About

Bihan Wen

Assistant Professor, School of EEE

Nanyang Technological University (NTU), Singapore

 

PhD 18', MS 15', ECE , University of Illinois at Urbana-Champaign (UIUC)

BE 12', EEE , NTU, Singapore

Email: bihan.wen at ntu.edu.sg

News

  • Mar, 2019

  • [Notice] I joined Nanyang Technological University (NTU) as a tenure-track Assistant Professor.

  • Feb, 2019

  • [Publicity & Service] I became the Area Chair (AC) and TPC member for ICIP 2019 .

    [Publicity & Service] I became the reviewer for ACM TOMM .

    [Publication] My PhD Thesis is publicly available at IDEALS @ Illinois [ Paper ] : Adaptive Nonlocal and Structured Data Modeling

    [Publicity & Service] I became the reviewer for ICCV 2019.

  • Jan, 2019

  • [Publicity & Service] I became the program committee (PC) member for IJCAI 2019.

    [Codes & Website] For exactly reproducible purpose, we release the original NLRN_v0 , used in our NIPS 2018 paper.

    [Publication] One invited paper got accepted to MIPR 2019 .

    [Invited Talk] I am invited to visit Nanyang Technological University (NTU) , Jan 28 - 30.

    [Publicity & Service] I became the reviewer for IEEE Signal Processing Letters (SPL).

  • Dec, 2018

  • [Publicity & Service] I became the reviewer for Aerospace Science and Technology (AST).

    [Publication] One invited paper got accepted to ICSM 2018 [ Paper ] : Smart Signal Processing meets Sensing.

    [Publicity & Service] I became the reviewer for ICME 2019.

    [Codes & Website] We released the NLRN code that was used in our NIPS 2018 paper.

  • Oct - Nov, 2018

  • [Publicity & Service] I am elected to be the IEEE Computational Imaging TC , for the term 2019 - 2021.

    [notice] I am travelling to Montreal, Canada for NIPS 2018 , from Dec 1 to 7 .

    [Publication] One paper got accepted to ACML 2018 [ Open Access ] [ Codes ] : Patch Group Sparsity via Dictionary Learning.

    [Publicity & Service] I became the reviewer for CVPR 2019.

  • September, 2018

  • [Notice] I joined [ Yitu (依图) ], working with their overseas research team.

    [Notice] Please always use [ www.bihanwen.com ] to visit my homepage. There may be domain changes recently.

    [Publication] One paper got accepted to NIPS 2018 [ Preprint ] [ Codes ] [ Paper ]: Non-Local RNN for Image Restoration.

    [Invited Talk] I am invited to visit Singapore University of Technology and Design (SUTD) and give talks, Sep 20 - 21.

    [Publication] One paper submitted to IEEE TIP [ Preprint ]: Connecting Denoising and High-Level Vision Tasks.

    [Publicity & Service] I became the Reviewer for IEEE Access .

  • August, 2018

  • [Publication] One paper submitted to IEEE TIP [ Preprint ]: The Power of Complementary Regularizers.

    [Publicity & Service] I became the Reviewer for IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) .

    [Invited Talk] I am invited to visit Nanyang Technological University (NTU) (my Alma Mater!), Aug 28 - 29.

    [Publication] One invited paper accepted to ICSM 2018 : When smart signal processing meets smart sensing.

    [Publicity & Service] I became the Reviewer for IOP Inverse Problems .

  • June - July, 2018

  • [Publication] One paper got accepted to IEEE TIP [ Preprint ], [ codes (coming soon) ]. Congratulations to Saiprasad!

    [Invited Talk] I presented my PhD thesis at the 3MT thesis competition, in ICME 2018. [ Slides ], [1st Place]

    [Milestone] I passed my PhD final defense!

  • May, 2018

  • [Publication] One paper submitted to NIPS 2018 [ Preprint ]: A Non-Local RNN framework for image denoising and super-resolution.

    [Publicity & Service] I became the Reviewer for ACCV 2018.

    [Publicity & Service] I became the demo session co-chair for MIPR 2019 .

    [Publication] One patent with Dolby Lab has been filed: histogram transfer for inverse HDR reshaping.

  • April, 2018

  • [Publication] One paper got accepted to IJCAI 2018 (rate = 20%) [ Preprint ], [ codes ]. Congratulations to Ding, Xianming, and Atlas!

    [Publicity & Service] I became the Reviewer for Journal of Experimental and Theoretical Artificial Intelligence (JETAI) .

    [Invited Talk] The video recording of my talk at CSL Student Conference 2018 is available online. [ Recording ]

    [Invited Talk] The slides of my guest lecture at Texas A&M University is available online. [ Slides ]

    Education

  • University of Illinois at Urbana-Champaign (UIUC), USA

  •      2012 - 2018, Master / PhD, Electrical and Computer Engineering (ECE)

         Advisor: Prof. Yoram Bresler

         Research Interests:

         Machine Learning, Sparse / Low-Rank Representation, Image / Video Processing,

         Computer Vision, Computational Imaging, Optimization.

  • Nanyang Technological University (NTU), Singapore

  •      2008 - 2012, Bachelor, Electrical and Electronic Engineering (EEE)

         Advisor: Prof. Yilong Lu

     

    Publications

  • Preprint

  •       D. Liu, B. Wen, J. Jiao, X. Liu, Z. Wang, and T. Huang, "Connecting Image Denoising and High-Level Vision Tasks via Deep Learning," IEEE Transcations on Image Processing (TIP), submitted. [ Arxiv:1809.01826 ]

          B. Wen, Y. Li, and Y. Bresler, "The Power of Complementary Regularizers: Image Recovery via Transform Learning and Low-Rank Modeling," IEEE Transcations on Image Processing (TIP), submitted. [ Arxiv:1808.01316 ]

  • 2019

  •       B. Wen, S. Ravishankar, and Y. Bresler, "VIDOSAT - High-dimensional Sparsifying Transform Learning for Online Video Restoration," IEEE Transcations on Image Processing (TIP), 2018. [ Arxiv:1710.00947 ]

  • 2018

  •       Z. Zha, X. Yuan, B. Wen , J. Zhou, and C. Zhu, "Joint Patch-Group Based Sparse Representation for Image Inpainting," Asian Conference on Machine Learning (ACML) 2018. [ Open Access ] [ Codes ]

          D. Liu, B. Wen, Y. Fan, C.-L. Chen, and T. Huang, "Non-Local Recurrent Network for Image Restoration," Conference on Neural Information Processing Systems (NIPS) 2018. [ Arxiv:1710.00947 ] [ Open Access ] [ Codes ]

          B. Wen , and G. Su, "When Smart Signal Processing Meets Smart Imaging," International Conference on Smart Multimedia (ICSM) 2018. [ Paper ]

          D. Liu, B. Wen, X. Liu, Zhangyang Wang, and T. Huang, “When Image Denoising Meets High-Level Vision Tasks: A Deep Learning Approach,” International Joint Conference on Artificial Intelligence (IJCAI), 2018, to appear. [ Arxiv:1706.04284 ], [ Open Access ] [ codes ]

          B. Wen, and G. Su, “TransIm: Transfer Image Local Statistics Across EOTFs for HDR Image Applications,” IEEE International Conference on Multimedia and Expo (ICME), 2018. [ PDF ]

          B. Wen, U. Kamilov, D. Liu, H. Mansour, and P. Boufounos, “DeepCASD: An End-to-End Approach for Multispectral Image Super-Resolution,” IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018. [ PDF ]

  • 2017

  •       B. Wen, Y. Li, L. Pfister, and Y. Bresler, “Joint Adaptive Sparsity and Low-rankness on the Fly: An Online Tensor Reconstruction Method for Video Denoising,” IEEE International Conference on Computer Vision (ICCV), 2017. [ open access ], [ PDF ], [ codes ]

          B. Wen, S. Ravishankar, and Y. Bresler, “FRIST Flipping and Rotational Invariant Sparsifying Transform Learning and Applications,” Inverse Problems (IVP), 2017. [ PDF ], [ codes ]

          B. Wen, Y. Li, and Y. Bresler, “When Sparsity meets Low-Rankness: Transform Learning with Non-local Low-rank Constraint for Image Restoration,” IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017. [ PDF ], [ codes ]

          Y. Zhu, T-T. Ng, B. Wen, X. Shen, and B. Li, “Copy-move Forgery Detection in the Presence of Similar but Genuine Objects,” IEEE International Conference on Signal and Image Processing (ICSIP), 2017. [ PDF ]

  • 2016

  •       B. Wen, S. Ravishankar, and Y. Bresler, “Structured Overcomplete Sparsifying Transform Learning with Convergence Guarantees and Applications,” International Journal of Computer Vision (IJCV), 2016. [ PDF ], [ codes ]

          D. Liu, Z. Wang B. Wen, J. Yang, W. Han, and T. Huang, “Robust Image Super-Resolution via Deep Networks with Sparse Prior,” IEEE Transcations on Image Processing (TIP), 2016. [ PDF ], [ codes ]

          S. Dev B. Wen, Y. Lee, and S. Winkler, “Ground-based Image Analysis: A Tutorial on Machine-Learning Techniques and Applications,” IEEE Geoscience and Remote Sensing Magazine (GRSM), 2016. [ PDF ]

          B. Wen, S. Ravishankar, and Y. Bresler, “Learning Flipping and Rotational Invariant Sparsifying Transform,” IEEE International Conference on Image Processing (ICIP), 2016. [ PDF ], [ codes ]

          B. Wen, Y. Zhu, R. Subramanian, T-T. Ng, X. Shen, and S. Winkler, “COVERAGE - A Novel Database for Copy-Move Forgery Detection,” IEEE International Conference on Image Processing (ICIP), 2016. [ PDF ], [ dataset ]

  • 2015

  •       S. Ravishankar, B. Wen, and Y. Bresler, “Online Sparsifying Transform Learning Part I: Algorithms,” IEEE Journal of Selected Topics in Signal Processing (JSTSP), 2015. [ PDF ]

          B. Wen, S. Ravishankar and Y. Brelser, “Video Denoising by Online 3D Sparsifying Transform Learning,” to appear in Proc. IEEE Int. Conf. Image Processing (ICIP), 2015. [ PDF ], , [ codes ]

  • 2014

  •       B. Wen, S. Ravishankar and Y. Brelser, “Learning Overcomplete Sparsifying Transforms with Block Cosparsity,” in Proc. IEEE Int. Conf. Image Processing (ICIP), 2014.  (10% Top Paper) [ PDF ], [ codes ]

          S. Ravishankar, B. Wen and Y. Brelser, “Online Sparsifying Transform Learning for Big Data Signal Processing,” in Proc. IEEE Global Conf. on Signal and Information Processing (Global SIP), 2014.  [ PDF ]

  • Undergrat Works

  •       B. Wen and Y. Lu, “A study of synthetic aperture radar imaging with compressed sensing,” in Proc. IEEE Asia-Pacific Conf. on Antennas and Propagation (APCAP), 2012.  [LINK]

          B. Wen and Y. Lu, “MATLAB tools for EnviSAT ASAR data visualization and image enhancement,” in Proc. SPIE Int. Symp. on Lidar and Radar Mapping Tech., 2011.  [LINK]

     

    Academic Services

  • Technical Committee Member

  • IEEE Computational Imaging, Technical Committee ( IEEE CI TC ), 2019 - 2021.

  • Conference Area Chair

  • IEEE International Conference on Image Processing (ICIP 2019)

  • Conference PC / Reviewer

  • IEEE International Conference on Computer Vision (ICCV 2019)

    International Joint Conference on Artificial Intelligence (IJCAI 2019)

    Conference on Computer Vision and Pattern Recognition (CVPR 2019)

    IEEE International Conference on Multimedia and Expo ( ICME 2019)

    Asian Conference on Computer Vision (ACCV 2018)

    IEEE International Conference on Image Processing (ICIP 2018)

    Conference on Computer Vision and Pattern Recognition (CVPR 2018)

    IEEE International Conference on Image Processing (ICIP 2017)

  • Journal Reviewer

  • IEEE Transactions on Pattern Analysis and Machine Intelligence ( TPAMI )

    IEEE Transactions on Image Processing ( TIP )

    IEEE Transactions on Signal Processing ( TSP )

    IEEE Transactions on Circuits and Systems for Video Technology ( TCSVT )

    IEEE Transactions on Information Forensics and Security ( TIFS )

    IEEE Transactions on Computational Imaging ( TCI )

    IEEE Signal Processing Letters ( SPL )

    Elsevier Neurocomputing ( Neurocomputing )

    IOP Inverse Problems ( IP )

    IEEE Access

    Electronics Letters ( EL )

    Aerospace Science and Technology ( AST )

    IET Radar, Sonar and Navigation ( RSN )

    Journal of Electronic Imaging ( JEI )

    Journal of Experimental & Theoretical Artificial Intelligence ( JETAI )

    Current Medical Imaging Reviews ( CMIR )

  • Conference Organization

  • Session Co-Chair, IEEE International Conference on Multimedia Information Processing and Retrieval ( MIPR 2019 )

    Session Chair, Coordinated Science Laboratory Student Conference ( CSLSC 2017 )

    Session Assistant, Allerton Conference on Communication, Control, and Computing ( Allerton 2017 )

    Experiences

    Coordinated Science Lab

    Aug 2012 – present

    I am working with Prof. Yoram Bresler on machine learning for sparse data representation. We developed novel sparse model and transform learning algorithms for many data applications. We are working on extension to high-dimensional and large-scale problems, as well as combination with high-level vision problems with deep learning.

    Mitsubishi Elec. Research Lab. (MERL)

    May – Aug 2017

    I worked with Prof. Ulugbek Kamilov and Dr. Dehong Liu on multi-spectral data fusion problems. We proposed novel deep neural networks by unfolding the coupled dictionary learning.

    Dolby Laboratories

    May - Aug 2016

    I worked with Dr. Guan-Ming Su and Dolby Vision team on high dynamic range (HDR) video enhancement and reshaping problems. Our proposed methods have been patented and used in Dolby Vision codec.

    Advancec Digital Science Center

     

    May - Aug 2015

    I worked with Dr. Stefan and Dr. Rama Ratnam on several computer vision projects, including (i) machine learning applications in remote sensing, and (ii) image forgery detection using multi-model signal and data.

    ECE Department ECE 210

     

    2013 - 2014

    I was the head teaching assistant for ECE 210 Analog Signal Processing under Prof. Erhan Kudeki. I teached in the weekly lab and provided office hours. It is the major course for ECE undergraduate students. I was nominated for Harold L. Olesen Award by the students.

    Nanyang Technological University

    2008 - 2012

    I received my B.S. degree from Nanyang Technological University (NTU), Electrical and Electronic Engineering (EEE) in Singapore. During the 4 years undergraduate study, I worked with Prof. Yilong Lu for synthetic aperture radar (SAR) data analysis research.

    Sofewares

    Video Denoising via SALT

    The proposed algorithm denoises video online by reconstructing Sparse And Low-rank Tensor (SALT) sequentially.

    It Provides state-of-the-art denoising quality with cheap computation, small memory footprint, and low latency.

    Paper available [ here ].

    Download the codes [ here ].

    OCTOBOS learning and applications

    The proposed algorithm adaptively learns a structured overcomplete sparsifying transform with block cosparsity.

    It Provides simultaneous data clustering and reconstruction.

    Paper available [ here ].

    Download the codes [ here ].

    COVERAGE dataset for copy-move forgery detection

    COVERAGE contains copymove forged (CMFD) images and their originals with similar but genuine objects (SGOs).

    COVERAGE is designed to highlight and address tamper detection ambiguity of popular methods, caused by self-similarity within natural images.

    Paper available [ here ].

    Download the dataset [ here ].