Dataset image examples

AI algorithms can automatically identify construction objects/instances/scenes in images and videos through parallel computation and graphic card implementation. However, they require large-scale datasets to mitigate the overfitting problem during the training stage. Since construction sites are often challenging to access, creating extensive datasets containing high-quality construction data poses a significant challenge. The construction community faces a critical barrier, which is the lack of standardized, high-quality, and domain-specific open data resources. This fragmentation undermines reproducibility, slows innovation, and prevents the construction community from developing benchmark tasks that can drive rapid progress 

ACID dataset suite was developed as one of the first pioneering open-source artifacts in construction community. Its novelty lies in providing the community with: 1) construction-specific AI research and education resources; 2) benchmark tasks and algorithm analysis to ensure reproducibility and reusability of construction AI research; and 3) annotation guidelines to standardize the creation of future datasets. Through years efforts, ACID has established a transformative foundation for construction AI. The following videos showcase various AI applications backboned by ACID in construction.