@inproceedings{1351f8faabcf4b7b95d597b38f454bb8,
title = "CrossNet: An end-to-end reference-based super resolution network using cross-scale warping",
abstract = "The Reference-based Super-resolution (RefSR) super-resolves a low-resolution (LR) image given an external high-resolution (HR) reference image, where the reference image and LR image share similar viewpoint but with significant resolution gap (8{\texttimes}). Existing RefSR methods work in a cascaded way such as patch matching followed by synthesis pipeline with two independently defined objective functions, leading to the inter-patch misalignment, grid effect and inefficient optimization. To resolve these issues, we present CrossNet, an end-to-end and fully-convolutional deep neural network using cross-scale warping. Our network contains image encoders, cross-scale warping layers, and fusion decoder: the encoder serves to extract multi-scale features from both the LR and the reference images; the cross-scale warping layers spatially aligns the reference feature map with the LR feature map; the decoder finally aggregates feature maps from both domains to synthesize the HR output. Using cross-scale warping, our network is able to perform spatial alignment at pixel-level in an end-to-end fashion, which improves the existing schemes [1, 2] both in precision (around 2 dB{\textendash}4{\^A} dB) and efficiency (more than 100 times faster).",
keywords = "Encoder-decoder, Image synthesis, Light field imaging, Optical flow, Reference-based Super Resolution",
author = "Haitian Zheng and Mengqi Ji and Haoqian Wang and Yebin Liu and Lu Fang",
note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2018.; 15th European Conference on Computer Vision, ECCV 2018 ; Conference date: 08-09-2018 Through 14-09-2018",
year = "2018",
doi = "10.1007/978-3-030-01231-1\_6",
language = "英语",
isbn = "9783030012304",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "87--104",
editor = "Martial Hebert and Yair Weiss and Vittorio Ferrari and Cristian Sminchisescu",
booktitle = "Computer Vision {\textendash} ECCV 2018 - 15th European Conference, 2018, Proceedings",
address = "德国",
}