Skip to content

Latest commit

 

History

History
79 lines (57 loc) · 4.43 KB

README.md

File metadata and controls

79 lines (57 loc) · 4.43 KB
Raw

Attention-guided-Feature-Fusion-for-SOD

Code of paper Attention-guided Feature Fusion for Small Object Detection

Overall

AFFM

Attention guided feature fusion module for contextual and spatial alignment of adjacent feature maps.

AFFM

SFSM

Shallow Feature supplement module for small object feature reinforcement using cross-attention.

SFSM

Installation

For MMYOLO, please see https://mmyolo.readthedocs.io/

Placing files in our repository to the appropriate place like MMYOLO, just overwrite or copy is enough.

Usage

Same as MMYOLO, please see 15 minutes to get started with MMYOLO object detection — MMYOLO 0.5.0 documentation and our config file is in configs/att-guided_yolov6s/yolov6_s_myneck.py.

We used a very simple and intuitive way to present the code, with all modules plug and play.

Result

TABLE I. Experimental results on COCO 2017 test-dev

Method Backbone AP AP50 AP75 APS APM APL
ABFPN ResNet-50 38.6 61.3 - 24.4 42.0 49.9
YOLOX-s Modified CSPNet 40.5 59.7 44.2 24.1 45.2 54.0
CL-FPN ResNet-101 41.0 62.9 44.5 23.4 44.0 52.0
AC-FPN ResNet-101 42.4 65.1 46.2 25.0 45.2 53.2
PPYOLOE-s CSPRepResNet 43.1 60.5 46.6 23.2 46.4 56.9
YOLOv6-s (baseline) EfficientRep 43.5 60.4 46.8 23.7 48.9 59.9
YOLOv8-s Modified CSPNet C2f 44.2 61.1 47.9 25.9 49.1 60.1
Ours EfficientRep 44.3 61.8 47.4 24.6 49.6 59.9

TABLE II. Experimental results on VisDrone2017

Method AP AP50 AP75 APS APM APL Epoch
YOLOX-s 17.6 33.9 16.2 9.0 27.7 45.0 50
YOLOv6-s (baseline) 19.5 33.2 19.5 9.7 30.8 47.4 50
PPYOLOE-s 20.0 34.6 20.0 10.5 31.5 51.0 50
Zhan et al. 20.6 37.6 - - - - 300
YOLOv8-s 20.9 36.8 20.7 10.7 33.2 49.7 50
FE-YOLOv5 21.0 37.0 20.7 13.2 29.5 39.1 300
AMMFN 24.7 48.1 22.9 17.0 43.6 60.1 300
Ours 24.1 37.5 24.7 14.2 33.8 49.2 50
① The bold ones mean the top performance.
② Test on RTX3080Ti, after 50 epochs training.

Contact

jiaxiongyang at tongji dot edu dot cn

Citation

If you find this project useful for your research, please use the following BibTeX entry.

@INPROCEEDINGS{10355735,
  author={Yang, Jiaxiong and Liu, Xianhui and Liu, Zhuang},
  booktitle={2023 IEEE International Conference on Imaging Systems and Techniques (IST)}, 
  title={Attention-guided Feature Fusion for Small Object Detection}, 
  year={2023},
  pages={1-6},
  doi={10.1109/IST59124.2023.10355735}}