CLI19
* *Learning for Computational Imaging
* Adaptive Ptych: Leveraging Image Adaptive Generative Priors for Subsampled Fourier Ptychography
* Blind Unitary Transform Learning for Inverse Problems in Light-Field Imaging
* CNN-Based Cross-Dataset No-Reference Image Quality Assessment
* Decoder-Free Approach for Unsupervised Clustering and Manifold Learning with Random Triplet Mining, A
* Deep Camera: A Fully Convolutional Neural Network for Image Signal Processing
* Deep Compressive Sensing for Visual Privacy Protection in FlatCam Imaging
* Deep Hyperspectral Prior: Single-Image Denoising, Inpainting, Super-Resolution
* Deep Learning-Based Imaging using Single-Lens and Multi-Aperture Diffractive Optical Systems
* Deep Plug-and-Play Prior for Parallel MRI Reconstruction
* Deep Video Deblurring: The Devil is in the Details
* Flickr1024: A Large-Scale Dataset for Stereo Image Super-Resolution
* HVS-Inspired Attention to Improve Loss Metrics for CNN-Based Perception-Oriented Super-Resolution, A
* Image Super-Resolution via Residual Block Attention Networks
* Integrating Data and Image Domain Deep Learning for Limited Angle Tomography using Consensus Equilibrium
* Lightweight and Accurate Recursive Fractal Network for Image Super-Resolution
* Online Regularization by Denoising with Applications to Phase Retrieval
* Removing Imaging Artifacts in Electron Microscopy using an Asymmetrically Cyclic Adversarial Network without Paired Training Data
* RIDNet: Recursive Information Distillation Network for Color Image Denoising
* Semi-Supervised Eye Makeup Transfer by Swapping Learned Representation
* Simple and Robust Deep Convolutional Approach to Blind Image Denoising, A
* SUPER Learning: A Supervised-Unsupervised Framework for Low-Dose CT Image Reconstruction
22 for CLI19