Hi there! Welcome to the landing page of our academic work Finding Moments in Video Collections Using Natural Language.
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Please cite if you find this project helpful for your research
@article{EscorciaSSGR2019,
title={Finding Moments in Video Collections Using Natural Language},
author={Victor Escorcia and Mattia Soldan and Josef Sivic and Bernard Ghanem and Bryan Russell},
journal={ArXiv},
year={2019},
volume={abs/1907.12763}
}Hit the ⭐ button in the Github banner if you like this project
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2023-03-08. We released the code. The editors/ACs and reviewers won. The paper will die in arxiv without any peer-reviewed stamp. Victor was stubborn and out of his mind for delaying the code release.
2022-11-23. Our paper got desk rejected from CVIU. The editor and Editor-In-Chief (Prof. Nicu Sebe) did not like that we submitted ~200 pages submission.
2022-09-12. Mattia found out how to stop Victor's procrastination. We submitted our paper, all the reviews, and all the previous rebuttals to CVIU. Looking forward ✌🏼.
2021-09-02. Our paper got rejected on IJCV.
After two revisions, we did not have a chance to address two reviewers 🤬.
OMG, the great editor appointed seven reviewers for free for IJCV.
2020-12-16. We submitted our work to IJCV. @Mattia improved STAL thanks to supervised contrastive learning.
2020-07-30. Our paper got rejected on ECCV'20, the fourth time due to novelty 😝. The code will be released for the CVPR'22 deadline. Get in touch if you plan to run comparisons!
2019-11-12. Model details (initialization), Video corpus moment retrieval evaluation details.
2019-11-08. Release features, baseline results, temporal proposals details.
2019-10-25. Team members at ICCV. Say hi to Bryan Russell and Josef Sivic.
2019-10-21. pre-alpha^n Launching.
On 2023-03-08, as a tribute to all the women Victor announced the code release 🌻.
Context: before the CVPR2020 submission deadline.
Features&Baselines, Evaluation protocol, Two-Stage evaluation protocol Model details, Temporal proposal details, Baseline implementation.
In a nutshell, most of the heavy lifting required to report fair comparisons.
Please open an issue. It helps us to keep all on the same page.