Single-Shot Object Detection with Enriched Semantics

@article{Zhang2018SingleShotOD,
  title={Single-Shot Object Detection with Enriched Semantics},
  author={Zhishuai Zhang and Siyuan Qiao and Cihang Xie and Wei Shen and Bo Wang and Alan L. Yuille},
  journal={2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year={2018},
  pages={5813-5821}
}
  • Zhishuai Zhang, Siyuan Qiao, +3 authors Alan L. Yuille
  • Published 2018
  • Computer Science
  • 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
  • We propose a novel single shot object detection network named Detection with Enriched Semantics (DES). Our motivation is to enrich the semantics of object detection features within a typical deep detector, by a semantic segmentation branch and a global activation module. The segmentation branch is supervised by weak segmentation ground-truth, i.e., no extra annotation is required. In conjunction with that, we employ a global activation module which learns relationship between channels and… CONTINUE READING

    Citations

    Publications citing this paper.
    SHOWING 1-10 OF 89 CITATIONS, ESTIMATED 90% COVERAGE

    Enriched Feature Guided Refinement Network for Object Detection

    VIEW 1 EXCERPT
    CITES METHODS

    Triply Supervised Decoder Networks for Joint Detection and Segmentation

    VIEW 3 EXCERPTS
    CITES BACKGROUND & METHODS

    PCL: Proposal Cluster Learning for Weakly Supervised Object Detection

    VIEW 1 EXCERPT
    CITES BACKGROUND

    Adaptively Dense Feature Pyramid Network for Object Detection

    VIEW 3 EXCERPTS
    CITES BACKGROUND
    HIGHLY INFLUENCED

    Learning Rich Features at High-Speed for Single-Shot Object Detection

    VIEW 1 EXCERPT
    CITES BACKGROUND

    FILTER CITATIONS BY YEAR

    2018
    2020

    CITATION STATISTICS

    • 7 Highly Influenced Citations

    • Averaged 30 Citations per year from 2018 through 2020

    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 30 REFERENCES

    Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation

    VIEW 2 EXCERPTS

    RON: Reverse Connection with Objectness Prior Networks for Object Detection

    You Only Look Once: Unified, Real-Time Object Detection

    VIEW 5 EXCERPTS
    HIGHLY INFLUENTIAL

    Object Detection via a Multi-region and Semantic Segmentation-Aware CNN Model

    VIEW 3 EXCERPTS

    R-FCN: Object Detection via Region-based Fully Convolutional Networks

    VIEW 7 EXCERPTS
    HIGHLY INFLUENTIAL

    SSD: Single Shot MultiBox Detector

    VIEW 7 EXCERPTS
    HIGHLY INFLUENTIAL

    Microsoft COCO: Common Objects in Context

    VIEW 10 EXCERPTS
    HIGHLY INFLUENTIAL

    Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

    VIEW 6 EXCERPTS
    HIGHLY INFLUENTIAL