AI/U-2-Net
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@ -16,11 +16,11 @@ __Contact__: xuebin[at]ualberta[dot]ca
**(2021-Apr-29)** Thanks [**Jonathan Benavides Vallejo**](https://www.linkedin.com/in/jonathanbv/) for releasing his App [**LensOCR: Extract Text & Image**](https://apps.apple.com/ch/app/lensocr-extract-text-image/id1549961729?l=en&mt=12), which uses U^2-Net for extracting the image foreground. **(2021-Apr-29)** Thanks [**Jonathan Benavides Vallejo**](https://www.linkedin.com/in/jonathanbv/) for releasing his App [**LensOCR: Extract Text & Image**](https://apps.apple.com/ch/app/lensocr-extract-text-image/id1549961729?l=en&mt=12), which uses U^2-Net for extracting the image foreground.
![LensOCR APP](figures/LensOCR.PNG) ![LensOCR APP](figures/LensOCR.jpg)
**(2021-Apr-18)** Thanks [**Andrea Scuderi**](https://www.linkedin.com/in/andreascuderi/) for releasing his App [**Clipping Camera**](https://apps.apple.com/us/app/clipping-camera/id1548192169?ign-mpt=uo%3D2), which is an U^2-Net driven realtime camera app and "is able to detect relevant object from the scene and clip them to apply fancy filters". **(2021-Apr-18)** Thanks [**Andrea Scuderi**](https://www.linkedin.com/in/andreascuderi/) for releasing his App [**Clipping Camera**](https://apps.apple.com/us/app/clipping-camera/id1548192169?ign-mpt=uo%3D2), which is an U^2-Net driven realtime camera app and "is able to detect relevant object from the scene and clip them to apply fancy filters".
![Clipping Camera APP](figures/clipping_camera.png) ![Clipping Camera APP](figures/clipping_camera.jpg)
**(2021-Mar-17)** [**Dennis Bappert**](https://github.com/dennisbappert) re-trained the U^2-Net model for [**human portrait matting**](https://github.com/dennisbappert/u-2-net-portrait). The results look very promising and he also provided the details of the training process and data generation(and augmentation) strategy, which are inspiring. **(2021-Mar-17)** [**Dennis Bappert**](https://github.com/dennisbappert) re-trained the U^2-Net model for [**human portrait matting**](https://github.com/dennisbappert/u-2-net-portrait). The results look very promising and he also provided the details of the training process and data generation(and augmentation) strategy, which are inspiring.