From 1c1a8011f63ff2f358de5ded9470281d5ad241a2 Mon Sep 17 00:00:00 2001 From: rajeevyasarla Date: Mon, 20 Apr 2020 17:25:43 -0400 Subject: [PATCH] Update README.md --- README.md | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/README.md b/README.md index 6f7be19..2914465 100644 --- a/README.md +++ b/README.md @@ -5,12 +5,12 @@ Deblurring Face Images using Uncertainty Guided Multi-Stream Semantic Networks [Paper Link](https://arxiv.org/pdf/1907.13106.pdf) -@article{yasarla2019deblurring, - title={Deblurring Face Images using Uncertainty Guided Multi-Stream Semantic Networks}, - author={Yasarla, Rajeev and Perazzi, Federico and Patel, Vishal M}, - journal={arXiv preprint arXiv:1907.13106}, - year={2019} -} + @article{yasarla2019deblurring, + title={Deblurring Face Images using Uncertainty Guided Multi-Stream Semantic Networks}, + author={Yasarla, Rajeev and Perazzi, Federico and Patel, Vishal M}, + journal={arXiv preprint arXiv:1907.13106}, + year={2019} + } We propose a novel multi-stream architecture and training methodology that exploits semantic labels for facial image deblurring. The proposed Uncertainty Guided MultiStream Semantic Network (UMSN) processes regions belonging to each semantic class independently and learns to combine their outputs into the final deblurred result. Pixel-wise semantic labels are obtained using a segmentation network. A predicted confidence measure is used during training to guide the network towards challenging regions of the human face such as the eyes and nose. The entire network is trained in an endto-end fashion.