research
∙
12/15/2021
Robust Depth Completion with Uncertainty-Driven Loss Functions
Recovering a dense depth image from sparse LiDAR scans is a challenging ...
share
research
∙
08/30/2021
Efficient Visual Recognition with Deep Neural Networks: A Survey on Recent Advances and New Directions
Visual recognition is currently one of the most important and active res...
research
∙
05/09/2021
Lightweight Image Super-Resolution with Hierarchical and Differentiable Neural Architecture Search
Single Image Super-Resolution (SISR) tasks have achieved significant per...
research
∙
04/06/2021
Searching Efficient Model-guided Deep Network for Image Denoising
Neural architecture search (NAS) has recently reshaped our understanding...
research
∙
03/12/2021
Deep Gaussian Scale Mixture Prior for Spectral Compressive Imaging
In coded aperture snapshot spectral imaging (CASSI) system, the real-wor...
research
∙
09/14/2020
Accurate and Lightweight Image Super-Resolution with Model-Guided Deep Unfolding Network
Deep neural networks (DNNs) based methods have achieved great success in...
research
∙
04/11/2020
MetaIQA: Deep Meta-learning for No-Reference Image Quality Assessment
Recently, increasing interest has been drawn in exploiting deep convolut...
research
∙
07/18/2018
Learning Hybrid Sparsity Prior for Image Restoration: Where Deep Learning Meets Sparse Coding
State-of-the-art approaches toward image restoration can be classified i...
research
∙
01/31/2018
ConvCSNet: A Convolutional Compressive Sensing Framework Based on Deep Learning
Compressive sensing (CS), aiming to reconstruct an image/signal from a s...
research
∙
01/21/2018
Denoising Prior Driven Deep Neural Network for Image Restoration
Deep neural networks (DNNs) have shown very promising results for variou...
research
∙
03/13/2017
GUN: Gradual Upsampling Network for single image super-resolution
In this paper, we propose an efficient super-resolution (SR) method base...
research
∙
12/06/2010