NTIRE 2023 challenge on efficient super-resolution: Methods and results
This paper reviews the NTIRE 2023 challenge on efficient single-image super-resolution
with a focus on the proposed solutions and results. The aim of this challenge is to devise a …
with a focus on the proposed solutions and results. The aim of this challenge is to devise a …
[HTML][HTML] A review of deep learning-based detection methods for COVID-19
COVID-19 is a fast-spreading pandemic, and early detection is crucial for stopping the
spread of infection. Lung images are used in the detection of coronavirus infection. Chest X …
spread of infection. Lung images are used in the detection of coronavirus infection. Chest X …
Rethinking coarse-to-fine approach in single image deblurring
Coarse-to-fine strategies have been extensively used for the architecture design of single
image deblurring networks. Conventional methods typically stack sub-networks with multi …
image deblurring networks. Conventional methods typically stack sub-networks with multi …
Pan-mamba: Effective pan-sharpening with state space model
Pan-sharpening involves integrating information from low-resolution multi-spectral and high-
resolution panchromatic images to generate high-resolution multi-spectral counterparts …
resolution panchromatic images to generate high-resolution multi-spectral counterparts …
Contrastive learning for compact single image dehazing
Single image dehazing is a challenging ill-posed problem due to the severe information
degeneration. However, existing deep learning based dehazing methods only adopt clear …
degeneration. However, existing deep learning based dehazing methods only adopt clear …
Low-light image and video enhancement using deep learning: A survey
Low-light image enhancement (LLIE) aims at improving the perception or interpretability of
an image captured in an environment with poor illumination. Recent advances in this area …
an image captured in an environment with poor illumination. Recent advances in this area …
Multiresolution knowledge distillation for anomaly detection
Unsupervised representation learning has proved to be a critical component of anomaly
detection/localization in images. The challenges to learn such a representation are two-fold …
detection/localization in images. The challenges to learn such a representation are two-fold …
Reconstructing the mind's eye: fMRI-to-image with contrastive learning and diffusion priors
We present MindEye, a novel fMRI-to-image approach to retrieve and reconstruct viewed
images from brain activity. Our model comprises two parallel submodules that are …
images from brain activity. Our model comprises two parallel submodules that are …
Image super-resolution: A comprehensive review, recent trends, challenges and applications
Super resolution (SR) is an eminent system in the field of computer vison and image
processing to improve the visual perception of the poor-quality images. The key objective of …
processing to improve the visual perception of the poor-quality images. The key objective of …
Authentic volumetric avatars from a phone scan
Creating photorealistic avatars of existing people currently requires extensive person-
specific data capture, which is usually only accessible to the VFX industry and not the …
specific data capture, which is usually only accessible to the VFX industry and not the …