tian, Yong Rui, Thomas S. Huang. Multimedia LEGO: Learning Structured Model by Probabilistic Logic Ontology Tree, in Proceeding of International Conference on Data Mining (ICDM 2013), Dallas, TX, USA, December 7-10, 2013.
  • Guo-Jun Qi, Charu Aggarwal, Jiawei Han, Thomas Huang. Mining Collective Intelligence in Groups, in Proc. of International World Wide Web conference (WWW 2013), Rio de Janeiro, Brazil, May 13th-17th, 2013. (Full Research Paper).
  • Guo-Jun Qi, Charu Aggarwal, and Thomas Huang. Link Prediction across Networks by Biased Cross-Network Sampling, in International Conference on Data Engineering (ICDE 2014), Brisbane, Australia, April 8-11, 2013. (The paper has been selected as one of the best papers by IEEE Transactions on Data and Knowledge Engineering)
  • Guo-Jun Qi, Charu Aggarwal and Thomas Huang.  Online Community Detection in Social Sensing, in ACM International Conference on Web Search and Data Mining (WSDM 2013), Rome, February 4-8, 2013.
  • Guo-Jun Qi, Charu Aggarwal, Thomas Huang. Community Detection with Edge Content in Social Media Networks, to appear in Proc. of IEEE International Conference on Data Engineering (ICDE 2012), Washington D.C., USA, April 1-5, 2012. (Full Paper).
  • Guo-Jun Qi, Yong Rui, Qi Tian, Charu Aggarwal, Shiyu Chang and Thomas Huang. Towards Cross-Category Knowledge Propagation for Learning Visual Concepts.  To appear in IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2011), Colorado Springs, Colorado, June 21-23, 2011.(Oral Presentation)
  • Guo-Jun Qi, Qi Tian, Thomas Huang. Locality-Sensitive Support Vector Machine by Exploring Local Correlation and Global Regularization. To appear in IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2011), Colorado Springs, Colorado, June 21-23, 2011.
  • Guo-Jun Qi, Charu Aggarwal and Thomas Huang, Towards Cross-Domain Knowledge Propagation from Text Corpus to Web Images, to appear in Proc. of International World Wide Web conference (WWW 2011), Hyderabad, India, March 28-April 1, 2011.(Full Paper)
  • Adam Lee, Marissa Passantino, Heng Ji, Guo-Jun Qi and Thomas Huang.  Enhancing Multi-lingual Information Extraction via Cross-Media Inference and Fusion, to apear in Proceedings of the 23rd International Conference on Computational Linguistics (COLING 2010), Beijing, August 23-27, 2010.
  • Guo-Jun Qi, Xian-Sheng Hua, Hong-Jiang Zhang.  Learning Distance from Community-Tagged Media Collection, to appear in International ACM Conference on Multimedia (ACM MM 2009), Beijing, China, October 19-24, 2009. (Full Paper)
  • Jinhui Tang, Shuicheng Yan, Richang Hong, Guo-Jun Qi, Tat-Seng Chua.  Inferring Semantic Concepts from Community-Contributed Images and Noisy Tags, to appear in International ACM Conference on Multimedia (ACM MM 2009), Beijing, China, October 19-24, 2009.
  • Guo-Jun Qi, Jinhui Tang, Tat-Seng Chua, Hong-Jiang Zhang, An Efficient Sparse Metric Learning in High-Dimensional Space via $\ell_1$-Penalized Log-Determinant Regularization, in International Conference on Machine Learning (ICML 2009), Montreal, Quebec, June 14-18, 2009.
  • Guo-Jun Qi, Xian-Sheng Hua, Yong Rui, Jinhui Tang, Hong-Jiang Zhang.Two Dimensional Active Learning for Image Classification, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2008), Anchorage, Alaska, June 24-26, 2008. [pdf]
  • Xian-Sheng Hua, Guo-Jun Qi.Online Multi-Label Active Annotation: Towards Large-Scale Content-Based Video Search, in International ACM Conference on Multimedia 2008 (ACM MM 2008), Vancouver, Canada, October 27 - November 1. (Full Paper, accept rate 17%)
  • Jinhui Tang, Haojie Li, Guo-Jun Qi and Tat-Seng Chua. Integrated Graph-based Semi-supervised Multiple/Single Instance Learning Framework for Image Annotation, in International ACM Conference on Multimedia 2008 (ACM MM 2008), Vancouver, Canada, October 27 - November 1. (Short Paper)
  • Guo-Jun Qi, Xian-Sheng Hua, Yong Rui, Jinhui Tang, Zheng-Jun Zha, Hong-Jiang Zhang.A Joint Appearance-Spatial Distance for Kernel-Based Image Categorization,in IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2008), Anchorage, Alaska, June 24-26, 2008. [[pdf]
  • Zhengjun Zha, Xian-Sheng Hua, Tao Mei, Jingdong Wang, Guo-Jun Qi, and Zengfu Wang. Joint Multi-Label Multi-Instance Learning for Image Classification, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2008), Anchorage, Alaska, June 24-26, 2008.
  • Yuan Liu, Tao Mei, Guo-Jun Qi, Xiuqing Wu, Xian-Sheng Hua.  Query-Independent Learning For Video Search, in IEEE International Conference on Multimedia and Expo (ICME 2008), Hannover, Germany, June 23-26, 2008.
  • Guo-Jun Qi, Xian-Sheng Hua, Yong Rui, Jinhui Tang, Tao Mei, Hong-Jiang Zhang.Correlative Multi-Label Video Annotation, in ACM Multimedia 2007 (ACM MM 2007), Augsburg, Germany, Sep. 23-29. (Full Paper, accept rate: 17%). Best Paper Award pdf
  • Jinhui Tang, Xian-Sheng Hua, Guo-Jun Qi, Meng Wang, Tao Mei, Xiuqing Wu.  Structure-Sensitive Manifold Ranking for Video Concept Detection, in ACM Multimedia 2007 (ACM MM 2007), Augsburg, Germany, Sep. 23-29. (Full Paper, accept rate: 17%) .
  • Jinhui Tang, Xian-Sheng Hua, Guo-Jun Qi, Xiuqing Wu. Typicality Ranking via Semi-Supervised Multiple-Instance Learning, in Proc. ACM Multimedia (ACM MM 2007), Augsburg, Germany, Sep. 23-29. (Short paper) 
  • Zheng-Jun Zha, Tao Mei, Xian-Sheng Hua, Guo-Jun Qi, Zengfu Wang. Refining video annotation by exploiting pairwise concurrent relation, in Proc. of ACM Multimedia 2007 (ACM MM 2007), Augsburg, Germany, Sep. 23-29. (Short Paper)
  • Jinhui Tang, Xian-Sheng Hua, Tao Mei, Guo-Jun Qi, Shipeng Li, Xiuqing Wu. Temporally Consistent Gaussian Random Field For Video Semantic Analysis, in IEEE International Conference on Image Processing (ICIP 2007), San Antonio, Texas, USA, September, 2007. 
  • Yong Rui, Guo-Jun Qi. Learning Concepts by Modeling Relationships. in International Workshop on Multimedia Content Analysis and Mining (MCAM 2007), Weihai, China. [pdf]
  • Guo-Jun Qi, Xian-Sheng Hua, Yan Song, Jinhui Tang, Hong-Jiang Zhang. Transductive Inference with Hierarchical Clustering for Video Annotation, in IEEE Conference on IEEE International Conference on Multimedia and Expo (ICME 2007). Beijing, China. July 2-5, 2007. (Oral) [pdf]
  • Jinhui Tang, Xian-Sheng Hua, Guo-Jun Qi, Zhiwei Gu, Xiuqing Wu. Beyond Accuracy: Typicality Ranking for Video Annotation, in IEEE Conference on IEEE International Conference on Multimedia and Expo (ICME 2007). Beijing, China. July 2-5, 2007. (Oral) [pdf][download dataset]
  • Xun Yuan, Xian-Sheng Hua, Meng Wang, Guo-Jun Qi, Xiuqing Wu. A Novel Multiple Instance Learning Approach For Image Retrieval Based on Adaboost Feature Selection, in IEEE Conference on IEEE International Conference on Multimedia and Expo (ICME 2007). Beijing, China. July 2-5, 2007.
  • Yan SONG, Xian-Sheng HUA, Guo-Jun QI, Li-Rong DAI, Meng WANG, Hong-Jiang ZHANG. Efficient Semantic Annotation Method for Indexing Large Personal Video Database, in Workshop on Multimedia Information Retrieval 2006 (MIR 2006 - ACM MM 2006 Workshop). (Oral)
  • Yan Song, Guo-Jun QI, Xian-Sheng HUA, Li-Rong DAI, Ren-Hua WANG. Video Annotation by Active Learning and Semi-Supervised Ensembling. In IEEE International Conference on Multimedia and Expo (ICME 2006). Toronto, Canada. July 9-12, 2006.
  • Guo-Jun Qi. Information Trust, Inference and Transfer in Social and Information Networks, Ph.D. Dissertation, University of Illinois at Urbana-Champaign, 2013.

§ The students I advised when preparing the papers. 
* Corresponding author.

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Last updated 12/17/14