4 papers
AIM 2025 Challenge on Real-World RAW Image Denoising
Feiran Li, Jiacheng Li, Marcos V. Conde +4
We introduce the AIM 2025 Real-World RAW Image Denoising Challenge, aiming to advance efficient and effective denoising techniques grounded in data synthesis. The competition is bu…
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…
ReRAW: RGB-to-RAW Image Reconstruction via Stratified Sampling for Efficient Object Detection on the Edge
Radu Berdan, Beril Besbinar, Christoph Reinders +2
Edge-based computer vision models running on compact, resource-limited devices benefit greatly from using unprocessed, detail-rich RAW sensor data instead of processed RGB images.…
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…