This research is like giving a safety inspector super-vision: a computer looks at construction site photos and automatically figures out what activities are happening, without needing pre-drawn boxes around workers or equipment.
Manually reviewing construction site photos to understand what tasks are being performed, track progress, or spot unsafe behavior is slow and inconsistent. This work aims to automatically recognize construction activities directly from single images, improving monitoring, documentation, and safety analytics.
Research-grade computer-vision model architecture and trained weights specific to construction activities and multiscale site scenes; potential proprietary labeled image datasets of construction activities.
Open Source (Llama/Mistral)
Unknown
High (Custom Models/Infra)
Training data collection and labeling for diverse construction activities and site conditions; inference cost/latency for high-resolution multiscale images.
Early Adopters
Focus on anchor-free, multiscale recognition of construction activities from still images, rather than generic object detection or video-based action recognition; tailored to construction domain scenes and activities.