Deep Photo Cropper and Enhancer
- URL: http://arxiv.org/abs/2008.00634v1
- Date: Mon, 3 Aug 2020 03:50:20 GMT
- Title: Deep Photo Cropper and Enhancer
- Authors: Aaron Ott, Amir Mazaheri, Niels D. Lobo, Mubarak Shah
- Abstract summary: We propose a new type of image enhancement problem: to crop an image which is embedded within a photo.
We split our proposed approach into two deep networks: deep photo cropper and deep image enhancer.
In the photo cropper network, we employ a spatial transformer to extract the embedded image.
In the photo enhancer, we employ super-resolution to increase the number of pixels in the embedded image.
- Score: 65.11910918427296
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: This paper introduces a new type of image enhancement problem. Compared to
traditional image enhancement methods, which mostly deal with pixel-wise
modifications of a given photo, our proposed task is to crop an image which is
embedded within a photo and enhance the quality of the cropped image. We split
our proposed approach into two deep networks: deep photo cropper and deep image
enhancer. In the photo cropper network, we employ a spatial transformer to
extract the embedded image. In the photo enhancer, we employ super-resolution
to increase the number of pixels in the embedded image and reduce the effect of
stretching and distortion of pixels. We use cosine distance loss between image
features and ground truth for the cropper and the mean square loss for the
enhancer. Furthermore, we propose a new dataset to train and test the proposed
method. Finally, we analyze the proposed method with respect to qualitative and
quantitative evaluations.
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