Image Sensor
Image sensors are crucial components in various applications, from autonomous driving to medical diagnostics, aiming to capture and process visual information efficiently and accurately. Current research emphasizes improving robustness against adversarial attacks and environmental variations, often integrating data from multiple sensor types (e.g., radar and camera) and employing deep learning models like convolutional neural networks (CNNs) and recurrent neural networks (RNNs) for enhanced image processing and object recognition. These advancements are driving significant improvements in image quality, data processing speed, and energy efficiency, impacting fields ranging from mobile photography to autonomous vehicle perception.
Papers
MIPI 2023 Challenge on RGBW Remosaic: Methods and Results
Qianhui Sun, Qingyu Yang, Chongyi Li, Shangchen Zhou, Ruicheng Feng, Yuekun Dai, Wenxiu Sun, Qingpeng Zhu, Chen Change Loy, Jinwei Gu
MIPI 2023 Challenge on RGBW Fusion: Methods and Results
Qianhui Sun, Qingyu Yang, Chongyi Li, Shangchen Zhou, Ruicheng Feng, Yuekun Dai, Wenxiu Sun, Qingpeng Zhu, Chen Change Loy, Jinwei Gu