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Image Segmentation

  1. summary image

    SeaBird: Segmentation in Bird’s View with Dice Loss Improves Monocular 3D Detection of Large Objects

    Abhinav Kumar, Yuliang Guo, Xinyu Huang, Liu Ren and Xiaoming Liu

    Monocular 3D detectors achieve remarkable performance on cars and smaller objects. However, their performance drops on larger objects, leading to fatal accidents. Some attribute the failures to training data scarcity or receptive field requirements of large objects. In this paper, we highlight this understudied problem of generalization to large objects ...

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    Keywords: 3D Object Detection, Image Segmentation

  2. summary image

    The Edge of Depth: Explicit Constraints between Segmentation and Depth

    Shengjie Zhu, Garrick Brazil, Xiaoming Liu

    In this work we study the mutual benefits of two common computer vision tasks, self-supervised depth estimation and semantic segmentation from images. For example, to help unsupervised monocular depth estimation, constraints from semantic segmentation has been explored implicitly such as sharing and transforming features. In contrast, we propose to explicitly ...

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    Keywords: Depth Prediction, Image Segmentation, Semantic Segmentation

  3. summary image

    Recurrent Flow-Guided Semantic Forecasting

    Adam M. Terwilliger, Garrick Brazil, Xiaoming Liu

    Understanding the world around us and making decisions about the future is a critical component to human intelligence. As autonomous systems continue to develop, their ability to reason about the future will be the key to their success. Semantic anticipation is a relatively under-explored area for which autonomous vehicles could ...

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    Keywords: Forecasting, Semantic Segmentation, Image Segmentation

  4. 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, Object Detection, Image Segmentation

  5. summary image

    Image Segmentation of Mesenchymal Stem Cells in Diverse Culturing Conditions

    Muhammad Jamal Afridi, Chun Liu, Christina Chan, Seungik Baek, Xiaoming Liu

    Researchers in the areas of regenerative medicine and tissue engineering have an enormous interest in understanding the relationship of different sets of culturing conditions and applied mechanical stimuli on the behavior of Mesenchymal Stem Cells (MSCs). However, it remains a challenge to design a general tool to perform automatic cell ...

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    Keywords: Medical Imaging, Image Segmentation, Application, Semantic Segmentation

2024

  • SeaBird: Segmentation in Bird's View with Dice Loss Improves Monocular 3D Detection of Large Objects
    Abhinav Kumar, Yuliang Guo, Xinyu Huang, Liu Ren, Xiaoming Liu
    In Proceeding of IEEE Computer Vision and Pattern Recognition (CVPR 2024), Seattle, WA, Jun. 2024
    Bibtex | PDF | arXiv | Supplemental | Project Webpage | Code
  • @inproceedings{ seabird-segmentation-in-birds-view-with-dice-loss-improves-monocular-3d-detection-of-large-objects,
      author = { Abhinav Kumar and Yuliang Guo and Xinyu Huang and Liu Ren and Xiaoming Liu },
      title = { SeaBird: Segmentation in Bird's View with Dice Loss Improves Monocular 3D Detection of Large Objects },
      booktitle = { In Proceeding of IEEE Computer Vision and Pattern Recognition },
      address = { Seattle, WA },
      month = { June },
      year = { 2024 },
    }

2020

  • The Edge of Depth: Explicit Constraints between Segmentation and Depth
    Shengjie Zhu, Garrick Brazil, Xiaoming Liu
    In Proceeding of IEEE Computer Vision and Pattern Recognition (CVPR 2020), Seattle, WA, Jun. 2020
    Bibtex | PDF | arXiv | Supplemental | Project Webpage | Code | Video
  • @inproceedings{ the-edge-of-depth-explicit-constraints-between-segmentation-and-depth,
      author = { Shengjie Zhu and Garrick Brazil and Xiaoming Liu },
      title = { The Edge of Depth: Explicit Constraints between Segmentation and Depth },
      booktitle = { In Proceeding of IEEE Computer Vision and Pattern Recognition },
      address = { Seattle, WA },
      month = { June },
      year = { 2020 },
    }

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 | Code
  • @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

  • Joint Multi-Leaf Segmentation, Alignment, and Tracking from Fluorescence Plant Videos
    Xi Yin, Xiaoming Liu, Jin Chen, David M. Kramer
    IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 40, No. 6, pp.1411-1423, , Jul. 2017
    Bibtex | PDF | arXiv | Project Webpage | Code
  • @article{ joint-multi-leaf-segmentation-alignment-and-tracking-from-fluorescence-plant-videos,
      author = { Xi Yin and Xiaoming Liu and Jin Chen and David M. Kramer },
      title = { Joint Multi-Leaf Segmentation, Alignment, and Tracking from Fluorescence Plant Videos },
      journal = { IEEE Transactions on Pattern Analysis and Machine Intelligence },
      volume = { 40 },
      number = { 6 },
      month = { July },
      year = { 2017 },
      pages = { 1411--1423 },
    }
  • 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 | Code
  • @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 },
    }

2016

2014

  • Image Segmentation of Mesenchymal Stem Cells in Diverse Culturing Conditions
    Muhammad Jamal Afridi, Chun Liu, Christina Chan, Seungik Baek, Xiaoming Liu
    Proc. IEEE Winter Conference on Application of Computer Vision (WACV 2014), Steamboat Springs, USA, Mar. 2014
    Bibtex | PDF | Project Webpage
  • @inproceedings{ image-segmentation-of-mesenchymal-stem-cells-in-diverse-culturing-conditions,
      author = { Muhammad Jamal Afridi and Chun Liu and Christina Chan and Seungik Baek and Xiaoming Liu },
      title = { Image Segmentation of Mesenchymal Stem Cells in Diverse Culturing Conditions },
      booktitle = { Proc. IEEE Winter Conference on Application of Computer Vision },
      address = { Steamboat Springs, USA },
      month = { March },
      year = { 2014 },
    }

2011

  • Automatic Surveillance Video Matting Using a Shape Prior
    Ting Yu, Xiaoming Liu, Ser-Nam Lim, Nils Krahnstoever, Peter Tu
    Proc. 11th IEEE Workshop on Visual Surveillance (ICCV 2011), Barcelona, Spain, Sep. 2011
    Bibtex | PDF
  • @inproceedings{ automatic-surveillance-video-matting-using-a-shape-prior,
      author = { Ting Yu and Xiaoming Liu and Ser-Nam Lim and Nils Krahnstoever and Peter Tu },
      title = { Automatic Surveillance Video Matting Using a Shape Prior },
      booktitle = { Proc. 11th IEEE Workshop on Visual Surveillance },
      address = { Barcelona, Spain },
      month = { September },
      year = { 2011 },
    }