Abstract
In recent years, deep convolutional neural networks have made breakthrough progress in object recognition and object detection tasks in the field of computer vision, and have achieved great results both in accuracy and speed. However, the detection of small objects is still difficult in the field of object detection, and the accuracy on the common dataset MS COCO is very low. This paper briefly reviews some work in multi-scale object detection algorithms, and then proposes a method of feature enhancement and fusion based on multi-scale feature maps, improving detection accuracy of small objects on MS COCO.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 39th Chinese Control Conference, CCC 2020 |
| Editors | Jun Fu, Jian Sun |
| Publisher | IEEE Computer Society |
| Pages | 7212-7217 |
| Number of pages | 6 |
| ISBN (Electronic) | 9789881563903 |
| DOIs | |
| Publication status | Published - Jul 2020 |
| Event | 39th Chinese Control Conference, CCC 2020 - Shenyang, China Duration: 27 Jul 2020 → 29 Jul 2020 |
Publication series
| Name | Chinese Control Conference, CCC |
|---|---|
| Volume | 2020-July |
| ISSN (Print) | 1934-1768 |
| ISSN (Electronic) | 2161-2927 |
Conference
| Conference | 39th Chinese Control Conference, CCC 2020 |
|---|---|
| Country/Territory | China |
| City | Shenyang |
| Period | 27/07/20 → 29/07/20 |
Keywords
- Feature Enhancement and Fusion
- Multi-scale
- Small Object Detection
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Xue, Z., Chen, W., & Li, J. (2020). Enhancement and Fusion of Multi-Scale Feature Maps for Small Object Detection. In J. Fu, & J. Sun (Eds.), Proceedings of the 39th Chinese Control Conference, CCC 2020 (pp. 7212-7217). Article 9189352 (Chinese Control Conference, CCC; Vol. 2020-July). IEEE Computer Society. https://doi.org/10.23919/CCC50068.2020.9189352