4.7 Article

Meta-Learning-Based Degradation Representation for Blind Super-Resolution

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Proceedings Paper Computer Science, Artificial Intelligence

ITERATIVE KERNEL RECONSTRUCTION FOR DEEP LEARNING-BASED BLIND IMAGE SUPER-RESOLUTION

Suleyman Yildirim et al.

Summary: Deep learning based methods have shown superior performance in solving the single image super-resolution (SISR) problem, but most of them lack generalization ability on real images. This paper proposes an Iterative Kernel Reconstruction network (IKR-Net) for blind SISR, achieving state-of-the-art results by iteratively estimating kernel and reconstructing high resolution images.

2022 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, ICIP (2022)

Proceedings Paper Computer Science, Artificial Intelligence

Metric Learning Based Interactive Modulation for Real-World Super-Resolution

Chong Mou et al.

Summary: This research presents a metric learning based interactive modulation method for real-world super-resolution, achieving excellent modulation and restoration performance through unsupervised degradation estimation and metric learning strategy.

COMPUTER VISION - ECCV 2022, PT XVII (2022)

Proceedings Paper Computer Science, Artificial Intelligence

Meta-Transfer Learning for Zero-Shot Super-Resolution

Jae Woong Soh et al.

2020 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR) (2020)

Article Computer Science, Artificial Intelligence

Multiple Cycle-in-Cycle Generative Adversarial Networks for Unsupervised Image Super-Resolution

Yongbing Zhang et al.

IEEE TRANSACTIONS ON IMAGE PROCESSING (2020)

Article Computer Science, Artificial Intelligence

LCSCNet: Linear Compressing-Based Skip-Connecting Network for Image Super-Resolution

Wenming Yang et al.

IEEE TRANSACTIONS ON IMAGE PROCESSING (2020)

Article Computer Science, Artificial Intelligence

Soft-Edge Assisted Network for Single Image Super-Resolution

Faming Fang et al.

IEEE TRANSACTIONS ON IMAGE PROCESSING (2020)

Article Computer Science, Artificial Intelligence

DCSR: Dilated Convolutions for Single Image Super-Resolution

Zhendong Zhang et al.

IEEE TRANSACTIONS ON IMAGE PROCESSING (2019)

Article Computer Science, Information Systems

Sketch-based manga retrieval using manga109 dataset

Yusuke Matsui et al.

MULTIMEDIA TOOLS AND APPLICATIONS (2017)

Article Computer Science, Artificial Intelligence

Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising

Kai Zhang et al.

IEEE TRANSACTIONS ON IMAGE PROCESSING (2017)

Proceedings Paper Computer Science, Artificial Intelligence

NTIRE 2017 Challenge on Single Image Super-Resolution: Dataset and Study

Eirikur Agustsson et al.

2017 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW) (2017)

Proceedings Paper Computer Science, Artificial Intelligence

Deep Laplacian Pyramid Networks for Fast and Accurate Super-Resolution

Wei-Sheng Lai et al.

30TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2017) (2017)

Proceedings Paper Computer Science, Artificial Intelligence

Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network

Christian Ledig et al.

30TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2017) (2017)

Article Computer Science, Artificial Intelligence

Image Super-Resolution Using Deep Convolutional Networks

Chao Dong et al.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2016)

Proceedings Paper Computer Science, Artificial Intelligence

Low-Complexity Single-Image Super-Resolution based on Nonnegative Neighbor Embedding

Marco Bevilacqua et al.

PROCEEDINGS OF THE BRITISH MACHINE VISION CONFERENCE 2012 (2012)