未验证 提交 d1014c4c 编写于 作者: T Tian Zhi 提交者: GitHub

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## Highlights
- **Totally anchor-free:** FCOS completely avoids the complicated computation related to anchor boxes and all hyper-parameters of anchor boxes.
- **Better performance:** The very simple one-stage detector achieves much better performance (38.7 vs. 36.8 in AP with ResNet-50) than Faster R-CNN. Check out more models and experimental results [here](https://github.com/tianzhi0549/FCOS#models).
- **Better performance:** The very simple one-stage detector achieves much better performance (38.7 vs. 36.8 in AP with ResNet-50) than Faster R-CNN. Check out more models and experimental results [here](#models).
- **Faster training:** With the same hardwares, FCOS also requires less training hours (6.5h vs. 8.8h) than Faster R-CNN.
- **State-of-the-art performance:** Our best model based on ResNeXt-64x4d-101 and deformable convolutions achieves **49.0%** in AP on COCO test-dev (with multi-scale testing).
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