Table Detection
20 papers with code • 3 benchmarks • 9 datasets
Benchmarks
These leaderboards are used to track progress in Table Detection
| Trend | Dataset | Best Model | Paper | Code | Compare |
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ICDAR 2013
FUNSD
SciTSR
TableBank
PubTables-1M
IIIT-AR-13K
TNCR Dataset
ICDAR 2019
STDW
Latest papers with no code
Semantic Table Detection with LayoutLMv3
This paper presents an application of the LayoutLMv3 model for semantic table detection on financial documents from the IIIT-AR-13K dataset.
DATa: Domain Adaptation-Aided Deep Table Detection Using Visual-Lexical Representations
More specifically, after pre-training one of state-of-the-art vision-based models as our backbone network, we re-train our augmented model, consisting of the vision-based model and the multilayer perceptron (MLP) architecture.
DEXTER: An end-to-end system to extract table contents from electronic medical health documents
We design a conventional computer vision-based approach for table type classification and cell detection using parameterized kernels based on image size for detecting rows and columns.
Robust Table Detection and Structure Recognition from Heterogeneous Document Images
We introduce a new table detection and structure recognition approach named RobusTabNet to detect the boundaries of tables and reconstruct the cellular structure of each table from heterogeneous document images.
On Cropped versus Uncropped Training Sets in Tabular Structure Detection
Prior works have addressed this problem under table detection and table structure detection tasks.
Current Status and Performance Analysis of Table Recognition in Document Images with Deep Neural Networks
Table understanding has substantially benefited from the recent breakthroughs in deep neural networks.
Imagined-Trailing-Whitespace-Agnostic Levenshtein Distance For Plaintext Table Detection
In this work, we provide an efficient $O(n^2)$ algorithm to compute the same.
Deep Structured Feature Networks for Table Detection and Tabular Data Extraction from Scanned Financial Document Images
The main contributions of this paper are proposing the Financial Documents dataset with table-area annotations, the superior detection model and the rule-based layout segmentation technique for the tabular data extraction from PDF files.
A Conglomerate of Multiple OCR Table Detection and Extraction
Information representation as tables are compact and concise method that eases searching, indexing, and storage requirements.
DocStruct: A Multimodal Method to Extract Hierarchy Structure in Document for General Form Understanding
The table detection and handcrafted features in previous works cannot apply to all forms because of their requirements on formats.
