Source Code of AAAI22-2171

Introduction

The source code includes training and inference procedures for the proposed method of the paper submitted to the Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI 2022) with title "Shape-Adaptive Selection and Measurement for Oriented Object Detection" (ID: 2171).

The the effectiveness of the proposed method is verified on two baseline methods. Corresponding source code and configurations reside in following two sub-directories:

• sasm_reppoints: the implementation and verification using RepPoints as baseline;
• sasm_s2anet: the implementation and verification using s2anet(https://ieeexplore.ieee.org/document/9377550) as baseline.

We provide only the source code related to the proposed method in the sub-directories so that reviewers can check them quickly and conveniently.

Please refer to the README.md file in each sub-directory for the detailed instructions of usage.

Introduction

| Method | Assignment | Reg. Loss | Tricks | mAP | | :--------: | :--------: | :-----------: | :---------: | :---: | | RepPoints | MaxIoU | GIoU | - | 70.46 | | RepPoints | SASM | BCLoss + GIoU | - | 74.27 | | RepPoints | SASM | BCLoss + GIoU | MS training | 77.19 | | s2anet | SASM | Smooth L1 | MS training | 79.17 |

Reference

1、https://github.com/open-mmlab/mmdetection

2、https://github.com/LiWentomng/OrientedRepPoints

3、https://github.com/SDL-GuoZonghao/BeyondBoundingBox

4、https://github.com/csuhan/s2anet

5、https://github.com/sfzhang15/ATSS