no code implementations • 14 Mar 2022 • Arushi Jain, Shubham Paliwal, Monika Sharma, Lovekesh Vig
In this paper, we propose to train a deep network to capture the spatial associations between different word pairs present in the table image for unravelling the table structure.
no code implementations • 8 Sep 2021 • Shubham Paliwal, Monika Sharma, Lovekesh Vig
The proposed pipeline, named OSSR-PID, is fast and gives outstanding performance for recognition of symbols on a synthetic dataset of 100 P&ID diagrams.
no code implementations • 8 Sep 2021 • Shubham Paliwal, Arushi Jain, Monika Sharma, Lovekesh Vig
A novel and efficient kernel-based line detection and a two-step method for detection of complex symbols based on a fine-grained deep recognition technique is presented in the paper.
5 code implementations • 6 Jan 2020 • Shubham Paliwal, Vishwanath D, Rohit Rahul, Monika Sharma, Lovekesh Vig
This includes accurate detection of the tabular region within an image, and subsequently detecting and extracting information from the rows and columns of the detected table.
Ranked #3 on Table Detection on ICDAR2013
no code implementations • 28 Jan 2019 • Rohit Rahul, Shubham Paliwal, Monika Sharma, Lovekesh Vig
To that end, we present a novel pipeline for information extraction from P&ID sheets via a combination of traditional vision techniques and state-of-the-art deep learning models to identify and isolate pipeline codes, pipelines, inlets and outlets, and for detecting symbols.