3 accepted papers
Object insertion has emerged as a promising augmentation paradigm to solve the label scarcity and long-tail distributions in remote sensing. It aims to generate training samples by synthesizing target instances onto real backgrounds. However, existing methods have three critical issues: (i) Semantic…
Existing single-image denoising algorithms often struggle to restore details when dealing with complex noisy images. The introduction of near-infrared (NIR) images offers new possibilities for RGB image denoising. However, due to the inconsistency between NIR and RGB images, the existing works still…
Image denoising enhances image quality, serving as a foundational technique across various computational photography applications. The obstacle to clean image acquisition in real scenarios necessitates the development of self-supervised image denoising methods only depending on noisy images, especia…