3 papers
eess.IV2025
RAW Image Reconstruction from RGB on Smartphones. NTIRE 2025 Challenge Report
Marcos V. Conde, Radu Timofte, Radu Berdan +30
Numerous low-level vision tasks operate in the RAW domain due to its linear properties, bit depth, and sensor designs. Despite this, RAW image datasets are scarce and more expensiv…
cs.CV2025
SemiISP/SemiIE: Semi-Supervised Image Signal Processor and Image Enhancement Leveraging One-to-Many Mapping sRGB-to-RAW
Masakazu Yoshimura, Junji Otsuka, Radu Berdan +1
DNN-based methods have been successful in Image Signal Processor (ISP) and image enhancement (IE) tasks. However, the cost of creating training data for these tasks is considerably…
cs.CV2024
RAW-Diffusion: RGB-Guided Diffusion Models for High-Fidelity RAW Image Generation
Christoph Reinders, Radu Berdan, Beril Besbinar +2
Current deep learning approaches in computer vision primarily focus on RGB data sacrificing information. In contrast, RAW images offer richer representation, which is crucial for p…