From a8da78d4d39bb24e564ae44ca8fc4a826f76f53c Mon Sep 17 00:00:00 2001
From: lxq1000 <130724750+lxq1000@users.noreply.github.com>
Date: Tue, 5 Sep 2023 18:09:57 +0800
Subject: [PATCH] Update README.md
---
README.md | 20 ++++++++++++--------
1 file changed, 12 insertions(+), 8 deletions(-)
diff --git a/README.md b/README.md
index 98eee07..25be94d 100644
--- a/README.md
+++ b/README.md
@@ -8,28 +8,32 @@ Our design, the SwinFace, consists of a single shared backbone together with a s
To address the conflicts among multiple tasks and meet the different demands of tasks, a Multi-Level Channel Attention (MLCA) module is integrated into each task-specific analysis subnet, which can adaptively select the features from optimal levels and channels to perform the desired tasks.
Extensive experiments show that the proposed model has a better understanding of the face and achieves excellent performance for all tasks.
Especially, it achieves 90.97\% accuracy on RAF-DB and 0.22 $\epsilon$-error on CLAP2015, which are state-of-the-art results on facial expression recognition and age estimation respectively.
-![image](https://github.com/lxq1000/SwinFace/blob/main/pictures/SwinFace.png)
+
## Evaluate
Here are some test results. For detailed experimental information, please refer to our paper.
- Face Recognition
- ![image](https://github.com/lxq1000/SwinFace/blob/main/pictures/face%20recognition.png)
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+
- Facial Expression Recognition
-![image](https://github.com/lxq1000/SwinFace/blob/main/pictures/facial%20expression%20recognition.png)
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+
- Age Estimation
-![image](https://github.com/lxq1000/SwinFace/blob/main/pictures/age%20estimation.png)
-- Facial Attribute Estimation
-![image](https://github.com/lxq1000/SwinFace/blob/main/pictures/facial%20attribute%20estimation.png)
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+- Facial Attribute Estimation
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## Train and Inference
-The "train.sh" file provides the necessary commands for training the model.
+The `train.sh` file provides the necessary commands for training the model.
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+The `inference.py` file provides an example of using SwinFace for inference.
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-The "inference.py" provides an example of using SwinFace for inference.