Harmful Object Detection

Harmful object detection aims to automatically identify and filter inappropriate or dangerous content from images and videos, crucial for online safety and security. Current research focuses on developing larger, more diverse datasets encompassing a wider range of harmful content categories and improving object detection algorithms, often leveraging advanced deep learning architectures, to enhance accuracy and efficiency. These advancements are vital for improving content moderation systems on online platforms and enabling safer online experiences, while also contributing to broader computer vision research on efficient object detection in challenging scenarios.