
## TFLOP: Table Structure Recognition Framework with Layout Pointer Mechanism
Minsoo Khang, Teakgyu Hong
Keywords: Computer Vision: CV: Recognition (object detection, categorization), Computer Vision: CV: Applications, Natural Language Processing: NLP: Applications
IJCAI/2024/Proceedings/0105 - TFLOP: Table Structure Recognition Framework with Layout Pointer Mechanism.pdf

### Implementation
_Given the documentation given by the authors on the method, how much time investment would it be to re-implement the method from scratch?_

[1]

[Source Code available +0
installation and examples available +0
code not majorly without comments +0
clear names + 0
]

### Data
_Given the data description in the documentation, how much effort take to either: Find the same dataset the authors used, or similar datasets and defend the comparability, or acquire one from scratch?_

[1]

(1/3)

[All 3 are cited only one is linked 2/3
Description given for all 3 +0
statistics given +0
No information about privacy given for 2 +4/3]

### Configuration 
_Given the (hyper)parameters, including semantic parameters, of the method: How much effort would it take to acquire the algorithm configurations used for their results, and compare against their budgetary constraints?_

[4]

[given in a table for one dataset rest is not clearly stated +2
Defined hyperparameters have values +0
chosen parameters, maybe also given from environment +1]

### Experimental Procedure
_Given the experimental set-up of the work, how difficult is it to set up a new experiment, similar to those presented in the original work, with the same procedure?_

[5]

[Metric is explained +0
One table not clear if full dataset or test +1
train test slit not given by 2 datasets +2
strategy implied as holdout +1
clear aggregation +0]

### Expertise
_How much effort would it take to acquire the expertise required to reproduce the work independently relying on the available documentation?_

[2]

[Code for paper is given atleast 1 dataset is available and seems to be the main result. other 2 datasets might require some search.]
