This paper provides a comprehensive review of the NTIRE 2024 challenge focusing on
efficient single-image super-resolution (ESR) solutions and their outcomes. The task of this …

Change detection is an essential and widely utilized task in remote sensing that aims to
detect and analyze changes occurring in the same geographical area over time, which has …

Today's deep learning methods focus on how to design the objective functions to make the
prediction as close as possible to the target. Meanwhile, an appropriate neural network …

Addressing the dual challenges of local redundancy and global dependencies in video
understanding, this work innovatively adapts the Mamba to the video domain. The proposed …

Recent years have seen significant advancements in image restoration, largely attributed to
the development of modern deep neural networks, such as CNNs and Transformers …

In the realm of medical image segmentation, both CNN-based and Transformer-based
models have been extensively explored. However, CNNs exhibit limitations in long-range …

The Transformer architecture has demonstrated remarkable results in 3D medical image
segmentation due to its capability of modeling global relationships. However, it poses a …

Accurate medical image segmentation demands the integration of multi-scale information,
spanning from local features to global dependencies. However, it is challenging for existing …

Pan-sharpening involves integrating information from low-resolution multi-spectral and high-
resolution panchromatic images to generate high-resolution multi-spectral counterparts …

In recent years, Transformers have become the de-facto architecture for sequence modeling
on text and multi-dimensional data, such as images and video. However, the use of self …