Please also see my publications at Google Scholar.

1. Zheng Ding, Mengqi Zhang, Jiajun Wu, Zhuowen Tu, "Patched Denoising Diffusion Models For High-Resolution Image Synthesis", arXiv:2308.01316, 2023.
2. Wenbo Hu, Yifan Xu, Yi Li, Weiyue Li, Zeyuan Chen, Zhuowen Tu, "BLIVA: A Simple Multimodal LLM for Better Handling of Text-Rich Visual Questions", arXiv:2308.09936, 2023.
3. Tyler A. Chang, Zhuowen Tu, Benjamin K. Bergen, "Characterizing Learning Curves During Language Model Pre-Training: Learning, Forgetting, and Stability", arXiv:2308.15419, 2023.
   
4. Zheng Ding, James Hou, and Zhuowen Tu, "Point Cloud Recognition with Position-to-Structure Attention Transformers", arXiv:2210.02030, 2022.
   
5. Yue Zhao, Yantao Shen, Yuanjun Xiong, Shuo Yang, Wei Xia, Zhuowen Tu, Bernt Schiele, and Stefano Soatto, "ELODI: Ensemble Logit Difference Inhibition for Positive-Congruent Training", arXiv:2205.06265, 2022.
6. Pengkai Zhu*, Zhaowei Cai*, Yuanjun Xiong*, Zhuowen Tu*, Luis Goncalves, Vijay Mahadevan, and Stefano Soatto, "Contrastive Neighborhood Alignment", arXiv:2201.01922, 2022. (*equal contribution)
7. Sainan Liu, Vincent Nguyen, Yuan Gao, Subarna Tripathi, and Zhuowen Tu, "Towards Panoptic 3D Parsing for Single Image in the Wild", arXiv:2111.03039, 2021.
   
8. Yifan Xu, Kening Zhang, Haoyu Dong, Yuezhou Sun, Wenlong Zhao, and Zhuowen Tu, "Rethinking Exposure Bias in Language Modeling", arXiv:1910.11235, 2019.
9. Yifan Xu, Lu Dai, Udaikaran Singh, Kening Zhang, and Zhuowen Tu, "Neural Program Synthesis by Self-Learning", arXiv:1910.05865, 2019.
10. Long Jin, Zeyu Chen, and Zhuowen Tu, "Object Detection Free Instance Segmentation With Labeling Transformations", arXiv:1611.08991, 2016.
    

		Uni-3D: A Universal Model for Panoptic 3D Scene Reconstruction Xiang Zhang*, Zeyuan Chen*, Fangyin Wei, and Zhuowen Tu (*equal contribution) ICCV 2023 / Paper
		MasQCLIP for Open-Vocabulary Universal Image Segmentation Xin Xu*, Tianyi Xiong*, Zheng Ding, and Zhuowen Tu (*equal contribution) ICCV 2023 / Paper
		Single-Stage Diffusion NeRF: A Unified Approach to 3D Generation and Reconstruction Hansheng Chen, Jiatao Gu, Anpei Chen, Wei Tian, Zhuowen Tu, Lingjie Liu, Hao Su ICCV 2023 / Paper
		Distilling Large Vision-Language Model with Out-of-Distribution Generalizability Xuanlin Li, Yunhao Fang, Minghua Liu, Zhan Ling, Zhuowen Tu, Hao Su ICCV 2023 / Paper
		DocTr: Document Transformer for Structured Information Extraction in Documents Haofu Liao, Aruni RoyChowdhury, Weijian Li, Ankan Bansal, Yuting Zhang, Zhuowen Tu, Ravi Kumar Satzoda, R Manmatha, Vijay Mahadevan ICCV 2023 / Paper
		Object-centric Multiple Object Tracking Zixu Zhao, Jiaze Wang, Max Horn, Yizhuo Ding, Tong He, Zechen Bai, Dominik Zietlow, Carl-Johann Simon-Gabriel, Bing Shuai, Zhuowen Tu, Thomas Brox, Bernt Schiele, Yanwei Fu, Francesco Locatello, Zheng Zhang, Tianjun Xiao ICCV 2023 / Paper
		SkeleTR: Towards Skeleton-based Action Recognition in the Wild Haodong Duan, Mingze Xu, Bing Shuai, Davide Modolo, Zhuowen Tu, Joseph Tighe, Alessandro Bergamo ICCV 2023 / Paper
		Open-Vocabulary Universal Image Segmentation with MaskCLIP Zheng Ding, Jieke Wang, and Zhuowen Tu ICML 2023 / Paper
		DiffusionRig: Learning Personalized Priors for Facial Appearance Editing Zheng Ding, Xuaner Zhang, Zhihao Xia, Lars Jebe, Zhuowen Tu, and Xiuming Zhang CVPR 2023 / Paper
		Guided Recommendation for Model Fine-Tuning Hao Li, Charless Fowlkes, Hao Yang, Onkar Debeer, Zhuowen Tu, and Stefano Soatto CVPR 2023 / Paper
		On the Feasibility of Cross-Task Transfer with Model-Based Reinforcement Learning Yifan Xu*, Nicklas Hansen*, Zirui Wang, Yung-Chieh Chan, Hao Su, and Zhuowen Tu (*equal contribution) ICLR 2023 / Paper

		Semi-supervised Vision Transformers at Scale Zhaowei Cai, Avinash Ravichandran, Paolo Favaro, Manchen Wang, Davide Modolo, Rahul Bhotika, Zhuowen Tu, and Stefano Soatto NeurIPS 2022 / Paper
		An In-depth Study of Stochastic Backpropagation Jun Fang, Mingze Xu, Hao Chen, Bing Shuai, Zhuowen Tu, and Joseph Tighe NeurIPS 2022 / Paper
		The Geometry of Multilingual Language Model Representations Tyler A. Chang, Zhuowen Tu, and Benjamin K. Bergen EMNLP 2022 / Paper
		X-DETR: A Versatile Architecture for Instance-wise Vision-Language Tasks Zhaowei Cai, Gukyeong Kwon, Avinash Ravichandran, Erhan Bas, Zhuowen Tu, Rahul Bhotika, and Stefano Soatta ECCV 2022 / Paper

		Text Spotting Transformers Xiang Zhang, Yongwen Su, Subarna Tripathi, and Zhuowen Tu CVPR 2022 / Paper / Code
		Instance Segmentation with Mask-supervised Polygonal Regression Transformers Justin Lazarow, Weijian Xu, and Zhuowen Tu CVPR 2022 / Paper / Code
		MeMOT: Multi-Object Tracking with Memory Jiarui Cai, Wei Li, Mingze Xu, Yuanjun Xiong, Wei Xia, Zhuowen Tu, and Stefano Soatto CVPR 2022 / Paper Oral Presentation
		ViTGAN: Training GANs with Vision Transformers Kwonjoon Lee, Huiwen Chang, Lu Jiang, Han Zhang, Zhuowen Tu, and Ce Liu ICLR 2022 / Paper / Code Spotlight

		Long Short-Term Transformer for Online Action Detection Mingze Xu, Yuanjun Xiong, Hao Chen, Xinyu Li, Wei Xia, Zhuowen Tu, Stefano Soatto NeurIPS 2021 / Paper / Code Spotlight
		Co-Scale Conv-Attentional Image Transformers Weijian Xu*, Yifan Xu*, Tyler A. Chang, and Zhuowen Tu (*equal contribution) ICCV 2021 / Paper / Code Oral Presentation
		Visual Relationship Detection Using Part-and-Sum Transformers with Composite Queries Qi Dong, Zhuowen Tu, Haofu Liao, Yuting Zhang, Vijay Mahadevan, Stefano Soatto ICCV 2021 / Paper
		Convolutions and Self-Attention: Re-interpreting Relative Positions in Pre-trained Language Models Tyler A. Chang, Yifan Xu, Weijian Xu, and Zhuowen Tu ACL 2021 / Paper (long) / Code
		Line Segment Detection Using Transformers without Edges Yifan Xu*, Weijian Xu*, David Cheung, and Zhuowen Tu (*equal contribution) CVPR 2021 / Paper / Code Oral Presentation
		Dual Contradistinctive Generative Autoencoder Gaurav Parmar*, Dacheng Li*, Kwonjoon Lee*, and Zhuowen Tu (*equal contribution) CVPR 2021 / Paper / Code
		Pose Recognition with Cascade Transformers Ke Li*, Shijie Wang*, Xiang Zhang*, Yifan Xu, Weijian Xu, and Zhuowen Tu (*equal contribution) CVPR 2021 / Paper / Code
		Exponential Moving Average Normalization for Self-supervised and Semi-supervised Learning Zhaowei Cai, Avinash Ravichandran, Subhransu Maji, Charless Fowlkes, Zhuowen Tu, and Stefano Soatto CVPR 2021 / Paper Oral Presentation
		Compatibility-aware Heterogeneous Visual Search Rahul Duggal, Hao Zhou, Shuo Yang, Yuanjun Xiong, Wei Xia, Zhuowen Tu, and Stefano Soatto CVPR 2021 / Paper
		Attentional Constellation Nets for Few-Shot Learning Weijian Xu*, Yifan Xu*, Huaijin Wang*, and Zhuowen Tu (*equal contribution) ICLR 2021 / Paper

		One-Pixel Signature: Characterizing CNN Models for Backdoor Detection Shanjiaoyang Huang*, Weiqi Peng*, Zhiwei Jia, and Zhuowen Tu (*equal contribution) ECCV 2020 / Paper
		Recognizing Objects from Any View with Object and Viewer-Centered Representations Sainan Liu, Vincent Nguyen, Isaac Rehg, and Zhuowen Tu CVPR 2020 / Paper
		Learning Instance Occlusion for Panoptic Segmentation Justin Lazarow*, Kwonjoon Lee*, Kunyu Shi*, and Zhuowen Tu (*equal contribution) CVPR 2020 / Paper / Code
		Guided Variational Autoencoder for Disentanglement Learning Zheng Ding*, Yifan Xu*, Weijian Xu, Gaurav Parmar, Yang Yang, Max Welling, and Zhuowen Tu (*equal contribution) CVPR 2020 / Paper
		Topology-Aware Single-Image 3D Shape Reconstruction Qimin Chen, Vincent Nguyen, Feng Han, Raimondas Kiveris, and Zhuowen Tu CVPR 2020 Workshop on Learning 3D Generative Models / Paper
		Local Binary Pattern Networks Jeng-Hau Lin, Justin Lazarow, Yunfan Yang, Dezhi Hong, Rajesh Gupta, and Zhuowen Tu WACV 2020 / Paper

		Learning Geometry-aware Skeleton Detection Weijian Xu, Gaurav Parmar, and Zhuowen Tu BMVC 2019 / Paper
		3D Volumetric Modeling with Introspective Neural Networks Wenlong Huang*, Brian Lai*, Weijian Xu, and Zhuowen Tu (*equal contribution) AAAI 2019 / Paper
		Accelerating Local Binary Pattern Networks with Software-Programmable FPGAs Jeng-Hau Lin, Atieh Lotfi, Vahideh Akhlaghi, Zhuowen Tu, and Rajesh Gupta Desgin, Automation and Test in Europe (DATE) 2019 / Paper

		Rethinking Spatiotemporal Feature Learning: Speed-Accuracy Trade-offs in Video Classification Saining Xie, Chen Sun, Jonathan Huang, Zhuowen Tu, and Kevin Murphy ECCV 2018 / Paper
		Wasserstein Introspective Neural Networks Kwonjoon Lee, Weijian Xu, Fan Fan, and Zhuowen Tu CVPR 2018 / Paper / Code Oral Presentation
		Attentional ShapeContextNet for Point Cloud Recognition Saining Xie*, Sainan Liu*, Zeyu Chen, and Zhuowen Tu (*equal contribution) CVPR 2018 / Paper / Code
		Deep Convolutional Neural Networks with Merge-and-Run Mappings Liming Zhao, Mingjie Li, Depu Meng, Xi Li, Zhaoxiang Zhang, Yueting Zhuang, Zhuowen Tu, and Jingdong Wang IJCAI 2018 / Pape r / Code

		Introspective Classification with Convolutional Nets Long Jin, Justin Lazarow, and Zhuowen Tu NeurIPS 2017 / Paper / Code
		Introspective Neural Networks for Generative Modeling Justin Lazarow*, Long Jin*, and Zhuowen Tu (*equal contribution) ICCV 2017 / Paper / Code
		Aggregated Residual Transformations for Deep Neural Networks Saining Xie, Ross Girshick, Piotr Dollár, Zhuowen Tu, and Kaiming He CVPR 2017 / Paper / Code
		Deeply Supervised Salient Object Detection with Short Connections Qibin Hou, Ming-Ming Cheng, Xiao-Wei Hu, Ali Borji, Zhuowen Tu, and Philip Torr CVPR 2017 / Paper / Code

		Top-down Learning for Structured Labeling with Convolutional Pseudoprior Saining Xie*, Xun Huang*, and Zhuowen Tu (*equal contribution) ECCV 2016 / Paper
		HFS: Hierarchical Feature Selection for Efficient Image Segmentation Ming-Ming Cheng, Yun  Liu, Qibin Hou, Jiawang  Bian, Philip Torr, Shimin Hu, and Zhuowen Tu ECCV 2016 / Paper / Code
		Dense Volume-to-Volume Vascular Boundary Detection Jameson Merkow, David Kriegman, Alison Marsden, and Zhuowen Tu MICCAI 2016 / Paper
		Generalizing Pooling Functions in Convolutional Neural Networks: Mixed, Gated, and Tree Chen-Yu Lee, Patrick Gallagher, and Zhuowen Tu AISTATS 2016 / Paper / Code

		Holistically-Nested Edge Detection Saining Xie and Zhuowen Tu ICCV 2015 / Paper / Code / IJCV Version Marr Prize Honorable Mention
		Deeply-Supervised Nets                                                              Chen-Yu Lee*, Saining Xie*, Patrick Gallagher, Zhengyou Zhang, and Zhuowen Tu (*equal contribution) AISTATS 2015 / Paper / Code / arXiv Oral Presentation at the NeurIPS'14 Deep Learning Workshop
		Structural Edge Detection for Cardiovascular Modeling Jameson Merkow, Zhuowen Tu, David Kriegman, Alison Marsden MICCAI 2016 / Paper

• Jiajun Wu, Yining Wang, Zhulin Li, and Zhuowen Tu, "Harvesting Motion Patterns in Still Images from the Internet", CogSci 2014. (pdf)
  
• Wei Bi, Liwei Wang, James Kwok, and Zhuowen Tu, "Learning to Predict from Crowdsourced Data", UAI 2014. (pdf)
• Jiajun Wu, Jun-Yan Zhu, and Zhuowen Tu, "Reverse Image Segmentation: A High-Level Solution to a Low-Level Task", BMVC 2014 (pdf).
  

• Bo Wang and Zhuowen Tu, and John Tsotsos, "Dynamic Label Propagation for Semi-supervised Multi-class Multi-label Classification", ICCV 2013. (pdf)
  
• Jun Zhu, Baoyuan Wang, Xiaokang Yang, Wenjun Zhang, and Zhuowen Tu, "Action Recognition with Actons", ICCV 2013. (pdf)
  
• Xinggang Wang, Baoyuan Wang, Xiang Bai, Wenyu Liu, and Zhuowen Tu, "Max-Margin Multiple Instance Dictionary Learning", International Conference on Machine Learning (ICML), Atlanta, June, 2013. (pdf) (code)
  
• Quannan Li, Jingdong Wang, David Wipf, and Zhuowen Tu, "Fixed-Point Model for Structured Labeling", International Conference on Machine Learning (ICML), Atlanta, June, 2013. (pdf) (matlab source code)
• Quannan Li, Jiajun Wu, and Zhuowen Tu, "Harvesting Mid-level Visual Concepts from Large-scale Internet Images", CVPR 2013 (pdf) (project page).
  
• Jiayi Ma, Ji Zhao, Jinwen Tian, Zhuowen Tu, and Alan Yuille, "Robust Estimation of Nonrigid Transformation for Point Set Registration", CVPR 2013 (pdf).
• Bo Wang and Zhuowen Tu, "Sparse Subspace Denoising for Image Manifolds", CVPR 2013. (pdf)
  

• Yan Xu, Jianwen Zhang, Eric Chang, Maode Lai, and Zhuowen Tu, "Contexts-Constrained Multiple Instance Learning for Histopathology Image Segmentation", MICCAI 2012. (pdf)
  
• Liwei Wang, Xiong Li, Zhuowen Tu, and Jiaya Jia, "Discriminative Clustering via Generative Feature Mapping", AAAI 2012. (pdf)
  
• Bo Wang and Zhuowen Tu, "Affinity Learning via Self-diffusion for Image Segmentation and Clustering", CVPR 2012. (pdf)
  
• Bo Wang, Jiayan Jiang, Wei Wang, Zhi-Hua Zhou, and Zhuowen Tu, "Unsupervised Metric Fusion by Cross Diffusion", CVPR 2012. (pdf)
  
• Jun-Yan Zhu, Jiajun Wu, Yichen Wei, Eric Chang, and Zhuowen Tu, "Unsupervised Object Class Discovery via Saliency-Guided Multiple Class Learning", CVPR 2012. (pdf) (project page)
  
• Yan Xu*, Jun-Yan Zhu*, Eric Chang, and Zhuowen Tu, "Multiple Clustered Instance Learning for Histopathology Cancer Image Segmentation, Clustering, and Classification", CVPR 2012 (* equal contribution). (pdf) (code)
  
• Cong Yao, Xiang Bai, Wenyu Liu, Yi Ma, and Zhuowen Tu, "Detecting Texts of Arbitrary Orientations in Natural Images", CVPR 2012. (pdf) (data)
  
• Wei Shen, Ke Deng, Xiang Bai, Tommer Leyvand, Baining Guo, and Zhuowen Tu, "Exemplar-Based Human Action Pose Correction and Tagging", CVPR 2012. (pdf)
• Jing Wang, Jingdong Wang, Gang Zeng, Zhuowen Tu, and Shipeng Li, "Scalable k-NN graph construction for Visual Descriptors", CVPR 2012. (pdf)
  

• Jiayan Jiang, Bo Wang, and Zhuowen Tu, "Unsupervised Metric Learning by Self-Smoothing Operator", ICCV 2011. (pdf) (code)
  
• Yi Hong, Quannan Li, Jiayan Jiang, and Zhuowen Tu, "Learning A Mixture of Sparse Distance Metrics for Classification and Dimensionality Reduction", ICCV 2011. (pdf)
  
• B. Speier, J.E. Iglesias, L. El-Kara, Z. Tu, and C.W. Arnold. "Robust Skull Stripping of Clinical Glioblastoma Multiforme Data'', MICCAI 2011. (pdf)
  
• J. E. Iglesias, Jiayan Jiang, Cheng-Yi Liu, and Zhuowen Tu, "Classification of Alzheimer's Disease Using a Self-Smoothing Operator", MICCAI 2011. (pdf)
  
• J. E. Iglesias, E. Konukoglu, A. Montillo, Z. Tu, and A. Criminisi, "Combining Generative and Discriminative Models for Semantic Segmentation of CT Scans via Active Learning", Information Processing in Medical Imaging (IPMI), July, 2011.

• Xiang Bai, Bo Wang, Xinggang Wang, Wenyu Liu, and Zhuowen Tu, "Co-Transduction for Shape Retrieval", ECCV 2010. (pdf)
  
• Bo Wang, Xiang Bai, Xinggang Wang, Wenyu Liu, and Zhuowen Tu, "Object Recognition Using Junctions", ECCV 2010. (pdf)
  
• Juan Eugenio Iglesias, Cheng-Yi Liu, Paul Thompson, and Zhuowen Tu, "Agreement-Based Semi-Supervised Learning for Skull Stripping", MICCAI, 2010. (pdf)
  
• Juan Eugenio Iglesias, Ivo Dinov, Jaskaran Singh, Gregory Tong, and Zhuowen Tu, "Synthetic MRI signal standardization: application to multi-atlas analysis", MICCAI, 2010. (pdf)
  

• Xiang Bai, Xinggang Wang, Wenyu Liu, Longin Jan Latecki, and Zhuowen Tu, "Active Skeleton for Non-rigid Object Detection", ICCV 2009 (pdf). (code)
  
• Jiayan Jiang and Zhuowen Tu, "Efficient Scale Space Auto-context for Image Segmentation and Labeling", CVPR 2009 (pdf).
• Xiang Bai, Quannan Li, Longin Jan Latecki, Wenyu Liu, and Zhuowen Tu, "Shape Band: A Deformable Object Detection Approach", CVPR 2009(pdf).
• Piotr Dollár, Zhuowen Tu, Pietro Perona, and Serge Belongie, "Integral Channel Features", Proc. of British Machine Vision Conference (BMVC), 2009 (pdf). (code)
  

• Zhuowen Tu, "Auto-context and Its Application to High-level Vision Tasks", CVPR, 2008 (pdf). (now matlab code included in the fixed point package)
  
• Jiayan Jiang, Songfeng Zheng, Arthur Toga, and Zhuowen Tu, "Learning Based Coarse-to-fine Image Registration", CVPR 2008 (pdf).
• Jason Corso, Alan Yuille, and Zhuowen Tu, "Graph-Shifts: Natural Images Labeling by Dynamic Hierarchical Computing", CVPR 2008 (pdf).
• Xingwei Yang, Xiang Bai, Longin Jan Latecki, and Zhuowen Tu, "Improving Shape Retrieval by Learning Graph Transduction", ECCV 2008 (pdf).
• Piotr Dollár, Boris Babenko, Serge Belongie, Pietro Perona, and Zhuowen Tu, "Multiple Component Learning for Object Detection", ECCV 2008 (pdf).

• Zhuowen Tu, "Learning Generative Models via Discriminative Approaches", IEEE Computer Vision and Pattern Recognition (CVPR), June, 2007. (pdf)
• Songfeng Zheng, Zhuowen Tu, and Alan Yuille, "Detecting Object Boundaries Using Low-, Mid-, and High-Level Information", IEEE Computer Vision and Pattern Recognition (CVPR), June, 2007. (pdf)
• Piotr Dollár, Zhuowen Tu, Hai Tao and Serge Belongie, "Feature Mining for Image Classification", IEEE Computer Vision and Pattern Recognition (CVPR), June, 2007. (pdf)
• Jason Corso, Zhuowen Tu, Alan Yuille, and Arthur Toga, "Likelihood Shift Graphs for Efficient Energy Minimization", Information Processing in Medical Imaging (IPMI), June, 2007. (pdf)

• Zhuowen Tu, Xiang Sean Zhou, Adrian Barbu, Luca Bogoni, and Dorin Comaniciu, "Probabilistic 3D Polyp Detection in CT Images: The Role of Sample Alignment", IEEE Computer Vision and Pattern Recognition (CVPR), June, 2006. (pdf)
• Piotr Dollár, Zhuowen Tu, and Serge Belongie, "Supervised Learning of Edges and Object Boundaries", IEEE Computer Vision and Pattern Recognition (CVPR), June, 2006. (pdf) (software)
  
• Zhuowen Tu, Xiang Sean Zhou, Dorin Comaniciu, and Luca Bogoni, "A Learning Based Approach for 3D Segmentation and Colon Detagging", 9th European Conf. on Computer Vision (ECCV), May 2006. (pdf)

• Zhuowen Tu, "An Integrated Frmework for Image Segmentation and Perceptual Grouping", 10th IEEE International Conference on Computer Vision (ICCV), Oct. 2005 (pdf). (code)
  
• Zhuowen Tu, "Probabilistic Boosting-Tree: Learning Discriminative Models for Classification, Recognition, and Clustering", 10th IEEE International Conf. on Computer Vision (ICCV), Oct. 2005 (pdf).

• Zhuowen Tu, and Alan Yuille "Shape Matching and Recognition--Using Generative Models and Informative Features", 8th European Conf. on Computer Vision (ECCV), May 2004 (pdf).
• Zhuowen Tu, Xiangrong Chen, Alan Yuille, and Song-Chun Zhu, "Image Parsing: Segmentation, Detection, and Object Recognition", 9th IEEE International Conf. on Computer Vision (ICCV), Oct. 2003 (Marr Prize). (pdf).
• Zhuowen Tu and Song-Chun Zhu, "Parsing Images into Region and Curve Processes", 7th European Conf. on Computer Vision (ECCV), May, 2002. (pdf)
• Feng Han, Zhuowen Tu, and Song-Chun Zhu, "A Stochastic Algorithm for Parsing and reconstructing 3D Scenes", 7th European Conf. on Computer Vision (ECCV), May, 2002. (pdf)
• Zhuowen Tu, Song-Chun Zhu, and Harry Shum, "Image Segmentation by Data Driven Markov Chain Monte Carlo", 8th IEEE International Conf. on Computer Vision (ICCV), July 2001. (pdf) (software)
  
• Song-Chun Zhu, Rong Zhang, and Zhuowen Tu, "Integrating Top-down/Bottom-up for Object Recognition by Data Driven Markov Chain Monte Carlo", IEEE Computer Vision and Pattern Recognition (CVPR), July 2000. (pdf)

1. Qibin Hou, Ming-Ming Cheng, Xiaowei Hu, Ali Borji, Zhuowen Tu, Philip H. S. Torr, "Deeply Supervised Salient Object Detection with Short Connections", IEEE Trans. on Pattern Analysis and Machine Intelligence, 2018.
   
2. Chen-Yu Lee, Patrick Gallagher, and Zhuowen Tu, "Generalizing Pooling Functions in Convolutional Neural Networks: Mixed, Gated, and Tree",  IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 40, no 4, pp. 863-875, May, 2017. (pdf)
3. Saining Xie and Zhuowen Tu, "Holistically-Nested Edge Detection", International Journal of Computer Vision, 125(1-3): 3-18, 2017. (pdf)
4. Jun-Yan Zhu, Jiajun Wu, Yan Xu, Eric Chang, and Zhuowen Tu, "Unsupervised Object Class Discovery via Saliency-Guided Multiple Class Learning", IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 37, no. 4, pp. 862-875, April, 2015. (pdf) (project page).
5. B. Wang, A. Mezlini, F. Demir, M. Fiume, Z. Tu, M. Brudno, B. Haibe-Kains, and A. Goldenberg, "Similarity Network Fusion for Aggregating Data Types on a Genomic Scale". Nature Methods, doi:10.1038/nmeth.2810, Jan. 2014. (link)
6. Yan Xu, Jun-Yan Zhu, Eric I-Chao Chang, Maode Lai, and Zhuowen Tu, "Weakly Supervised Histopathology Cancer Image Segmentation and Classification", Medical Image Analysis, 2014. (pdf) (project page) (code)
7. Xinggang Wang, Zhengdong Zhang, Yi Ma, Xiang Bai, Wenyu Liu, and Zhuowen Tu, "Robust Subspace Discovery via Relaxed Rank Minimization", Neural Computation, 2014 (pdf).


8. Jiayi Ma, Ji Zhao, Jianwen Tian, Xiang Bai, and Zhuowen Tu, "Regularized Vector Field Learning with Sparse Approximation for Mismatch Removal", Pattern Recognition 2013.
   
9. Cong Yao, Xin Zhang, Xiang Bai, Wenyu Liu, Yi Ma, Zhuowen Tu, "Rotation-invariant Features for Multi-oriented Text Detection in Natural Images", Plos One, August 5, 2013.
   
10. Cheng-Yi Liu, Juan Eugenio Iglesias, and Zhuowen Tu, "Integrated Deformable Templates and Discriminative Models for Robust 3D Brain MRI Segmentation", Neuroinformatics, 2013. (code)
    
11. Huazhu Fu, Xiaochun Cao, and Zhuowen Tu, "Cluster-based Co-saliency Detection", IEEE Tran. on Image Processing, 2013 (pdf) .
12. Y Xu, Y Wang, J Liu, Z Tu, JT Sun, J Tsujii, E Chang, "Suicide note sentiment classification: a supervised approach augmented by web data", Biomedical informatics insights 5 (Suppl. 1), 31, 2012.
    
13. Yan Xu, Jiahua Liu, Jiajun Wu, Yue Wang, Zhuowen Tu, Jian-Tao Sun, Junichi Tsujii, Eric Chang, "A Classification Approach to Coreference in Discharge Summaries: 2011 I2b2 Challenge", J. of the American Medical Informatics Association, doi:10.1136/amiajnl-2011-000734, 2012.
    
14. Xiang Bai, Bo Wang, Cong Yao, Wenyu Liu, and Zhuowen Tu, "Co-Transduction for Shape Retrieval", IEEE Trans. on Image Processing, vol. 21, no. 5, pp. 2747-2757, May, 2012. (pdf)
    
15. Juan Eugenio Iglesias, Paul M. Thompson, Chen-Yi Liu and Zhuowen Tu, "Fast Approximate Stochastic Tractography", Neuroinformatics, 10(1): 5-17, Jan. 2012. (pdf)
    
16. Juan Eugenio Iglesias, Chen-Yi Liu, Paul M. Thompson, and Zhuowen Tu, "Robust Brain Extraction Across Datasets and Comparison with Publicly Available Methods", IEEE Trans. on Medical Imaging, vol. 30, no. 9, pp. 1617-34, Sept., 2011. (pdf) (software)
    
17. Juan Eugenio Iglesias, Paul M. Thompson, and Zhuowen Tu, "Modeling diffusion-weighted MRI as a spatially-variant Gaussian mixture: application to image denoising", Medical Physics, vol. 38, no. 7, pp. 4350-43064, July, 2011. (pdf)
    
18. S. G Costafreda, I. D Dinov, Z. Tu, Y. Shi, C.-Y. Liu, I. Kloszewska, P. Mecocci, H. Soininen, M. Tsolaki, B. Vellas, L.-O. Wahlund, C. Spenger, A. W Toga, S. Lovestone, A. Simmons, "Automated hippocampal shape analysis predicts the onset of dementia in mild cognitive impairment", NeuroImage, Jan. 2011. (pdf)
    
19. Songfeng Zheng, Alan Yuille, and Zhuowen Tu, "Detecting Object Boundaries Using Low-, Mid-, and High-Level Information", Journal of Computer Vision and Image Understanding, vol. 114, no. 19, Oct. 2010. (pdf)
    
20. Zhuowen Tu and Xiang Bai, "Auto-context and Its Application to High-level Vision Tasks and 3D Brain Image Segmentation", IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 21, no. 10, pp. 1744-1757, 2010. (pdf)
    
21. Jonathan H. Morra, Zhuowen Tu, Liana G. Apostolova, Amity Green, Arthur W. Toga, and Paul M. Thompson, "Comparison of AdaBoost and Support Vector Machines for Detecting Alzheimer's Disease through Automated Hippocampal Segmentation, IEEE Trans. on Medical Imaging, vol. 29, no. 1, pp. 30-43, Jan. 2010 (pdf).
22. Xiang Bai, Xingwei Yang, Longin Jan Latecki, Wenyu Liu, and Zhuowen Tu, "Learning Context Sensitive Shape Similarity by Graph Transduction", IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 32, no. 5, pp. 861-874, May, 2010. (pdf)
23. S. Fears, W. Melega, S. K. Service, C. Lee, K. Chen, Z. Tu, M. J. Jorgensen, L. A. Fairbanks, N. Freimer, R. P. Woods, "Identifying Heritable Brain Phenotypes in an Extended Pedigree of Vervet Monkeys”, Journal of Neuroscience, vol. 29, no. 9, pp. 2867-2875, 2009. (pdf)
    
24. Y. Shi, Z. Tu, A. L. Reiss, R. Dutton, A. Lee, A.M. Galaburda, I. Dinov, P. Thompson, A. Toga, "Joint Sulcal Detection on Cortical Surfaces with Graphical Models and Boosted Priors", IEEE Trans. on Medical Imaging, vol. 28, no. 3, pp. 361-373, 2009. (pdf)
25. J. H. Morra, Z. Tu, L. G. Apostolova, A. E. Greena, C. Avedissiana, S. K. Madsen, N. Parikshak, X. Hua, A. W. Toga, C. R. JackJrc, M. W. Weiner, P. M. Thompson, "Validation of a Fully Automated 3D Hippocampal Segmentation Method Using Subjects with Alzheimer's Disease, Mild Cognitive Impairment, and Elderly Controls", NeuroImge, Oct. 15; (43(1), pp. 59-68, 2008. (pdf)
    
26. Zhuowen Tu, Katherin Narr, Piotr Dollar, Iov Dinov, Paul Thompson, and Arthur Toga, "Brain Anatomical Structure Segmentation by Hybrid Discriminative/Generative Models", IEEE Trans. on Medical Imaging, vol. 27, no. 4, pp. 495-508, April, 2008. (pdf)
27. Zhuowen Tu, Songfeng Zheng, and Alan Yuille, "Shape Matching and Registration by Data-driven EM", Journal of Computer Vision and Image Understanding, vol. 109, pp. 290-304, 2008. (pdf)
28. Y. Shi, P. M. Thompson, G. I. De Zubicaray, S. E. Rose, Z. Tu, I. Dinov, and A. Toga, "Direct Mapping of Hippocampal surfaces with Intrinsic Shape Context", Neuroimage, vol. 37, no. 3, pp. 792-807, Sep., 2007.
29. Z. Tu, S. Zheng, , A. Yuille, A. Reiss, R. Dutton, A.Lee, A.Galaburda, I. Dinov, P. Thompson, A. Toga, "Automated Extraction of the Cortical Sulci Based on a Supervised Learning Approach", IEEE Trans. on Medical Imaging, vol. 26, no. 4, April, pp. 541-552, 2007. (pdf)
30. Zhuowen Tu and Song-Chun Zhu, "Parsing Images into Regions, Curves, and Curve Groups", International Journal of Computer Vision, vol. 69, no. 2, pp. 223-249, Aug., 2006. (pdf)
31. Zhuowen Tu, Xiangrong Chen, Alan Yuille, and Song-Chun Zhu, "Image Parsing: Unifying Segmentation, Detection, and Object Recognition", International Journal of Computer Vision, vol. 63, no. 2, pp. 113-140, July, 2005. (pdf)
32. Feng Han, Zhuowen Tu, and Song-Chun Zhu, "Range Image Segmentation by an Efficient Jump-Diffusion Method", IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 26, no. 9, pp. 1138-1153, Sept. 2004. (pdf)
33. Zhuowen Tu and Song-Chun Zhu, "Image Segmentation by Data-Driven Markov Chain Monte Carlo", IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 24, No. 5, pp. 657-673,May, 2002. (pdf)
34. Zhuowen Tu and Ronxing Li, "A Framework for Automatic Recognition of Spatial Features from Mobile Mapping Imagery", Journal of Photogrammetric Engineering and Remote Sensing, Vol. 68, No. 3, March, 2002.

1. Weichao Qiu, Xinggang Wang, Xiang Bai, Alan Yuille, and Zhuowen Tu, "Scale-Space Sift Flow", Proc. of WACV, 2014 (pdf).
2. Boris Babenko, Piotr Dollár, Zhuowen Tu, and Serge Belongie, "Simultaneous Learning and Alignment: Multi-Instance and Multi-Pose Learning", RealFaces, Marseille, France, 2008. (pdf)