The Global Fight League (GFL), originally announced as the World Fight League (WFL), [4][5] is an American mixed martial arts (MMA) league that launched in 2025. [6]

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这两个方法，即QFL和DFL的作用是正交的，他们的增益互不影响，所以结合使用更香（我们统一称之为GFL）。 我们在基于Resnet50的backbone的ATSS（CVPR20）的baseline上1x训练无multi-scale直接基本无cost地提升了一个点，在COCO validation上从 39.2 提到了 40.2 AP。

W is the only operator who can place an offensive summon (mines in her case) on tiles where enemies are currently standing on. If placed there, these mines will explode as soon as they are planted. Even if the attack misses, like with Tiacuah Brave or Manfred, they can still be stunned if they are not immune to it.

2020年6月8日 · We then propose Generalized Focal Loss (GFL) that generalizes Focal Loss from its discrete form to the continuous version for successful optimization. On COCO test-dev, GFL achieves 45.0\% AP using ResNet-101 backbone, surpassing state-of-the-art SAPD (43.5\%) and ATSS (43.6\%) with higher or comparable inference speed, under the same backbone ...

而在GFL中，却用到IOU指导分类训练，具体来说，用预测的边界框与定位标签计算的IOU，不仅用于计算IOU loss，还用来作为分类的标签，即one-hot分类标签的1改成IOU，再计算分类损失。

2020年12月26日 · mmdetection 已经实现了GFL，简单的说是继承的onestage，loss改成作者提出的qfl+dfl，正负样本选择继承ATSS。 在ATSS中，作者对基于中心点的FCOS和基于anchor的retinanet进行各种对比试验，发现anchor free和base anchor的本质区别是正负样本的选择，于是提出了一种更为合适的正负样本策略，这里可以参考我前面那一篇博客： ATSS。 算法再一次提升，在这个基础之上PAA又做了改进。 至此ATSS和PAA一套效果已经大幅度超过了FasterRcnn …

2022年10月30日 · 作者将GFLv2（包括本文提出的DGQP结构，和GFL v1中的一般分布表示）应用到其它dense 目标检测模型 中，结果如下所示，可以看出在其它常见的检测模型中也都获得了精度提升。

2020年11月12日 · 所以论文对Focal loss进行拓展，提出了GFL (Generalized Focal Los)，能够处理连续值目标的全局优化问题。 GFL包含QFL (Quality Focal Los)和DFL ( Distribution Focal Los)两种具体形式，QFL用于优化难样本同时预测对应类别的连续值分数，而DFL则通过对预测框位置进行general分布的建模 ...

2024年12月11日 · On Wednesday, Darren Owen announced that a new, team-based MMA league, the Global Fight League, will launch its first season starting in April of 2025.