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Object detector with enriched global context information

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Abstract

How to add more context information and bring more accurate detection is an important problem to be considered in object detection. In this paper, we propose a new object detector with enriched global context information by a pyramid feature pool module and several global activation blocks, named EGCI-Net, which is a one-stage object detector from scratch as DSOD.The global activation blocks are added into the backbone sub network of the detector to weaken the local information of the detected object feature maps and increase the global context of them. And the pyramid feature pool module produces multi-scale global context features to supervise the pyramid features by multi-scale global average pooling. Then the features obtained by the main structure are fused with the pyramid pooling features to merge into the final multibox detector. We have evaluated our detector on the Pascal VOC and MS COCO datasets. The experimental results show that our proposed detector achieves better results than DSOD and exceeds most of the existing excellent detectors, especially detects partially occluded objects and small objects well.

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Acknowledgment

This work is supported by the Natural Science Foundation of China (Grant 61572214 and U1536203).

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Authors and Affiliations

  1. School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China

    Jingjuan Guo, Yihao Luo & Tianjiang Wang

  2. School of Information Science and Technology, Jiujiang University, Jiujiang, 332005, China

    Jingjuan Guo & Zhiqiang Zhao

  3. School of Computer and Information Engineering, Henan University, Kaifeng, 475004, China

    Caihong Yuan

  4. International Joint Research Center For Data Science and High-Performance Computing, Guizhou University of Finance and Economics, Guiyang, 550025, China

    Ping Feng

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  1. Jingjuan Guo
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  2. Caihong Yuan
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  3. Zhiqiang Zhao
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  4. Ping Feng
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  5. Yihao Luo
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  6. Tianjiang Wang
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Correspondence to Jingjuan Guo or Tianjiang Wang.

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Guo, J., Yuan, C., Zhao, Z. et al. Object detector with enriched global context information. Multimed Tools Appl 79, 29551–29571 (2020). https://doi.org/10.1007/s11042-020-09500-6

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