Towards End-to-End Semi-Supervised Table Detection with Semantic Aligned Matching Transformer

arXiv:2405.00187v1 Announce Type: new
Abstract: Table detection within document images is a crucial task in document processing, involving the identification and localization of tables. Recent strides in deep learning have substantially improved the accuracy of this task, but it still heavily relies on large labeled datasets for effective training. Several semi-supervised approaches have emerged to overcome this challenge, often employing CNN-based detectors with anchor proposals and post-processing techniques like non-maximal suppression (NMS). However, recent advancements in the field have shifted …

abstract accuracy arxiv cs.cv datasets deep learning detection document document processing identification images localization processing semantic semi-supervised table table detection tables training transformer type