Wheat Head Detection Resources

AICrowd Global Wheat Challenge 2021 Solutions

AICrowd: Global Wheat Challenge 2021 solutions:

Kaggle Global WHeat Detection 2020 Solution

Kaggle Global Wheat Detection 2020

1st place solution

https://www.kaggle.com/c/global-wheat-detection/discussion/172418

Summary

  • Custom mosaic data augmentation
  • MixUp
  • Heavy augmentation
  • Data cleaning
  • EfficientDet
  • Faster RCNN FPN
  • Ensemble multi-scale model: Weighted-Boxes-Fusion, special thank @zfturbo
  • Test time augmentation(HorizontalFlip, VerticalFlip, Rotate90)
  • Pseudo labeling

2nd Place Solution

Link: https://www.kaggle.com/c/global-wheat-detection/discussion/175961

Repository: https://github.com/liaopeiyuan/TransferDet

3rd Place Solution

Code repository https://github.com/ufownl/global-wheat-detection

  • YOLOv3 from GluonCV
  • Use Darknet53 backbone
  • Use WBF over TTA
  • Use pseudo-labeling technique

Dataset Repository

Papers on Dataset

Papers on Solutions

Papers on object detection

Papers on Out Of Domain

Code Solutions

Yolo5 was not eligible for 2020 Wheat Head Challenge, but it can be used in 2021 Wheat Head Challenge [discussion]

YoloV5 vs EfficientDet

Articles

Other Wheat Dataset

Links

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