Projects

  1. summary image

    M3D-RPN: Monocular 3D Region Proposal Network for Object Detection

    Garrick Brazil, Xiaoming Liu

    Understanding the world in 3D is a critical component of urban autonomous driving. Generally, the combination of expensive LiDAR sensors and stereo RGB imaging has been paramount for successful 3D object detection algorithms, whereas monocular image-only methods experience drastically reduced performance. We propose to reduce the gap by reformulating the ...

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    Keywords: 3D Object Detection

  2. summary image

    Pedestrian Detection with Autoregressive Network Phases

    Garrick Brazil, Xiaoming Liu

    We present an autoregressive pedestrian detection framework with cascaded phases designed to progressively improve precision. The proposed framework utilizes a novel lightweight stackable decoder-encoder module which uses convolutional re-sampling layers to improve features while maintaining efficient memory and runtime cost. Unlike previous cascaded detection systems, our proposed framework is designed ...

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    Keywords: Pedestrian Detection

  3. summary image

    Illuminating Pedestrians via Simultaneous Detection & Segmentation

    Garrick Brazil, Xi Yin, Xiaoming Liu

    Pedestrian detection is a critical problem in computer vision with significant impact on safety in urban autonomous driving. In this work, we explore how semantic segmentation can be used to boost pedestrian detection accuracy while having little to no impact on network efficiency. We propose a segmentation infusion network to ...

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    Keywords: Pedestrian Detection, Semantic Segmentation

Publications

2019

  • M3D-RPN: Monocular 3D Region Proposal Network for Object Detection
    Garrick Brazil, Xiaoming Liu
    In Proceeding of International Conference on Computer Vision (ICCV 2019), Seoul, South Korea, Oct. 2019 (Oral presentation)
    Bibtex | PDF | arXiv | Project Webpage | Video
  • @inproceedings{ m3d-rpn-monocular-3d-region-proposal-network-for-object-detection,
      author = { Garrick Brazil and Xiaoming Liu },
      title = { M3D-RPN: Monocular 3D Region Proposal Network for Object Detection },
      booktitle = { In Proceeding of International Conference on Computer Vision },
      address = { Seoul, South Korea },
      month = { October },
      year = { 2019 },
    }
  • Pedestrian Detection with Autoregressive Network Phases
    Garrick Brazil, Xiaoming Liu
    In Proceeding of IEEE Computer Vision and Pattern Recognition (CVPR 2019), Long Beach, CA, Jun. 2019
    Bibtex | PDF | arXiv | Poster | Project Webpage
  • @inproceedings{ pedestrian-detection-with-autoregressive-network-phases,
      author = { Garrick Brazil and Xiaoming Liu },
      title = { Pedestrian Detection with Autoregressive Network Phases },
      booktitle = { In Proceeding of IEEE Computer Vision and Pattern Recognition },
      address = { Long Beach, CA },
      month = { June },
      year = { 2019 },
    }
  • Recurrent Flow-Guided Semantic Forecasting
    Adam M. Terwilliger, Garrick Brazil, Xiaoming Liu
    Proc. IEEE Winter Conference on Application of Computer Vision (WACV 2019), Hawaii, Jan. 2019
    Bibtex | PDF | arXiv | Poster | Project Webpage
  • @inproceedings{ recurrent-flow-guided-semantic-forecasting,
      author = { Adam M. Terwilliger and Garrick Brazil and Xiaoming Liu },
      title = { Recurrent Flow-Guided Semantic Forecasting },
      booktitle = { Proc. IEEE Winter Conference on Application of Computer Vision },
      address = { Hawaii },
      month = { January },
      year = { 2019 },
    }

2017

  • Illuminating Pedestrians via Simultaneous Detection & Segmentation
    Garrick Brazil, Xi Yin, Xiaoming Liu
    In Proceeding of International Conference on Computer Vision (ICCV 2017), Venice, Italy, Oct. 2017
    Bibtex | PDF | arXiv | Poster | Project Webpage
  • @inproceedings{ illuminating-pedestrians-via-simultaneous-detection-segmentation,
      author = { Garrick Brazil and Xi Yin and Xiaoming Liu },
      title = { Illuminating Pedestrians via Simultaneous Detection & Segmentation },
      booktitle = { In Proceeding of International Conference on Computer Vision },
      address = { Venice, Italy },
      month = { October },
      year = { 2017 },
    }