The VidSTG dataset is a spatio-temporal video grounding dataset built on the VidOR dataset. VidOR is a video relation dataset containing 7,000, 835, and 2,165 videos for training, validation, and testing, respectively. The goal of the spatio-temporal video grounding task is to locate the spatio-temporal part of an uncut video that matches a given sentence describing the target.

Citation

@inproceedings{zhang2020does, title={Where Does It Exist: Spatio-Temporal Video Grounding for Multi-Form Sentences}, author={Zhang, Zhu and Zhao, Zhou and Zhao, Yang and Wang, Qi and Liu, Huasheng and Gao, Lianli} booktitle={CVPR}, year={2020} } @inproceedings{shang2019annotating, title={Annotating Objects and Relations in User-Generated Videos}, author={Shang, Xindi and Di, Donglin and Xiao, Junbin and Cao, Yu and Yang, Xun and Chua, Tat-Seng} booktitle={Proceedings of the 2019 on International Conference on Multimedia Retrieval}, pages={279–287}, year={2019}, organization={ACM} }