Frame Detector

Frame detectors are algorithms designed to identify and locate objects within image or point cloud sequences, a crucial task in applications like autonomous driving and robotics. Current research focuses on improving accuracy and efficiency, particularly in challenging scenarios like low light, small targets, and cross-domain adaptation. This involves leveraging temporal information across multiple frames using techniques like recurrent neural networks, transformer architectures, and motion-guided fusion, often within a multi-frame or self-training framework. These advancements significantly impact the reliability and performance of object detection systems in real-world applications.