Built on

The PASCAL Visual Object Classes Challenge 2012 (VOC2012) Results
M. Everingham, L. Van Gool, C. K. I. Williams, J. Winn, and A. Zisserman · 2012
Earlier work this paper cites.

Similar

The VGG image annotator (VIA)
Original
Abhishek Dutta and Andrew Zisserman · 2019
Cited alongside, same era.

Then

An objective comparison of detection and segmentation algorithms for artefacts in clinical endoscopy
Sharib Ali, Felix Zhou, Barbara Braden, Adam Bailey, Suhui Yang, Guanju Cheng, Pengyi Zhang, Xiaoqiong Li, Maxime Kayser, Roger D. Soberanis-Mukul, Shadi Albarqouni, Xiaokang Wang, Chunqing Wang, Seiryo Watanabe, Ilkay Oksuz, Qingtian Ning, Shufan Yang, Mohammad Azam Khan, Xiaohong W. Gao, Stefano Realdon, Maxim Loshchenov, Julia A. Schnabel, James E. East, Geroges Wagnieres, Victor B. Loschenov, Enrico Grisan, Christian Daul, Walter Blondel, and Jens Rittscher · 2020
Closest in time.

Beyond the bibliography

alphaXiv searches the wider corpus for related work and actual follow-ups.

Open on alphaXiv

alphaXiv is searching for related work…

Reading the bibliography…

2020

Endoscopy disease detection challenge 2020

Ali, Sharib, Ghatwary, Noha, Braden, Barbara et al.

Understand

Whilst many technologies are built around endoscopy, there is a need to have a comprehensive dataset collected from multiple centers to address the generalization issues with most deep learning frameworks.

What could be more important than disease detection and localization? Through our extensive network of clinical and computational experts, we have collected, curated and annotated gastrointestinal endoscopy video frames.
We have released this dataset and have launched disease detection and segmentation challenge EDD2020 https://edd2020.grand-challenge.org to address the limitations and explore new directions.
EDD2020 is a crowd sourcing initiative to test the feasibility of recent deep learning methods and to promote research for building robust technologies.