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input size and readme

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Nathan Qin 2020-05-16 13:51:31 -06:00
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@ -5,13 +5,13 @@ The code for our newly accepted paper in Pattern Recognition 2020:
__Contact__: xuebin[at]ualberta[dot]ca
## News
## News !!!
(2020-May-16) The official paper of U^2-Net (U square net) [PDF in elsevier](https://www.sciencedirect.com/science/article/pii/S0031320320302077?dgcid=author) is now available. If you are not able to access that, please feel free to drop me an email.
**(2020-May-16)** The official paper of **U^2-Net (U square net)** [PDF in elsevier](https://www.sciencedirect.com/science/article/pii/S0031320320302077?dgcid=author) is now available. If you are not able to access that, please feel free to drop me an email.
(2020-May-16) We fix the upsampling issue of the network. Now, the model should be able to handle *arbitrary* input size. (Tips: This modification is to facilitate the retraining of U^2-Net on your own datasets. When using our pre-trained model on SOD datasets, please keep the input size as 320x32 to guarantee the performance.)
**(2020-May-16)** We fixed the upsampling issue of the network. Now, the model should be able to handle **arbitrary input size**. (Tips: This modification is to facilitate the retraining of U^2-Net on your own datasets. When using our pre-trained model on SOD datasets, please keep the input size as 320x32 to guarantee the performance.)
(2020-May-16) We highly appreciate Cyril Diagne for building this fantastic AR project: [AR Copy and Paste](https://github.com/cyrildiagne/ar-cutpaste) using our [BASNet](https://github.com/NathanUA/BASNet) and U^2-Net. The [demo video](https://twitter.com/cyrildiagne/status/1256916982764646402) has achieved over 5M views, which is phenomenal and show us more probabilities of SOD.
**(2020-May-16)** We highly appreciate Cyril Diagne for building this fantastic AR project: [AR Copy and Paste](https://github.com/cyrildiagne/ar-cutpaste) using our [BASNet](https://github.com/NathanUA/BASNet) and U^2-Net. The [demo video](https://twitter.com/cyrildiagne/status/1256916982764646402) has achieved over **5M** views, which is phenomenal and show us more probabilities of SOD.
## U^2-Net Results (173.6 MB)