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Found 5 papers, 2 papers with code
GridFormer: Towards Accurate Table Structure Recognition via Grid Prediction
In this representation, the vertexes and edges of the grid store the localization and adjacency information of the table.
ICDAR 2023 Competition on Structured Text Extraction from Visually-Rich Document Images
It is hoped that this competition will attract many researchers in the field of CV and NLP, and bring some new thoughts to the field of Document AI.
StrucTexTv2: Masked Visual-Textual Prediction for Document Image Pre-training
Compared to the masked multi-modal modeling methods for document image understanding that rely on both the image and text modalities, StrucTexTv2 models image-only input and potentially deals with more application scenarios free from OCR pre-processing.
Ranked #1 on
Table Recognition
on WTW
TRUST: An Accurate and End-to-End Table structure Recognizer Using Splitting-based Transformers
The Vertex-based Merging Module is capable of aggregating local contextual information between adjacent basic grids, providing the ability to merge basic girds that belong to the same spanning cell accurately.
Ranked #5 on
Table Recognition
on PubTabNet
Deformable Siamese Attention Networks for Visual Object Tracking
In this paper, we propose Deformable Siamese Attention Networks, referred to as SiamAttn, by introducing a new Siamese attention mechanism that computes deformable self-attention and cross-attention.
