4 papers
RAW-Flow: Advancing RGB-to-RAW Image Reconstruction with Deterministic Latent Flow Matching
Zhen Liu, Diedong Feng, Hai Jiang +6
RGB-to-RAW reconstruction, or the reverse modeling of a camera Image Signal Processing (ISP) pipeline, aims to recover high-fidelity RAW data from RGB images. Despite notable progr…
Learning Arbitrary-Scale RAW Image Downscaling with Wavelet-based Recurrent Reconstruction
Yang Ren, Hai Jiang, Wei Li +5
Image downscaling is critical for efficient storage and transmission of high-resolution (HR) images. Existing learning-based methods focus on performing downscaling within the sRGB…
Learning to See in the Extremely Dark
Hai Jiang, Binhao Guan, Zhen Liu +5
Learning-based methods have made promising advances in low-light RAW image enhancement, while their capability to extremely dark scenes where the environmental illuminance drops as…
ISPDiffuser: Learning RAW-to-sRGB Mappings with Texture-Aware Diffusion Models and Histogram-Guided Color Consistency
Yang Ren, Hai Jiang, Menglong Yang +2
RAW-to-sRGB mapping, or the simulation of the traditional camera image signal processor (ISP), aims to generate DSLR-quality sRGB images from raw data captured by smartphone sensor…