We show that raw degradation features can effectively guide deep restoration models,
providing accurate degradation priors to facilitate better restoration. While networks that do …

Most consumer-grade digital cameras can only capture a limited range of luminance in real-
world scenes due to sensor constraints. Besides, noise and quantization errors are often …

Image processing is a fundamental task in computer vision, which aims at enhancing image
quality and extracting essential features for subsequent vision applications. Traditionally …

Image enhancement aims at improving the aesthetic visual quality of photos by retouching
the color and tone, and is an essential technology for professional digital photography …

Over the last decade, object detection, as a leading application in computer vision, has been
intensively studied, heavily engineered and widely applicable to everyday life. However …

Point cloud completion aims to predict complete shape from its partial observation. Current
approaches mainly consist of generation and refinement stages in a coarse-to-fine style …

While single task image restoration (IR) has achieved significant successes, it remains a
challenging issue to train a single model which can tackle multiple IR tasks. In this work, we …

Current exposure correction methods have three challenges, labor-intensive paired data
annotation, limited generalizability, and performance degradation in low-level computer …

In recent years, the lookup tables (LUTs) with deep learning for image enhancement have
achieved remarkable results with extremely high inference efficiency. However, when …

Abstract High Dynamic Range (HDR) images have more powerful image expression
capabilities and better visual quality than Low Dynamic Range (LDR) images, which can …