Random shuffle transformer for image restoration
Non-local interactions play a vital role in boosting performance for image restoration.
However, local window Transformer has been preferred due to its efficiency for processing …
However, local window Transformer has been preferred due to its efficiency for processing …
AverNet: All-in-one video restoration for time-varying unknown degradations
Traditional video restoration approaches were designed to recover clean videos from a
specific type of degradation, making them ineffective in handling multiple unknown types of …
specific type of degradation, making them ineffective in handling multiple unknown types of …
VRetouchEr: Learning Cross-frame Feature Interdependence with Imperfection Flow for Face Retouching in Videos
Abstract Face Video Retouching is a complex task that often requires labor-intensive manual
editing. Conventional image retouching methods perform less satisfactorily in terms of …
editing. Conventional image retouching methods perform less satisfactorily in terms of …
Region-Aware Sequence-to-Sequence Learning for Hyperspectral Denoising
Proper spectral modeling within hyperspectral image (HSI) is critical yet highly challenging
for HSI denoising. In contrast to existing methods that struggle between effectiveness and …
for HSI denoising. In contrast to existing methods that struggle between effectiveness and …
Image deblurring method based on self-attention and residual wavelet transform
B Zhang, J Sun, F Sun, F Wang, B Zhu - Expert Systems with Applications, 2024 - Elsevier
The restoration technology of non-uniform blurred images is a challenging open topic. Most
of the existing algorithms fail to effectively fuse multi-scale feature extraction with a self …
of the existing algorithms fail to effectively fuse multi-scale feature extraction with a self …
Rethinking prediction-based video anomaly detection from local–global normality perspective
Video anomaly detection (VAD) has been intensively studied for years because of its
potential applications in intelligent video systems. Prediction-based VAD methods have …
potential applications in intelligent video systems. Prediction-based VAD methods have …
Attentive Large Kernel Network with Mixture of Experts for Video Deblurring
Video deblurring is a fundamental problem in low-level vision, and many methods have
employed designs based on CNNs and transformers. Traditional CNNs often require deeper …
employed designs based on CNNs and transformers. Traditional CNNs often require deeper …
An implicit alignment for video super-resolution
Video super-resolution commonly uses a frame-wise alignment to support the propagation
of information over time. The role of alignment is well-studied for low-level enhancement in …
of information over time. The role of alignment is well-studied for low-level enhancement in …
EvTexture: Event-driven Texture Enhancement for Video Super-Resolution
Event-based vision has drawn increasing attention due to its unique characteristics, such as
high temporal resolution and high dynamic range. It has been used in video super …
high temporal resolution and high dynamic range. It has been used in video super …
Memory-based gradient-guided progressive propagation network for video deblurring
G Song, S Gai, F Da - The Visual Computer, 2024 - Springer
Video deblurring is a challenging visual task because it requires handling temporal
correlations among frames and dealing with various sources of uncertainty in motion blur. To …
correlations among frames and dealing with various sources of uncertainty in motion blur. To …