Search Results for author: Yun Cao

Found 10 papers, 5 papers with code

Spectrum-to-Kernel Translation for Accurate Blind Image Super-Resolution

no code implementations NeurIPS 2021 Guangpin Tao, Xiaozhong Ji, Wenzhuo Wang, Shuo Chen, Chuming Lin, Yun Cao, Tong Lu, Donghao Luo, Ying Tai

In this paper, we propose a novel blind SR framework to super-resolve LR images degraded by arbitrary blur kernel with accurate kernel estimation in frequency domain.

Image Super-Resolution Translation

Frequency Consistent Adaptation for Real World Super Resolution

no code implementations18 Dec 2020 Xiaozhong Ji, Guangpin Tao, Yun Cao, Ying Tai, Tong Lu, Chengjie Wang, Jilin Li, Feiyue Huang

From this point of view, we design a novel Frequency Consistent Adaptation (FCA) that ensures the frequency domain consistency when applying existing SR methods to the real scene.


DML-GANR: Deep Metric Learning With Generative Adversarial Network Regularization for High Spatial Resolution Remote Sensing Image Retrieval

no code implementations7 Oct 2020 Yun Cao, Yuebin Wang, Junhuan Peng, Liqiang Zhang, Linlin Xu, Kai Yan, Lihua Li

With a small number of labeled samples for training, it can save considerable manpower and material resources, especially when the amount of high spatial resolution remote sensing images (HSR-RSIs) increases considerably.

Image Retrieval Metric Learning

Adversarial Learning for Image Forensics Deep Matching with Atrous Convolution

no code implementations8 Sep 2018 Yaqi Liu, Xianfeng Zhao, Xiaobin Zhu, Yun Cao

Constrained image splicing detection and localization (CISDL) is a newly proposed challenging task for image forensics, which investigates two input suspected images and identifies whether one image has suspected regions pasted from the other.

Image Forensics

Image Forgery Localization Based on Multi-Scale Convolutional Neural Networks

1 code implementation13 Jun 2017 Yaqi Liu, Qingxiao Guan, Xianfeng Zhao, Yun Cao

In this paper, we propose to utilize Convolutional Neural Networks (CNNs) and the segmentation-based multi-scale analysis to locate tampered areas in digital images.

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