Streaming Perception

Streaming perception focuses on developing real-time object detection systems that accurately perceive dynamic environments, addressing the challenges of computational delays and environmental changes during processing. Current research emphasizes model architectures that incorporate adaptive mechanisms, such as dynamic routing and multi-timestep prediction, often leveraging transformer networks or YOLO-based approaches, to improve accuracy and efficiency across diverse hardware and environmental conditions. This field is crucial for autonomous driving and other real-time applications requiring robust and low-latency perception, impacting safety, efficiency, and the development of more sophisticated intelligent systems.