The topic of table detection and recognition has been spotlighted in recent years, however, the latest works only aim at the coarse scene in table-wise detection. In this paper, we present TableCell, a new image-based dataset which contains 5262 samples with 170K high precision cell-wised annotations based on a novel semi-supervised method.. Several classical deep learning detection models are evaluated to build a strong baseline using the proposed dataset. Furthermore, we come up with an efficient table projection method to facilitate capturing long-range global feature, which consists of row projection and column projection. Experiments demonstrate that our proposed method improves the accuracy of table detection. Our dataset and code will be made available at https://github.com/weidafeng/TableCell upon publication.