7 papers
PAGen: Phase-guided Amplitude Generation for Domain-adaptive Object Detection
Shuchen Du, Shuo Lei, Feiran Li +2
Unsupervised domain adaptation (UDA) greatly facilitates the deployment of neural networks across diverse environments. However, most state-of-the-art approaches are overly complex…
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…
Noise Modeling in One Hour: Minimizing Preparation Efforts for Self-supervised Low-Light RAW Image Denoising
Feiran Li, Haiyang Jiang, Daisuke Iso
Noise synthesis is a promising solution for addressing the data shortage problem in data-driven low-light RAW image denoising. However, accurate noise synthesis methods often neces…
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.…
Beyond RGB: Adaptive Parallel Processing for RAW Object Detection
Shani Gamrian, Hila Barel, Feiran Li +2
Object detection models are typically applied to standard RGB images processed through Image Signal Processing (ISP) pipelines, which are designed to enhance sensor-captured RAW im…