We present a new video understanding pentathlon challenge, an open competition held in conjunction with the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2020. The objective of the challenge was to explore and evaluate new methods for text-to-video retrieval-the task of searching for content within a corpus of videos using natural language queries. This report summarizes the results of the first edition of the challenge together with the findings of the participants.
@article{arxiv.2008.00744,
title = {The End-of-End-to-End: A Video Understanding Pentathlon Challenge (2020)},
author = {Samuel Albanie and Yang Liu and Arsha Nagrani and Antoine Miech and Ernesto Coto and Ivan Laptev and Rahul Sukthankar and Bernard Ghanem and Andrew Zisserman and Valentin Gabeur and Chen Sun and Karteek Alahari and Cordelia Schmid and Shizhe Chen and Yida Zhao and Qin Jin and Kaixu Cui and Hui Liu and Chen Wang and Yudong Jiang and Xiaoshuai Hao},
journal= {arXiv preprint arXiv:2008.00744},
year = {2020}
}
Comments
Individual reports, dataset information, rules, and released source code can be found at the competition webpage (https://www.robots.ox.ac.uk/~vgg/challenges/video-pentathlon)