### GIoU 参考文献及本科论文格式写法
#### 1. GIoU 的参考文献
GIoU（Generalized Intersection over Union）的提出基于一篇发表于 CVPR 2019 的论文，标题为《Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regression》[^1]。这篇论文详细介绍了 GIoU 的定义、计算方法及其在目标检测中的应用。
以下是 GIoU 的主要参考文献：
- Rezatofighi, H., Tsoi, N., Gwak, J., Sadeghian, A., Reid, I., & Savarese, S. (2019). Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regression. *CVPR 2019*. [PDF](https://arxiv.org/abs/1902.09630)[^1]
此外，后续研究中提出了 DIoU 和 CIoU，这些改进版本进一步提升了边界框回归的性能。相关文献包括：
- Zheng, Z., Dai, J., & Sun, Y. (2020). Distance-IoU Loss: Faster and Better Learning for Bounding Box Regression. *AAAI 2020*. [PDF](https://arxiv.org/abs/1911.08287)[^2]
- Zheng, Z., Dai, J., & Sun, Y. (2021). Towards Real-Time Object Detection with Region Proposal Networks. *TPAMI 2021*. [PDF](https://arxiv.org/abs/2005.00064)[^3]
#### 2. 本科论文参考文献格式写法
根据本科论文的要求，参考文献通常需要按照特定的格式书写。以下是一些常见的参考文献格式示例：
##### （1）APA 格式
Rezatofighi, H., Tsoi, N., Gwak, J., Sadeghian, A., Reid, I., & Savarese, S. (2019). Generalized intersection over union: A metric and a loss for bounding box regression. *Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)*, 658–666. https://doi.org/10.1109/CVPR.2019.00075[^1]
##### （2）IEEE 格式
H. Rezatofighi, N. Tsoi, J. Gwak, A. Sadeghian, I. Reid, and S. Savarese, "Generalized intersection over union: A metric and a loss for bounding box regression," in *Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)*, 2019, pp. 658-666[^1].
##### （3）MLA 格式
Rezatofighi, Hamid, et al. "Generalized Intersection Over Union: A Metric and A Loss for Bounding Box Regression." *Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)*, 2019, pp. 658-666.
##### （4）GB/T 7714 格式
Rezatofighi H, Tsoi N, Gwak J, et al. Generalized intersection over union: A metric and a loss for bounding box regression[J]. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019: 658-666[^1].
#### 3. 示例代码
以下是 GIoU 的 Python 实现示例：
```python
import torch
def generalized_iou_loss(pred, target):
x1 = torch.max(pred[:, 0], target[:, 0])
y1 = torch.max(pred[:, 1], target[:, 1])
x2 = torch.min(pred[:, 2], target[:, 2])
y2 = torch.min(pred[:, 3], target[:, 3])
w = (x2 - x1 + 1).clamp(min=0)
h = (y2 - y1 + 1).clamp(min=0)
intersection = w * h
area_pred = (pred[:, 2] - pred[:, 0] + 1) * (pred[:, 3] - pred[:, 1] + 1)
area_target = (target[:, 2] - target[:, 0] + 1) * (target[:, 3] - target[:, 1] + 1)
union = area_pred + area_target - intersection
iou = intersection / union
x1_c = torch.min(pred[:, 0], target[:, 0])
y1_c = torch.min(pred[:, 1], target[:, 1])
x2_c = torch.max(pred[:, 2], target[:, 2])
y2_c = torch.max(pred[:, 3], target[:, 3])
c_area = (x2_c - x1_c + 1) * (y2_c - y1_c + 1)
giou = iou - ((c_area - union) / c_area)
return 1 - giou.mean()
```
#### 4. 注意事项
在撰写本科论文时，确保参考文献部分符合导师或学校要求的格式规范。如果不确定具体格式，可以咨询导师或参考学校提供的写作指南。
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