简介

文碧汉

 

研究生/博士生

计算机电子工程系

伊利诺伊香槟大学

340 Coordinated Science Lab, 1308 W. Main Street, Urbana Illinois 61801

电邮: bwen3 at illinois dot edu

最近新闻

  • 四月, 2018

  • [论文] 一篇论文被 IJCAI 2018 接受 (录取率 = 20%) [ 论文preprint ], [ 代码 ].. 恭喜刘鼎,先明和Atlas!

  • 三月, 2018

  • [报告邀请] 我接受了 Texas A&M University 的邀请并做了客座授课. [ 新闻 ]

    [项目代码] 我开源了简明的 Unitary Transform Learning 代码包,被使用于 STROLLR 这篇论文 (ICASSP 2017).

    [论文] 一篇论文被 ICME 2018 接受并做口头演讲报告 (录取率 = 15%). 恭喜 Guan-Ming!

    [报告邀请] 我接受了 Texas A&M University 的邀请并做报告. [ 新闻 ]

    [报告邀请] 我接受了 Huawei (华为) 主办的 Midwest Research Summit 的邀请并做报告. [最佳报告奖]

  • 二月, 2018

  • [报告邀请] 我接受了 CSL Student Conference 2018 的邀请并做了演讲. [ 新闻 ], [ 最佳演讲奖 ,评选 by NVIDIA]

    [学术服务] 我加入了 ICIP 2018 的会议审稿委员会.

    [项目代码] 我们公开了 FRIST (IVP 2017, ICIP 2016) 的代码.

    [学术服务] 我加入了 ISCAIE 2018 的审稿委员会.

    [报告邀请] 我接受了 Toutiao (今日头条)的要求并做演讲.

  • 一月, 2018

  • [论文] 一篇论文被 ICASSP 2018 接受. 恭喜 Ulugbek, Dehong, Hassan, and Petros!

    [学术服务] 我加入了 Current Medical Imaging Reviews 刊物的审稿委员会.

    [项目代码] 我们公开了 STROLLR denoising (ICASSP 2017) 的代码.

    [项目代码] 我创建了 可复现图像降噪算法列表 。现在上线在Github开源项目,欢迎大家来添砖加瓦。

  • 12月, 2017

  • [学术服务] 我加入CVPR 2018会议成员组,担任审稿人.

    [论文] 提交了 VIDOSAT video denoising 论文到 TIP.

    教育

  • 伊利诺伊香槟大学(UIUC), 美国

  •      2012.8 - present, 研究生 / 博士生, 计算机与电子工程 (ECE)

         导师: Prof. Yoram Bresler

         研究兴趣:

         机器学习

         稀疏表达

         大数据

         图像/视频处理

     

  • 南洋理工大学 (NTU), 新加坡

  •      2008.8 - 2012.6, 本科, 电子电机工程 (EEE)

         导师: Prof. Yilong Lu

     

    发表

  • Preprint

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

  • 2018

  •       D. Liu, B. Wen, X. Liu, 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 ], [ 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, to appear.

          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, to appear.

  • 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 ]

          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 ]

          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 ]

          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]

     

    学术服务

  • 会议成员/审稿人

  • Conference on Computer Vision and Pattern Recognition (CVPR 2018)

    IEEE International Conference on Image Processing (ICIP 2017)

  • 期刊审稿人

  • 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 )

    Elsevier Neurocomputing Neurocomputing

    Electronics Letters ( EL )

    IET Radar, Sonar and Navigation ( RSN )

    Journal of Electronic Imaging ( JEI )

  • 组织会议

  • 领域主席, Coordinated Science Laboratory Student Conference ( CSLSC 2017 )

    领域助理, Allerton Conference on Communication, Control, and Computing ( Allerton 2017 )

    经历

    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.

    开源程序

    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 ].