Please also see my publications at Google Scholar.

Selected Preprints
  1. Kwonjoon Lee, Huiwen Chang, Lu Jiang, Han Zhang, Zhuowen Tu, and Ce Liu, "ViTGAN: Training GANs with Vision Transformers", arXiv:2107.04589, 2021.
  2. Yifan Xu, Kening Zhang, Haoyu Dong, Yuezhou Sun, Wenlong Zhao, and Zhuowen Tu, "Rethinking Exposure Bias in Language Modeling", arXiv:1910.11235, 2019.
  3. Yifan Xu, Lu Dai, Udaikaran Singh, Kening Zhang, and Zhuowen Tu, "Neural Program Synthesis by Self-Learning", arXiv:1910.05865, 2019.
  4. Long Jin, Zeyu Chen, and Zhuowen Tu, "Object Detection Free Instance Segmentation With Labeling Transformations", arXiv:1611.08991, 2016.

Selected Conferences





Co-Scale Conv-Attentional Image Transformers
Weijian Xu*, Yifan Xu*, Tyler A. Chang, and Zhuowen Tu (*equal contribution)
 ICCV 2021 / Pape
r / 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 / Pape
r / 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 / Paper / 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



  Journals
  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.
Other Refereed Conferences and Workshops
  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)