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https://github.com/MathamPollard/awesome-table-structure-recognition
A Curated List of Awesome Table Structure Recognition (TSR) Research. Including models, papers, datasets and codes. Continuously updating.
https://github.com/MathamPollard/awesome-table-structure-recognition
List: awesome-table-structure-recognition
document-understanding table-detection table-extraction table-functional-analysis table-structure-recognition
Last synced: 16 days ago
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A Curated List of Awesome Table Structure Recognition (TSR) Research. Including models, papers, datasets and codes. Continuously updating.
- Host: GitHub
- URL: https://github.com/MathamPollard/awesome-table-structure-recognition
- Owner: MathamPollard
- License: apache-2.0
- Created: 2023-12-15T09:50:35.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2024-04-17T12:09:54.000Z (8 months ago)
- Last Synced: 2024-05-21T22:01:21.138Z (7 months ago)
- Topics: document-understanding, table-detection, table-extraction, table-functional-analysis, table-structure-recognition
- Homepage: https://github.com/MathamPollard/awesome-table-structure-recognition
- Size: 145 KB
- Stars: 33
- Watchers: 2
- Forks: 2
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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- ultimate-awesome - awesome-table-structure-recognition - A Curated List of Awesome Table Structure Recognition (TSR) Research. Including models, papers, datasets and codes. Continuously updating. (Other Lists / Monkey C Lists)
README
# A Curated List of Awesome Table Structure Recognition (TSR) Research.
This is a curated list of awesome table structure recognition (TSR) research.Including **sota models**, influential papers, popular datasets and open-source **codes**. Continuously updating.
If you find any relevant academic papers that have not been included in our research, please submit a request for an update. We welcome contributions from everyone.
## Popular Datasets
| Name | Tables | Data Type | TD | TSR | TCR | Year|
| ---- | ---- | ---- | ---- | ---- | ---- | ----|
| [ICDAR2013](https://paperswithcode.com/dataset/icdar-2013) | 156 | Digital | √ | √ | √ |2013|
| [SciTSR](https://github.com/Academic-Hammer/SciTSR) | 15K | Digital | × | √ | √ |2019|
| [TableBank](https://doc-analysis.github.io/tablebank-page/) | 417K | Digital | √ | × | × |2020|
| [TableBank](https://doc-analysis.github.io/tablebank-page/) | 145K | Digital | × | √ | × |2020|
| [PubTabNet](https://github.com/ibm-aur-nlp/PubTabNet) | 1M+ | Digital | × | √ | √ |2020|
| [PubTables-1M](https://github.com/microsoft/table-transformer?tab=readme-ov-file)| 1M+ | Digital | √ | √ | × |2021|
| [FinbTabNet](https://developer.ibm.com/exchanges/data/all/fintabnet/) | 91596 | Digital | × | √ | √ |2021|
| [WTW](https://github.com/wangwen-whu/WTW-Dataset) | 14581 | Both | × | √ | × |2021|
| [SynthTabNet](https://github.com/IBM/SynthTabNet) | 600K | Digital | × | √ | √ |2022|
| [TabRecSet](https://github.com/MaxKinny/TabRecSet) | 38177 | Both | √ | √ | √ |2023|
| [iFLYTAB](https://github.com/ZZR8066/SEMv2?tab=readme-ov-file) | 12104 | Both | √ | √ | × |2023|
**TD** means **T**able **D**etection
**TSR** means **T**able **S**tructure **R**ecognition
**TCD** means **T**able **C**ontent **R**ecognition
**Both** means including both digital and physical data
## SOTA Models
Method Type
Method Name
Citation Count
Year
Venue
Open Source
Bottom-up
Res2TIM
37
2019
ICDAR
√
CascadeTabNet
182
2020
CVPR
√
TabStruct-Net
87
2020
ECCV
LGPMA
63
2021
ICDAR
√
Cycle-CenterNet
39
2021
ICCV
TGRNet
42
2021
ICCV
√
FLAG-NET
30
2021
MM
GTE
116
2021
WACV
NCGM
25
2022
CVPR
LORE
7
2023
AAAI
Image2Markup
EDD
171
2020
ECCV
√
TableMaster
34
2021
ICDAR
√
TableFormer
41
2022
CVPR
VAST
12
2023
CVPR
UniTable
2024
√
OminParser
2024
CVPR
√
Split-and-Merge Based
SPLERGE
91
2019
ICDAR
√
SEM
40
2022
PR
√
TSRFormer
20
2022
MM
RobusTabNet
32
2023
PR
SEMv2
3
2024
PR
√
TSRFormer-DQ-DETR
2024
PR
Others
TableNet
188
2019
ICDAR
√
DETR
60
2022
CVPR
√
TRACE
3
2023
ICDAR
√
## Influential Papers
### CVPR 2024
+ OMNIPARSER: A Unified Framework for Text Spotting, Key Information Extraction and Table Recognition-[Paper](https://arxiv.org/abs/2403.19128),[code]( https://github.com/AlibabaResearch/AdvancedLiterateMachinery/tree/main/OCR/OmniParser)
### PR 2024
+ SEMv2: Table Separation Line Detection Based on Conditional Convolution-[Paper](https://www.semanticscholar.org/paper/SEMv2%3A-Table-Separation-Line-Detection-Based-on-Zhang-Hu/c78daabab3666d08d945098bc462f882b78803fd),
[code](https://github.com/ZZR8066/SEMv2)
+ Robust table structure recognition with dynamic queries enhanced detection transformer-[Paper](https://www.sciencedirect.com/science/article/abs/pii/S0031320323005150)
### CVPR 2023
+ Improving Table Structure Recognition with Visual-Alignment Sequential Coordinate Modeling-[Paper](https://openaccess.thecvf.com/content/CVPR2023/papers/Huang_Improving_Table_Structure_Recognition_With_Visual-Alignment_Sequential_Coordinate_Modeling_CVPR_2023_paper.pdf)
### AAAI 2023
+ LORE: Logical Location Regression Network for Table Structure Recognition=[Paper](https://ojs.aaai.org/index.php/AAAI/article/view/25402/25174)
### PR 2023
+ Robust Table Detection and Structure Recognition from Heterogeneous Document Images-[Paper](https://www.sciencedirect.com/science/article/abs/pii/S0031320322004861)
+ Scene table structure recognition with segmentation collaboration and alignment-[Paper](https://www.sciencedirect.com/science/article/abs/pii/S0167865522003828?via%3Dihub)
### ACL 2023
+ TableVLM: Multi-modal Pre-training for Table Structure Recognition-[Paper](https://aclanthology.org/2023.acl-long.137/)
### ICDAR 2023
+ TRACE: Table Reconstruction Aligned to Corner and Edges-[Paper](https://link.springer.com/chapter/10.1007/978-3-031-41734-4_29)
+ Aligning benchmark datasets for table structure recognition-[Paper](https://link.springer.com/chapter/10.1007/978-3-031-41734-4_23)
+ Optimized Table Tokenization for Table Structure Recognition-[Paper](https://link.springer.com/chapter/10.1007/978-3-031-41679-8_3)
### CVPR 2022
+ Neural Collaborative Graph Machines for Table Structure Recognition-[Paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Liu_Neural_Collaborative_Graph_Machines_for_Table_Structure_Recognition_CVPR_2022_paper.pdf)
+ TableFormer: Table Structure Understanding with Transformers-[Paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Nassar_TableFormer_Table_Structure_Understanding_With_Transformers_CVPR_2022_paper.pdf)
+ PubTables-1M: Towards comprehensive table extraction from unstructured documents-[Paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Smock_PubTables-1M_Towards_Comprehensive_Table_Extraction_From_Unstructured_Documents_CVPR_2022_paper.pdf),
[code](https://github.com/microsoft/table-transformer)
### PR 2022
+ Split, Embed and Merge: An accurate table structure recognizer-[Paper](https://www.sciencedirect.com/science/article/abs/pii/S0031320322000462)
### WACV 2022
+ Visual Understanding of Complex Table Structures from Document Images-[Paper](https://openaccess.thecvf.com/content/WACV2022/papers/Raja_Visual_Understanding_of_Complex_Table_Structures_From_Document_Images_WACV_2022_paper.pdf)
### MM 2022
+ TSRFormer: Table Structure Recognition with Transformers-[Paper](https://dl.acm.org/doi/abs/10.1145/3503161.3548038)
### ICCV 2021
+ Parsing Table Structures in the Wild-[Paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Long_Parsing_Table_Structures_in_the_Wild_ICCV_2021_paper.pdf)
+ TGRNet: A Table Graph Reconstruction Network for Table Structure Recognition-[Paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Xue_TGRNet_A_Table_Graph_Reconstruction_Network_for_Table_Structure_Recognition_ICCV_2021_paper.pdf),
[code](https://github.com/xuewenyuan/TGRNet)
### WACV 2021
+ Global Table Extractor (GTE): A Framework for Joint Table Identification and Cell Structure Recognition Using Visual Context-[Paper](https://openaccess.thecvf.com/content/WACV2021/papers/Zheng_Global_Table_Extractor_GTE_A_Framework_for_Joint_Table_Identification_WACV_2021_paper.pdf)
### MM 2021
+ Show, Read and Reason: Table Structure Recognition with Flexible Context Aggregator-[Paper](https://dl.acm.org/doi/abs/10.1145/3474085.3481534)
### ICDAR 2021
+ LGPMA: Complicated Table Structure Recognition with Local and Global Pyramid Mask Alignment-[Paper](https://link.springer.com/chapter/10.1007/978-3-030-86549-8_7)
+ PINGAN-VCGROUP’S SOLUTION FOR ICDAR 2021 COMPETITION ON SCIENTIFIC LITERATURE PARSING TASK B:TABLE RECOGNITION TO HTML-[Paper](https://www.semanticscholar.org/paper/PingAn-VCGroup%27s-Solution-for-ICDAR-2021-on-Table-He-Qi/754087ddb922b22873c20b3b4eec3272898326d9),
[code](https://github.com/JiaquanYe/TableMASTER-mmocr)
+ TabLeX: A Benchmark Dataset for Structure and Content Information Extraction from Scientific Tables-[Paper](https://link.springer.com/chapter/10.1007/978-3-030-86331-9_36)
### CVPRW 2020
+ CascadeTabNet: An approach for end to end table detection and structure recognition from image-based documents-[Paper](https://openaccess.thecvf.com/content_CVPRW_2020/papers/w34/Prasad_CascadeTabNet_An_Approach_for_End_to_End_Table_Detection_and_CVPRW_2020_paper.pdf),
[code](https://github.com/DevashishPrasad/CascadeTabNet)
### ECCV 2020
+ Image-based table recognition: data, model, and evaluation-[Paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123660562.pdf)
+ Table Structure Recognition using Top-Down and Bottom-Up Cues-[Paper](https://link.springer.com/chapter/10.1007/978-3-030-58604-1_5)
### LERC 2020
+ TableBank: Table Benchmark for Image-based Table Detection and Recognition-[Paper](https://aclanthology.org/2020.lrec-1.236/)
### ICDAR 2019
+ Challenges in end-to-end neural scientific table recognition-[Paper](https://ieeexplore.ieee.org/document/8978078)
+ Deep Splitting and Merging for Table Structure Decomposition-[Paper](https://ieeexplore.ieee.org/document/8977975)
+ DeepTabStR: Deep Learning based Table Structure Recognition-[Paper](https://ieeexplore.ieee.org/document/8978137)
+ Rethinking Table Recognition using Graph Neural Networks-[Paper](https://www.computer.org/csdl/proceedings-article/icdar/2019/301400a142/1h81qHhrzaM)
+ ReS2TIM: Reconstruct Syntactic Structures from Table Images-[Paper](https://ieeexplore.ieee.org/document/8978027)
+ TableNet: Deep Learning model for end-to-end Table detection and Tabular data extraction from Scanned Document Images-[Paper](https://www.computer.org/csdl/proceedings-article/icdar/2019/301400a128/1h81vwkHTwY),[code](https://github.com/AmanSavaria1402/TableNet),[model](https://drive.google.com/file/d/11cl-QP5xsYmuM-IwCtc1psMH14bb7kFx/view)
## Others
#### 2024
+ UniTable: Towards a Unified Framework for Table Structure Recognition via Self-Supervised Pretraining-[Paper](https://arxiv.org/abs/2403.04822)
#### 2023
+ A large-scale dataset for end-to-end table recognition in the wild-[Paper](https://www.nature.com/articles/s41597-023-01985-8),[code](https://github.com/MaxKinny/TabRecSet)
#### 2021
+ Multi-Type-TD-TSR -- Extracting Tables from Document Images using a Multi-stage Pipeline for Table Detection and Table Structure Recognition: from OCR to Structured Table Representations-[Paper](https://link.springer.com/chapter/10.1007/978-3-030-87626-5_8),
[code](https://github.com/Psarpei/Multi-Type-TD-TSR)
## Surveys
+ **[ICDAR 2023]** A Study on Reproducibility and Replicability of Table Structure Recognition Methods-[Paper](https://link.springer.com/chapter/10.1007/978-3-031-41679-8_1)
+ Deep Learning for Table Detection and Structure Recognition: A Survey-[Paper](https://dl.acm.org/doi/abs/10.1145/3657281)
## Star History
[](https://star-history.com/#MathamPollard/awesome-table-structure-recognition&Date)