Plug-and-play Image Restoration (IR) has been widely recognized as a fle...
Hyperspectral imaging (HI) has emerged as a powerful tool in diverse fie...
Hyperspectral imaging systems that use multispectral filter arrays (MSFA...
Pixel binning based Quad sensors have emerged as a promising solution to...
The performance of video frame interpolation is inherently correlated wi...
Reference-based image super-resolution (RefSR) aims to exploit auxiliary...
Deep neural networks have exhibited remarkable performance in image
supe...
Video restoration aims at restoring multiple high-quality frames from
mu...
While recent years have witnessed a dramatic upsurge of exploiting deep
...
Video restoration (e.g., video super-resolution) aims to restore high-qu...
Image restoration is a long-standing low-level vision problem that aims ...
Video super-resolution (VSR), with the aim to restore a high-resolution ...
We study how to introduce locality mechanisms into vision transformers. ...
Deep neural networks (DNNs) are vulnerable to adversarial examples that ...
Deep neural networks (DNNs) are vulnerable to adversarial examples with ...
Generative adversarial networks (GANs) have shown remarkable success in
...
Recently, deep neural networks (DNNs) have made great progress on automa...
Deep neural networks have exhibited promising performance in image
super...
Neural network quantization is an effective way to compress deep models ...
Joint distribution matching (JDM) problem, which aims to learn bidirecti...
Online Active Learning (OAL) aims to manage unlabeled datastream by
sele...
Multiple marginal matching problem aims at learning mappings to match a
...
Deep neural networks have exhibited promising performance in image
super...
Generative adversarial networks (GANs) aim to generate realistic data fr...