Capturing images with incorrect exposure settings fails to deliver a
sat...
Modern displays are capable of rendering video content with high dynamic...
Moire patterns occur when capturing images or videos on screens, severel...
Image restoration aims to restore high-quality images from degraded
coun...
Aphid infestation poses a significant threat to crop production, rural
c...
The under-display camera (UDC) provides consumers with a full-screen vis...
Aphids are one of the main threats to crops, rural families, and global ...
Image super-resolution (SR) with generative adversarial networks (GAN) h...
Flexible laryngoscopy is commonly performed by otolaryngologists to dete...
Image steganography is the process of concealing secret information in i...
Since training a deep neural network (DNN) is costly, the well-trained d...
For grasp network algorithms, generating grasp datasets for a large numb...
Vision Transformers have attracted a lot of attention recently since the...
Vision Transformers has demonstrated competitive performance on computer...
Gradient inversion attack enables recovery of training samples from mode...
The attention mechanism plays a pivotal role in designing advanced
super...
Under-Display Camera (UDC) has been widely exploited to help smartphones...
Conventional neural structures tend to communicate through analog quanti...
Low-light video enhancement (LLVE) is an important yet challenging task ...
Advances in perception for self-driving cars have accelerated in recent ...
This paper reviews the challenge on constrained high dynamic range (HDR)...
Recent advances in single image super-resolution (SISR) have achieved
ex...
Transformer-based methods have shown impressive performance in low-level...
Self-driving cars must detect vehicles, pedestrians, and other traffic
p...
Learning an generalized prior for natural image restoration is an import...
Mean field approximation methodology has laid the foundation of modern
C...
In this paper, we proposed an end-to-end realtime global attention neura...
Crowd estimation is a very challenging problem. The most recent study tr...
Nowadays modern displays are capable to render video content with high
d...
The cyclically equivariant neural decoder was recently proposed in [Chen...
Most consumer-grade digital cameras can only capture a limited range of
...
Neural decoders were introduced as a generalization of the classic Belie...
Human beings can recognize new objects with only a few labeled examples,...
Photo retouching aims at improving the aesthetic visual quality of image...
Low-precision training has become a popular approach to reduce computati...
Recently, deep learning has been successfully applied to robotic grasp
d...
In the domain of autonomous driving, deep learning has substantially imp...
Grasping in cluttered scenes is challenging for robot vision systems, as...
Deep Learning with noisy labels is a practically challenging problem in
...
Reconfigurable intelligent surfaces (RISs) comprised of tunable unit cel...
Aggregating extra features of novel modality brings great advantages for...