Liefeng Bo, Senior Research Scientist at Intel Labs

Collaborators: Dieter Fox, Xiaofeng Ren, and Anthony LaMarca

University of Washington Computer Science & Engineering

Box 352350, Paul G. Allen Center for CSE436
Seattle, WA 98195-2350

Email: lfb@cs.washington.edu, liefengbo@gmail.com

Biography: I am a senior research scientist at the Intel Science and Technology Center on Pervasive Computing (ISTC-PC). I also hold an affiliate faculty in the Department of Computer Science and Engineering at the University of Washington (UW). My research interests are in Machine Learning, Computer Vision and Robotics. I was a postdoc at the UW from 2010-2012 and at the Toyota Technological Institute at Chicago from 2008-2009, respectively. From 2002-2007, I was a PhD student at the Xidian University, where I received a doctorate in Electronic Engineering, with a specialization in Machine Learning.

[Research][Publication][Software][CV][Google Scholar Page]

News

  • Intel Labs Research Scientist Opportunity in Computer Vision!!! Please contact me if you are interested in it.

  • Reproducible Research via Open Source Software and Open Access to Data and Publications

  • Multipath Sparse Coding Using Hierarchical Matching Pursuit: CVPR 2013

  • Hierarchical Matching Pursuit for Learning Expressive Features from RGB-Detph Data: Source Code

  • Hierarchical Kernel Descriptors for RGB-Depth Data: Source Code, Dataset and Demos

  • Best Vision Paper Award at ICRA 2011 - Flagship Robotics Conference

  • 2010 National Excellent Doctoral Dissertation Award: Highest Award for PhD Thesis in China

Research Interests

  • Machine Learning: Deep Learning and Feature Learning, Hierarchical Matching Pursuit, Dictionary Learning and Sparse Coding, Big Data Systems, Support Vector Machines and Kernel Methods, Structured Prediction, Graphical Models

  • Computer Vision and Robotics: Object Recognition, Fine-Grained Recognition, Depth Cameras for Computer Vision, RGB-Depth Kernel Descriptors, Integrating Natural Language and Vision, Human Pose Estimation, Scene Understanding

Recent Software (More Software)

Recent Papers (More Papers)

Learning Hierarchical Sparse Representations

  • Liefeng Bo, Xiaofeng Ren and Dieter Fox, Multipath Sparse Coding Using Hierarchical Matching Pursuit, In IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), June 2013. [PDF] [BIB]

  • Michael Ruhnke, Liefeng Bo and Dieter Fox and Wolfram Burgard, Compact RGBD Surface Models Based on Sparse Coding, In the AAAI Conference on Artificial Intelligence (AAAI), July 2013. [PDF] [BIB]

  • Xiaofeng Ren and Liefeng Bo, Discriminatively Trained Sparse Code Gradients for Contour Detection, Advances in Neural Information Processing Systems ( NIPS), December, 2012. [PDF] [BIB] [Code]

  • Liefeng Bo, Xiaofeng Ren and Dieter Fox, Unsupervised Feature Learning for RGB-D Based Object Recognition, In International Symposium on Experimental Robotics, (ISER), June 2012. [PDF] [BIB] [Code] [Slides]
    Hierarchical matching pursuit (HMP) over four channels: grayscale, RGB, depth, and surfrace normal
    Higher accuracy than many state-of-the-art recognition algorithms

  • Liefeng Bo, Xiaofeng Ren and Dieter Fox, Hierarchical Matching Pursuit for Image Classification: Architecture and Fast Algorithms, Advances in Neural Information Processing Systems (NIPS), December, 2011. [PDF] [BIB] [Code] [Poster]
    A multi-layer sparse coding model that yields higher accuracy than single-layer sparse coding on top of SIFT
    Batch tree orthogonal matching pursuit = highly efficient sparse coding

Integrating Language and Vision

  • Yuyin Sun, Liefeng Bo and Dieter Fox, Attribute Based Object Identification, In IEEE International Conference on Robotics and Automation (ICRA), May, 2013. [PDF] [BIB]

  • Cynthia Matuszek, Nicholas FitzGerald, Luke Zettlemoyer, Liefeng Bo, and Dieter Fox, A joint model of language and perception for grounded attribute learning, In International Conference on Machine Learning (ICML), July 2012. [PDF] [BIB]

RGB-D Kernel Descriptors

  • Shulin Yang, Liefeng Bo, Jue Wang and Linda Shapiro, Unsupervised Template Learning for Fine-Grained Object Recognition, Advances in Neural Information Processing Systems (NIPS), December, 2012. [PDF] [BIB]

  • Xiaofeng Ren, Liefeng Bo and Dieter Fox, RGB-(D) Scene Labeling: Features and Algorithms, In IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), June 2012. [PDF] [BIB] [Code]
    Kernel descriptors + segmentation tree achieves the state-of-the-art results on the NYU and Stanford Background datasets

  • Liefeng Bo, Xiaofeng Ren and Dieter Fox, Depth Kernel Descriptors for Object Recognition, In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September 2011. [PDF] [BIB] [Dataset] [Code]
    Kernel Descriptors over depth maps and 3D point clouds

  • Liefeng Bo, Kevin Lai, Xiaofeng Ren and Dieter Fox, Object Recognition with Hierarchical Kernel Descriptors, In IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), June 2011. [PDF] [BIB] [Dataset] [Code]
    Kernel descriptors over kernel descriptors: a deep architecture

  • Liefeng Bo, Xiaofeng Ren and Dieter Fox, Kernel Descriptors for Visual Recognition, Advances in Neural Information Processing Systems (NIPS), December, 2010. [PDF] [Spotlight] [Video] [BIB] [Code]
    A general approach to extract local features from pixel attributes that includes popular SIFT and HOG features as special cases
    KDES + EMK + linear SVMs has 77.5% accuracy on Caltech101 and 87.5% accuracy on Scene15 (higher than those reported in the paper)

  • Liefeng Bo and Cristian Sminchisescu, Efficient Match Kernels between Sets of Features for Visual Recognition, Advances in Neural Information Processing Systems (NIPS), December, 2009. (spotlight acceptance rate 8%) [PDF] [BIB]