Construction progress is a key part of project management. Traditional progress management mostly relies on manual inspection, which is time-consuming and can not guarantee the progress evaluation. In order to automatically and efficiently monitor construction progress, this article proposed an intelligent framework for indoor construction progress evaluation. This framework can automatically extract the tile laying progress of indoor wall and ground based on the improved Mask R-CNN, and map the progress results to the BIM for visualization using camera tracking algorithm. The framework was successfully applied in a building project in Shanghai with a high precision of image segmentation, verifying the feasibility of the presented framework. This study provides theoretical and practical reference for the automated progress tracking and unmanned construction progress supervision of indoor continuous space.