diff --git a/README.md b/README.md
index 471ea88c5122ca46d418aba54edae45b65191d6a..d02c6f72ae3508bff553b17236e71bdb6a66637f 100644
--- a/README.md
+++ b/README.md
@@ -178,8 +178,8 @@ DeepSparkHub甄选上百个应用算法和模型，覆盖AI和通用计算各领
 [ContextNet](cv/semantic_segmentation/contextnet/pytorch/README.md)  | PyTorch | COCO
 [DabNet](cv/semantic_segmentation/dabnet/pytorch/README.md)  | PyTorch | COCO
 [DANet](cv/semantic_segmentation/danet/pytorch/README.md)  | PyTorch | COCO
-[DeepLab](cv/semantic_segmentation/deeplabv3/pytorch/README.md)  | PyTorch | COCO
-[DeepLab](cv/semantic_segmentation/deeplabv3/paddlepaddle/README.md)  | PaddlePaddle | COCO
+[DeepLabV3](cv/semantic_segmentation/deeplabv3/pytorch/README.md)  | PyTorch | COCO
+[DeepLabV3](cv/semantic_segmentation/deeplabv3/paddlepaddle/README.md)  | PaddlePaddle | COCO
 [DeepLabV3](cv/semantic_segmentation/deeplabv3/MindSpore/README.md)  | MindSpore | VOC
 [DeepLabV3+](cv/semantic_segmentation/deeplabv3plus/paddlepaddle/README.md)  | PaddlePaddle | COCO
 [DenseASPP](cv/semantic_segmentation/denseaspp/pytorch/README.md)  | PyTorch | COCO
diff --git a/cv/semantic_segmentation/deeplabv3/paddlepaddle/README.md b/cv/semantic_segmentation/deeplabv3/paddlepaddle/README.md
index c8043bbd8264bda5c7a8929dab65e9f2e3f93aff..a049d3718e8d962b8980df7290f0a8fbc5d110b6 100644
--- a/cv/semantic_segmentation/deeplabv3/paddlepaddle/README.md
+++ b/cv/semantic_segmentation/deeplabv3/paddlepaddle/README.md
@@ -1,8 +1,8 @@
-# DeepLab
+# DeepLabV3
 
 ## Model description
 
-DeepLabv3 is a semantic segmentation architecture that improves upon DeepLabv2 with several modifications. 
+DeepLabV3 is a semantic segmentation architecture that improves upon DeepLabV2 with several modifications.
 To handle the problem of segmenting objects at multiple scales, modules are designed which employ atrous convolution in cascade or in parallel to capture multi-scale context by adopting multiple atrous rates. 
 
 ## Step 1: Installing
diff --git a/cv/semantic_segmentation/deeplabv3/pytorch/README.md b/cv/semantic_segmentation/deeplabv3/pytorch/README.md
index c0427db4b7c40ef69b988e84c1b1715ac3ac5350..37b073c025fb28ca0cbd1f17706a495a36993466 100644
--- a/cv/semantic_segmentation/deeplabv3/pytorch/README.md
+++ b/cv/semantic_segmentation/deeplabv3/pytorch/README.md
@@ -1,8 +1,8 @@
-# DeepLab
+# DeepLabV3
 
 ## Model description
 
-DeepLabv3 is a semantic segmentation architecture that improves upon DeepLabv2 with several modifications. 
+DeepLabV3 is a semantic segmentation architecture that improves upon DeepLabV2 with several modifications.
 To handle the problem of segmenting objects at multiple scales, modules are designed which employ atrous convolution in cascade or in parallel to capture multi-scale context by adopting multiple atrous rates. 
 
 ## Step 1: Installing
diff --git a/cv/semantic_segmentation/deeplabv3plus/paddlepaddle/README.md b/cv/semantic_segmentation/deeplabv3plus/paddlepaddle/README.md
index a00aa6c524fae7512ed8a5c2147fd06a8769f285..3f3207f5e96173e400c6f76962c13ef74bf8f81e 100644
--- a/cv/semantic_segmentation/deeplabv3plus/paddlepaddle/README.md
+++ b/cv/semantic_segmentation/deeplabv3plus/paddlepaddle/README.md
@@ -2,7 +2,7 @@
 
 ## Model description
 
-DeepLabv3 is a semantic segmentation architecture that improves upon DeepLabv2 with several modifications. 
+DeepLabV3 is a semantic segmentation architecture that improves upon DeepLabV2 with several modifications.
 To handle the problem of segmenting objects at multiple scales, modules are designed which employ atrous convolution in cascade or in parallel to capture multi-scale context by adopting multiple atrous rates. 
 
 ## Step 1: Installing
@@ -62,4 +62,4 @@ python3 -u -m paddle.distributed.launch --gpus 0,1,2,3 train.py \
 
 | GPU         | FP32                                 |
 | ----------- | ------------------------------------ |
-| 8 cards     | mIoU =80.42%                         |
\ No newline at end of file
+| 8 cards     | mIoU =80.42%                         |