This paper reviews the NTIRE 2024 low light image enhancement challenge, highlighting
the proposed solutions and results. The aim of this challenge is to discover an effective …

Spoken language understanding (SLU) is a fundamental task in the task-oriented dialogue
systems. However, the inevitable errors from automatic speech recognition (ASR) usually …

Images captured under poor lighting conditions often suffer from low brightness, low
contrast, color distortion, and noise. The function of low-light image enhancement is to …

Automatic radiology report generation has attracted enormous research interest due to its
practical value in reducing the workload of radiologists. However, simultaneously …

In this paper, we propose a diffusion-based unsupervised framework that incorporates
physically explainable Retinex theory with diffusion models for low-light image …

How to effectively explore multi-scale representations of rain streaks is important for image
deraining. In contrast to existing Transformer-based methods that depend mostly on single …

Low-light remote sensing (RS) images generally feature high resolution and high spatial
complexity, with continuously distributed surface features in space. This continuity in scenes …

Medical image segmentation plays a critical role in clinical decision-making, treatment
planning, and disease monitoring. However, accurate segmentation of medical images is …

Underwater images suffer from light refraction and absorption, which impairs visibility and
interferes the subsequent applications. Existing underwater image enhancement methods …

In the field of low-light image enhancement, both traditional Retinex methods and advanced
deep learning techniques such as Retinexformer have shown distinct advantages and …