CNN's limited receptive field restricts its ability to capture long-range spatial-temporal
dependencies, leading to unsatisfactory performance in video super-resolution. To tackle …

Abstract Neural Radiance Fields (NeRF) have become an increasingly popular
representation to capture high-quality appearance and shape of scenes and objects …

Robotic systems employed in tasks such as navigation, target tracking, security, and
surveillance often use camera gimbal systems to enhance their monitoring and security …

Efficient feature extraction is a pivotal requirement for Deep Neural Network (DNN) models,
particularly in the realm of visual tasks where effective feature extraction relies on well …

Feature registration is a core problem in computer vision and machine learning techniques.
In recent years, significant progress has been made in learning-based feature registration …

The degradation of printed photographs due to inadequate preservation is a major problem
that can be addressed through deep learning-based restoration methods. However, these …

Recently, the contrastive learning paradigm has achieved remarkable success in high-level
tasks such as classification, detection, and segmentation. However, contrastive learning …

Recently, there have been significant advancements in Image Restoration based on CNN
and transformer. However, the inherent characteristics of the Image Restoration task are …

This paper introduces ConStyle v2, a strong plug-and-play prompter designed to output
clean visual prompts and assist U-Net Image Restoration models in handling multiple …

现在高效的图像压缩已经成为数字图像有效存储和传输的必要手段. 经过压缩之后的图像难免
存在块伪影, 震荡伪影, 图像模糊等问题. 压缩图像增强技术作为图像编码效率提升的重要方式 …