The field of event-driven imaging and perception is rapidly evolving, with a focus on leveraging the unique benefits of event cameras, such as high dynamic range and low latency, to improve imaging tasks and enable new applications. Recent research has explored the use of event cameras for 3D reconstruction, image and video enhancement, and real-time perception. Self-supervised learning methods have been proposed to effectively process the sparse and asynchronous event streams, and novel architectures have been designed to achieve precise per-pixel encoding of event timestamps and polarities. Additionally, event cameras have been applied to various domains, including contactless cardiac pulse monitoring and neural 3D rendering. Noteworthy papers in this area include:

• A survey on event-based imaging technologies, which provides a comprehensive study of recent advances and challenges in the field.
• A paper on self-supervised event representations, which introduces a novel method for achieving precise per-pixel encoding of event timestamps and polarities.
• A survey of 3D reconstruction with event cameras, which categorizes existing works into three major types and highlights current research limitations and future directions.
• A study on contactless cardiac pulse monitoring using event cameras, which demonstrates the potential of this novel sensor for remote heart rate monitoring.