NTIRE 2024 challenge on bracketing image restoration and enhancement: Datasets methods and results
Low-light photography presents significant challenges. Multi-image processing methods
have made numerous attempts to obtain high-quality photos yet remain unsatisfactory …
have made numerous attempts to obtain high-quality photos yet remain unsatisfactory …
Deep learning on image denoising: An overview
Deep learning techniques have received much attention in the area of image denoising.
However, there are substantial differences in the various types of deep learning methods …
However, there are substantial differences in the various types of deep learning methods …
Learning for vehicle-to-vehicle cooperative perception under lossy communication
Deep learning has been widely used in intelligent vehicle driving perception systems, such
as 3D object detection. One promising technique is Cooperative Perception, which …
as 3D object detection. One promising technique is Cooperative Perception, which …
Burst image restoration and enhancement
Modern handheld devices can acquire burst image sequence in a quick succession.
However, the individual acquired frames suffer from multiple degradations and are …
However, the individual acquired frames suffer from multiple degradations and are …
Nan: Noise-aware nerfs for burst-denoising
Burst denoising is now more relevant than ever, as computational photography helps
overcome sensitivity issues inherent in mobile phones and small cameras. A major …
overcome sensitivity issues inherent in mobile phones and small cameras. A major …
Kbnet: Kernel basis network for image restoration
How to aggregate spatial information plays an essential role in learning-based image
restoration. Most existing CNN-based networks adopt static convolutional kernels to encode …
restoration. Most existing CNN-based networks adopt static convolutional kernels to encode …
Spatially-adaptive pixelwise networks for fast image translation
We introduce a new generator architecture, aimed at fast and efficient high-resolution image-
to-image translation. We design the generator to be an extremely lightweight function of the …
to-image translation. We design the generator to be an extremely lightweight function of the …
Physics-based noise modeling for extreme low-light photography
Enhancing the visibility in extreme low-light environments is a challenging task. Under
nearly lightless condition, existing image denoising methods could easily break down due to …
nearly lightless condition, existing image denoising methods could easily break down due to …
Deep reparametrization of multi-frame super-resolution and denoising
We propose a deep reparametrization of the maximum a posteriori formulation commonly
employed in multi-frame image restoration tasks. Our approach is derived by introducing a …
employed in multi-frame image restoration tasks. Our approach is derived by introducing a …
Image denoising in the deep learning era
Over the last decade, the number of digital images captured per day has increased
exponentially, due to the accessibility of imaging devices. The visual quality of photographs …
exponentially, due to the accessibility of imaging devices. The visual quality of photographs …