From a1a42eb88c367a382b2506e7819e57145a2ba901 Mon Sep 17 00:00:00 2001 From: Nathan Qin Date: Sat, 16 May 2020 13:57:40 -0600 Subject: [PATCH] input size and readme --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 8c49e40..25b1e88 100644 --- a/README.md +++ b/README.md @@ -11,7 +11,7 @@ __Contact__: xuebin[at]ualberta[dot]ca **(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 **U^2-Net** and [**BASNet**](https://github.com/NathanUA/BASNet). The [demo video](https://twitter.com/cyrildiagne/status/1256916982764646402) in twitter has achieved over **5M** views, which is phenomenal and shows 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 **U^2-Net** (Qin *et al*, PR 2020) and [**BASNet**](https://github.com/NathanUA/BASNet)(CVPR19, Qin *et al*, CVPR 2019). The [demo video](https://twitter.com/cyrildiagne/status/1256916982764646402) in twitter has achieved over **5M** views, which is phenomenal and shows us more probabilities of SOD. ## U^2-Net Results (173.6 MB)