Motion Blur

Motion blur, the blurring of objects in images or videos due to movement during exposure, is a significant challenge in computer vision, hindering accurate object detection, 3D reconstruction, and other applications. Current research focuses on mitigating motion blur through various techniques, including the development of sophisticated deblurring algorithms often employing neural networks (like transformers and convolutional neural networks), and the integration of event cameras which offer high temporal resolution to capture motion information more effectively. These advancements are crucial for improving the robustness and accuracy of computer vision systems in dynamic real-world scenarios, impacting fields such as autonomous driving, robotics, and video analysis.