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SELECTED PUBLICATIONS Selected Publications [
Full
Publication List ] 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. Refereed Journal papers Liangxi Liu , Xi Jiang , Feng Zheng , Hong Chen , Guo-Jun Qi
, Heng Huang , Ling Shao. A Bayesian Federated Learning Framework with
Online Laplace Approximation, in Transactions on Pattern Analysis and
Machine Intelligence (T-PAMI), October, 2023. [pdf] Ying Wang, Ziwei Xuan, Chiuman Ho, Guo-Jun Qi. Adversarial Dense Contrastive Learning for Semi-Supervised Semantic Segmentation, in IEEE Transactions on Image Process (T-IP), Volume 32, page 4459-4471, 2023. Weiyao Lin, Huabin Liu, Shizhan Liu, Yuxi Li, Hongkai Xiong, Guo-Jun Qi, Nicu Sebe. HiEve: A Large-Scale Benchmark for Human-Centric Video Analysis in Complex Events, in International Journal of Computer Vision (IJCV), Volume 131, Number 1, Janaury 2023. 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. [pdf] Xiao Wang, Guo-Jun Qi. Contrastive Learning with Stronger Augmentations, in IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), August, 2022. [pdf] 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. [pdf] 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. [pdf] 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. [pdf] 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. [pdf] 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 [pdf]. 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 (T-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. [pdf] 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. [pdf] 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. Guo-Jun Qi. Loss-Sensitive Generative Adversarial Networks on Lipschitz Densities, to appear in International Journal of Computer Vision (IJCV), 2019. [pdf] Xiangbo Shu, Jinhui Tang, Guo-Jun Qi, Wei Liu, Jian Yang. Hierarchical Long Short-Term Concurrent Memory for Human Interaction Recognition, in IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2019. [pdf] 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. [pdf] Xiangbo Shu, Jinhui Tang, Guo-Jun Qi, Zechao Li, Yu-Gang Jiang, Shuicheng Yan. Image Classification with Tailored Fine-Grained Dictionaries, in IEEE Transactions on Circuits and Systems for Video Technology (CSVT), Volume 28, Number 2, page 454-467, 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. 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. 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. Jun Ye§, Hao Hu§, Guo-Jun Qi*, Kien Hua. A Temporal Order Modeling Approach to Human Action Recognition from Multimodal Sensor Data, in ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), Volume 13 Issue 2, Article No. 14, May 2017. [pdf] Kai Li§, Guo-Jun Qi*, Jun Ye, Kien Hua. Linear Subspace Ranking Hashing for Cross-modal Retrieval, in IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), Volume 39, Issue 9, September 2016. [pdf] [code] Guo-Jun Qi, Wei Liu, Charu Aggarwal, and Thomas Huang. Joint Intermodal and Intramodal Label Transfers for Extremely Rare or Unseen Classes, in IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), Volume 39, Issue 7, July 2016. [pdf] 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, in IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), Vol. 39, No. 8, pp. 1662 - 1674, August 2017. [pdf] Guo-Jun Qi, Charu Aggarwal, and Thomas Huang. Breaking the Barrier to Transferring Link Information across Networks, "the issue of the best ICDE 2013 papers" in IEEE Transactions on Knowledge and Data Engineering (T-KDE), Volume 27, Issue 7, pp. 1741 - 1753, July 2015. [pdf] 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. Guo-Jun Qi, Min-Hsuan Tsai, Shen-Fu Tsai,
Liangliang Cao, Thomas Huang. Web-Scale Multimedia Information
Networks, in Proceedings
of the IEEE (P
IEEE), Volume 100, Issue 9,
2012. Guo-Jun Qi, Charu Aggarwal, Qi Tian, Ji Heng,
Thomas Huang. Exploring Context and Content Links in Social Media: A
Latent Space Method, in
IEEE Transactions on Pattern Analysis and
Machine Intelligence (T-PAMI), Volume 34, Issue 5, May 2012. [pdf] Guo-Jun Qi, Xian-Sheng Hua, Yong Rui, Jinhui Tang, Hong-Jiang Zhang. Image Classification with Kernelized Spatial-Context, in IEEE Transactions on Multimedia (T-MM), Issue 4, Volume 12, page 278-287, June 2010. [pdf] 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 (CSVT),
vol. 19, no. 5, 2009. Guo-Jun Qi, Xian-Sheng Hua, Yong Rui, Jinhui
Tang, Hong-Jiang Zhang.
Two-Dimensional
Multi-Label Active Learning with An Efficient Online Adaptation Model
for Image Classification, in IEEE Transactions on Pattern Analysis and
Machine Intelligence (T-PAMI),vol.31,no.10,
2009.[pdf] [code]
Guo-Jun Qi, Xian-Sheng Hua, Yong Rui, Jinhui
Tang, Tao Mei, Meng Wang and Hong-Jiang Zhang. Correlative Multi-Label
Video Annotation with Temporal Kernels, in ACM Transactions on
Multimedia Computing, Communications, and Applications (TOMCCAP), Vol.
5, No. 1, 2008. [pdf] 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), Dec 9 - Dec 15, Vancouver, Canada, 2024.[pdf][github] 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.[pdf] [github] 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. [pdf] 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. [pdf] [github] 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. [pdf] [github] 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. [pdf] Xianpeng Liu, Ce Zheng, Kelvin B Cheng, Nan Xue, Guo-Jun Qi, Tianfu Wu. Monocular 3D Object Detection with Bounding Box Denoising in 3D by Perceiver, in Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV 2023), page 1813-1822, 2023. [pdf] Benzhi Wang, Yang Yang, Jinlin Wu, Guo-jun Qi, Zhen Lei. Self-similarity Driven Scale-invariant Learning for Weakly Supervised Person Search, in Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV 2023), page 1813-1822, 2023. [pdf] Yuelang Xu, Hongwen Zhang, Lizhen Wang, Xiaochen Zhao, Han Huang, Guo-Jun Qi, Yebin Liu. LatentAvatar: Learning Latent Expression Code for Expressive Neural Head Avatar, in ACM SIGGRAPH 2023 Conference Proceedings, SIGGRAPH 2023, Los Angeles, CA, USA, August 6-10, 2023. [pdf] 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. [pdf] 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. [pdf] 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. 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. 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, Mostafa Kahla, Ruoxi Jia, Guo-Jun Qi*. 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 for Vision-Language Tasks, 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. Ning Wang, Wengang Zhou, Guo-Jun Qi, Houqiang Li. POST: POlicy-Based Switch Tracking, in Proceedings of The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2020), New York, NY, Febuary 7-12, 2020. 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. (Oral) [pdf] 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. [pdf] 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. [pdf] 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. [pdf] 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. [pdf] 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. (Oral) [pdf] 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] Liheng Zhang§, Marzieh Edraki§, Guo-Jun Qi*. CapProNet: Deep Feature Learning via Orthogonal Projections onto Capsule Subspaces, in Proccedings of Thirty-second Conference on Neural Information Processing Systems (NeurIPS 2018), Palais des Congrès de Montréal, Montréal, Canda, December 3-8, 2018. [pdf] [code] 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. [pdf][code: torch, blocks] 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. 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 and 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] [code 1: generation, code 2: semi-supervised learning] 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. [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. [pdf] [code] 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] 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. [pdf] 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. [pdf] [code] Yilin Wang, Suhang Wang, Jiliang Tang, Guo-Jun Qi, Huan Liu, Baoxin Li. CLARE: A Joint Approach to Label Classification and Tag Recommendation. in Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI 2017), San Francisco, California, USA, , 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, 2016. (Oral Presentation, 3.9% acceptance rate) [pdf] 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. [pdf] 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. [pdf] 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. [pdf] 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. [pdf] 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. [pdf] 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. [pdf] 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) [pdf] Ting Zhang§, Guo-Jun Qi, Jinhui Tang, Jingdong Wang. Sparse Composite Quantization, in Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2015), Boston, MA, June 7-12, 2015. [pdf] Jun Ye§, Kai Li§, Guo-Jun Qi, Kien Hua. Temporal-Order Preserving Dynamic Quantization for Human Action Recognition from Multimodal Sensor Streams (ICMR 2015), Shanghai, China, June 23-26, 2015 (full paper). [pdf] (On UTKinect-Action dataset, our best approach has achived 100% accuracy) Shiyu
Chang§, Guo-Jun
Qi,
Charu Aggarwal, Jiayu Zhou, Meng Wang, Thomas S. Huang.
Factorized Similarity Learning in Networks, in Proc. Of IEEE
International Conference on Data Mining (ICDM 2014),
Shenzhen, China, 2014. [pdf] (Best
Student Paper) Guo-Jun Qi, Charu Aggarwal, Jiawei Han, Thomas
Huang. Mining Collective Intelligence in Diverse Groups, to appear in
Proc. of International World Wide Web conference (WWW 2013), Rio de
Janeiro, Brazil, May 13th-17th, 2013. [pdf]
(Full Research Paper) Guo-Jun Qi, Charu Aggarwal, Thomas Huang.
Link Prediction across Networks by Biased Cross-Network Sampling, in
International Conference on Data Engineering (ICDE 2013),
Brisbane,
Australia, April 8-11, 2013. [pdf]
(Full Paper) ("Best ICDE 2013 Paper" by IEEE
Transactions on Knowledge and Data Engineering) Guo-Jun Qi, Charu Aggarwal, Thomas Huang.
Online Community Detection in Social Sensing, in ACM International
Conference on Web Search and Data Mining (WSDM 2013), Rome,
Italy,
February 4-8, 2013. [pdf] Guo-Jun Qi, Charu Aggarwal, Thomas Huang.
Transfer Learning of Distance Metrics by Cross-Domain Metric Sampling
across Heterogeneous Spaces, in SIAM International Conference on Data
Mining (SDM 2012),
Anaheim, California, USA, April 26-28, 2012.
(Full Paper) Guo-Jun Qi, Charu Aggarwal, Thomas Huang. On
Clustering Heterogeneous Social Media Objects with Outlier Links, in
the fifth ACM International Conference on Web Search and Data Mining (WSDM 2012),
Seattle, Washington, February 8-12, 2012. Guo-Jun Qi, Charu Aggarwal, Thomas Huang.
Community Detection with Edge Content in Social Media Networks, in
Proc. of IEEE International Conference on Data Engineering (ICDE 2012),
Washington D.C., USA, April 1-5, 2012. (Full
Paper) Guo-Jun Qi, Charu Aggarwal and Thomas Huang,
Towards Semantic Knowledge Propagation from Text Corpus to Web Images, in Proc. of
International World Wide Web conference (WWW 2011),
Hyderabad, India,
March 28-April 1, 2011. (Full Regular Paper)
[pdf] [code] Guo-Jun Qi, Charu Aggarwal, Yong Rui, Qi
Tian, Shiyu Chang and Thomas Huang. Towards Cross-Category Knowledge
Propagation for Learning Visual Concepts, in Proc. of IEEE Conference on Computer Vision
and Pattern Recognition (CVPR
2011), Colorado Springs, Colorado, June
21-23, 2011.(Oral) [pdf] [code] Guo-Jun Qi, Qi Tian, Thomas Huang.
Locality-Sensitive Support Vector Machine by Exploring Local
Correlation and Global Regularization, in Proc. of IEEE Conference on Computer Vision
and Pattern Recognition (CVPR
2011), Colorado Springs, Colorado, June
21-23, 2011. [pdf] [code]
Guo-Jun Qi, Jinhui Tang, Zheng-Jun Zha,
Tat-Seng Chua, Hong-Jiang Zhang, An Efficient Sparse Metric Learning in
High-Dimensional Space via $\ell_1$-Penalized Log-Determinant
Regularization, in Proc. of International Conference on Machine
Learning (ICML 2009),
Montreal, Quebec, June 14-18, 2009.[pdf] Guo-Jun Qi, Xian-Sheng Hua, Hong-Jiang Zhang.
Learning Semantic Distance from Community-Tagged Media Collection, in
Proc. of International ACM Conference on Multimedia (ACM MM 2009),
Beijing, China, October 19-24, 2009.(Full Paper, Oral Presentation) [pdf] 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, 2008. (Full
Paper, Oral Presentation) 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] 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, 2007. (Full Paper, Oral
Presentation). Best
Paper Award [pdf] Guo-Jun Qi, Xian-Sheng Hua, Yong Rui, Tao Mei, Jinhui Tang, Hong-Jiang Zhang. Concurrent Multiple Instance Learning for Image Categorization, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2007), Minneapolis, Minnesota, June, 2007. [pdf] Book Chapters
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