Efficient Object Detection

Efficient object detection focuses on developing deep learning models that accurately identify and locate objects in images or other data modalities (like LiDAR or radar) while minimizing computational cost and latency. Current research emphasizes lightweight architectures like variations of YOLO and transformers, often incorporating techniques such as knowledge distillation, attention mechanisms, and novel feature fusion strategies to improve accuracy and speed on resource-constrained devices. This pursuit is crucial for deploying object detection in real-time applications across diverse domains, including assistive technologies, autonomous driving, and mobile computing, where efficiency is paramount.