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The Multi-Modal Video Reasoning and Analyzing Competition. /
Peng, Haoran; Huang, He; Xu, Li et al.
2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW). IEEE, 2021. p. 806-813 (Proceedings of the IEEE International Conference on Computer Vision; Vol. 2021-October).
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Harvard
Peng, H, Huang, H, Xu, L, Li, T, Liu, J
, Rahmani, H, Ke, Q, Guo, Z, Wu, C, Li, R, Ye, M, Wang, J, Zhang, J, Liu, Y, He, T, Zhang, F, Liu, X & Lin, T 2021,
The Multi-Modal Video Reasoning and Analyzing Competition. in
2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW). Proceedings of the IEEE International Conference on Computer Vision, vol. 2021-October, IEEE, pp. 806-813.
https://doi.org/10.1109/ICCVW54120.2021.00095
APA
Peng, H., Huang, H., Xu, L., Li, T., Liu, J.
, Rahmani, H., Ke, Q., Guo, Z., Wu, C., Li, R., Ye, M., Wang, J., Zhang, J., Liu, Y., He, T., Zhang, F., Liu, X., & Lin, T. (2021).
The Multi-Modal Video Reasoning and Analyzing Competition. In
2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW) (pp. 806-813). (Proceedings of the IEEE International Conference on Computer Vision; Vol. 2021-October). IEEE.
https://doi.org/10.1109/ICCVW54120.2021.00095
Vancouver
Author
Bibtex
@inproceedings{d7c813780d7d416187f8155ecd26f9d0,
title = "The Multi-Modal Video Reasoning and Analyzing Competition",
abstract = "In this paper, we introduce the Multi-Modal Video Reasoning and Analyzing Competition (MMVRAC) workshop in conjunction with ICCV 2021. This competition is composed of four different tracks, namely, video question answering, skeleton-based action recognition, fisheye video-based action recognition, and person re-identification, which are based on two datasets: SUTD-TrafficQA and UAV-Human. We summarize the top-performing methods submitted by the participants in this competition and show their results achieved in the competition.",
author = "Haoran Peng and He Huang and Li Xu and Tianjiao Li and Jun Liu and Hossein Rahmani and Qiuhong Ke and Zhicheng Guo and Cong Wu and Rongchang Li and Mang Ye and Jiahao Wang and Jiaxu Zhang and Yuanzhong Liu and Tao He and Fuwei Zhang and Xianbin Liu and Tao Lin",
year = "2021",
month = nov,
day = "24",
doi = "10.1109/ICCVW54120.2021.00095",
language = "English",
series = "Proceedings of the IEEE International Conference on Computer Vision",
publisher = "IEEE",
pages = "806--813",
booktitle = "2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)",
}
RIS
TY - GEN
T1 - The Multi-Modal Video Reasoning and Analyzing Competition
AU - Peng, Haoran
AU - Huang, He
AU - Xu, Li
AU - Li, Tianjiao
AU - Liu, Jun
AU - Rahmani, Hossein
AU - Ke, Qiuhong
AU - Guo, Zhicheng
AU - Wu, Cong
AU - Li, Rongchang
AU - Ye, Mang
AU - Wang, Jiahao
AU - Zhang, Jiaxu
AU - Liu, Yuanzhong
AU - He, Tao
AU - Zhang, Fuwei
AU - Liu, Xianbin
AU - Lin, Tao
PY - 2021/11/24
Y1 - 2021/11/24
N2 - In this paper, we introduce the Multi-Modal Video Reasoning and Analyzing Competition (MMVRAC) workshop in conjunction with ICCV 2021. This competition is composed of four different tracks, namely, video question answering, skeleton-based action recognition, fisheye video-based action recognition, and person re-identification, which are based on two datasets: SUTD-TrafficQA and UAV-Human. We summarize the top-performing methods submitted by the participants in this competition and show their results achieved in the competition.
AB - In this paper, we introduce the Multi-Modal Video Reasoning and Analyzing Competition (MMVRAC) workshop in conjunction with ICCV 2021. This competition is composed of four different tracks, namely, video question answering, skeleton-based action recognition, fisheye video-based action recognition, and person re-identification, which are based on two datasets: SUTD-TrafficQA and UAV-Human. We summarize the top-performing methods submitted by the participants in this competition and show their results achieved in the competition.
U2 - 10.1109/ICCVW54120.2021.00095
DO - 10.1109/ICCVW54120.2021.00095
M3 - Conference contribution/Paper
T3 - Proceedings of the IEEE International Conference on Computer Vision
SP - 806
EP - 813
BT - 2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)
PB - IEEE
ER -
