From 8e8009f053545509fd98ae44639d43f302cbe0c3 Mon Sep 17 00:00:00 2001
From: WZMIAOMIAO <605169423@qq.com>
Date: Tue, 17 May 2022 17:59:17 +0800
Subject: [PATCH 1/2] update paper link for FCOS refence

---
 torchvision/models/detection/fcos.py | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/torchvision/models/detection/fcos.py b/torchvision/models/detection/fcos.py
index 684b52100db..379794911b8 100644
--- a/torchvision/models/detection/fcos.py
+++ b/torchvision/models/detection/fcos.py
@@ -201,7 +201,10 @@ def forward(self, x: List[Tensor]) -> Tensor:
 
 class FCOSRegressionHead(nn.Module):
     """
-    A regression head for use in FCOS.
+    A regression head for use in FCOS, which combines regression branch and center-ness branch.
+    This can obtain better performance.
+
+    Reference: `FCOS: A simple and strong anchor-free object detector(updated version) <https://arxiv.org/abs/2006.09214>`_.
 
     Args:
         in_channels (int): number of channels of the input feature
@@ -680,6 +683,7 @@ def fcos_resnet50_fpn(
     Constructs a FCOS model with a ResNet-50-FPN backbone.
 
     Reference: `FCOS: Fully Convolutional One-Stage Object Detection <https://arxiv.org/abs/1904.01355>`_.
+               `FCOS: A simple and strong anchor-free object detector(updated version) <https://arxiv.org/abs/2006.09214>`_.
 
     The input to the model is expected to be a list of tensors, each of shape ``[C, H, W]``, one for each
     image, and should be in ``0-1`` range. Different images can have different sizes.

From 1ec9cad67cd739e8bff8b772fdf5685017d9be99 Mon Sep 17 00:00:00 2001
From: WZMIAOMIAO <605169423@qq.com>
Date: Tue, 17 May 2022 19:53:56 +0800
Subject: [PATCH 2/2] remove 'updated version'

---
 torchvision/models/detection/fcos.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/torchvision/models/detection/fcos.py b/torchvision/models/detection/fcos.py
index 379794911b8..3544ea3117e 100644
--- a/torchvision/models/detection/fcos.py
+++ b/torchvision/models/detection/fcos.py
@@ -204,7 +204,7 @@ class FCOSRegressionHead(nn.Module):
     A regression head for use in FCOS, which combines regression branch and center-ness branch.
     This can obtain better performance.
 
-    Reference: `FCOS: A simple and strong anchor-free object detector(updated version) <https://arxiv.org/abs/2006.09214>`_.
+    Reference: `FCOS: A simple and strong anchor-free object detector <https://arxiv.org/abs/2006.09214>`_.
 
     Args:
         in_channels (int): number of channels of the input feature
@@ -683,7 +683,7 @@ def fcos_resnet50_fpn(
     Constructs a FCOS model with a ResNet-50-FPN backbone.
 
     Reference: `FCOS: Fully Convolutional One-Stage Object Detection <https://arxiv.org/abs/1904.01355>`_.
-               `FCOS: A simple and strong anchor-free object detector(updated version) <https://arxiv.org/abs/2006.09214>`_.
+               `FCOS: A simple and strong anchor-free object detector <https://arxiv.org/abs/2006.09214>`_.
 
     The input to the model is expected to be a list of tensors, each of shape ``[C, H, W]``, one for each
     image, and should be in ``0-1`` range. Different images can have different sizes.