From 47662de873bffe1ed9ffd25aecccce967bd11b7c Mon Sep 17 00:00:00 2001 From: rajeevyasarla Date: Mon, 20 Apr 2020 17:24:19 -0400 Subject: [PATCH] Update README.md --- README.md | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/README.md b/README.md index 4716869..70f96de 100644 --- a/README.md +++ b/README.md @@ -4,6 +4,12 @@ Deblurring Face Images using Uncertainty Guided Multi-Stream Semantic Networks [Rajeev Yasarla](https://sites.google.com/view/rajeevyasarla/home), [Federico Perazzi](https://research.adobe.com/person/federico-perazzi/), [Vishal M. Patel](https://engineering.jhu.edu/ece/faculty/vishal-m-patel/) [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} +} 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.