SoccerNet 2022 Challenges Results

challenge; dataset; SoccerNet; video understanding; sports; soccer; neural netwok; artificial intelligence; human tracking; player tracking; machine learning; deep learning; Sport; Football

Abstract :

[en] The SoccerNet 2022 challenges were the second annual video understanding challenges organized by the SoccerNet team. In 2022, the challenges were composed of 6 vision-based tasks: (1) action spotting, focusing on retrieving action timestamps in long untrimmed videos, (2) replay grounding, focusing on retrieving the live moment of an action shown in a replay, (3) pitch localization, focusing on detecting line and goal part elements, (4) camera calibration, dedicated to retrieving the intrinsic and extrinsic camera parameters, (5) player re-identification, focusing on retrieving the same players across multiple views, and (6) multiple object tracking, focusing on tracking players and the ball through unedited video streams. Compared to last year's challenges, tasks (1-2) had their evaluation metrics redefined to consider tighter temporal accuracies, and tasks (3-6) were novel, including their underlying data and annotations. More information on the tasks, challenges and leaderboards are available on https://www.soccer-net.org. Baselines and development kits are available on https://github.com/SoccerNet .

Research center :

Telim
Montefiore

Disciplines :

Electrical & electronics engineering

Author, co-author :

Giancola, Silvio ^✱; KAUST, Thuwal, Saudi Arabia

Cioppa, Anthony ^✱; Université de Liège - ULiège > Montefiore Institute of Electrical Engineering and Computer Science

Deliège, Adrien ; Université de Liège - ULiège > Département d'électricité, électronique et informatique (Institut Montefiore) > Télécommunications

Magera, Floriane ; Université de Liège - ULiège > Montefiore Institute of Electrical Engineering and Computer Science

Somers, Vladimir; Sportradar, UCLouvain, & EPFL, Minneapolis, MN, USA

Kang, Le; Baidu Research, Seattle, WA, USA

Zhou, Xin; Baidu Research, Seattle, WA, USA

Barnich, Olivier; EVS Broadcast Equipment, Seraing, Belgium

De Vleeschouwer, Christophe; UCLouvain, Louvain-la-Neuve, Belgium

Alahi, Alexandre; EPFL, Lausanne, Switzerland

More authors (84 more)

^✱ These authors have contributed equally to this work.

Language :

English

Title :

SoccerNet 2022 Challenges Results

Publication date :

10 October 2022

Event name :

5th International ACM Workshop on Multimedia Content Analysis in Sports (MMSports)

Event organizer :

ACM

Event place :

Lisboa, Portugal

Event date :

10/10/2022

Audience :

International

Main work title :

ACM International Conference on Multimedia

Publisher :

Association for Computing Machinery, New York, United States - New York

Pages :

75-86

Peer reviewed :

Peer reviewed

Name of the research project :

Applications et Recherche pour une Intelligence Artificielle de Confiance (ARIAC)

Funders :

SPW - Public Service of Wallonia [BE]

Funding number :

2010235

Data Set :

https://www.soccer-net.org/

Available on ORBi :

since 04 November 2022

Statistics

Number of views

44 (4 by ULiège)

Number of downloads

56 (3 by ULiège)

More statistics

Scopus citations^®

Scopus citations^®
without self-citations

OpenCitations

Bibliography

Andrei Boiarov and Eduard Tyantov. 2019. Large Scale Landmark Recognition via Deep Metric Learning. In ACM Int. Conf. Inf. Knowl. Manag. ACM, Beijing China, 169-178. https://doi.org/10.1145/3357384.3357956
Shimin Chen, Chen Chen, Wei Li, Xunqiang Tao, and Yandong Guo. 2022. Faster-TAD: Towards Temporal Action Detection with Proposal Generation and Classication in a Unied Network. arXiv abs/2204.02674 (2022), 16 pages. arXiv:2204.02674
Bowen Cheng, Ishan Misra, Alexander G Schwing, Alexander Kirillov, and Rohit Girdhar. 2022. Masked-Attention mask transformer for universal image segmentation. In IEEE Conf. Comput. Vis. Pattern Recog. New Orleans, LA, USA, 1290-1299.
Anthony Cioppa, Adrien Deliège, Silvio Giancola, Bernard Ghanem, and Marc Van Droogenbroeck. 2022. Scaling up SoccerNet with multi-view spatial localization and re-identication. Scientic Data 9, 1 (June 2022), 1-9. https: //doi.org/10.1038/s41597-022-01469-1
Anthony Cioppa, Adrien Deliège, Silvio Giancola, Floriane Magera, Olivier Barnich, Bernard Ghanem, and Marc Van Droogenbroeck. 2021. Camera Calibration and Player Localization in SoccerNet-v2 and Investigation of their Representations for Action Spotting. In IEEE Int. Conf. Comput. Vis. and Pattern Recogn. Work. (CVPRW), CVsports. Inst. Elect. and Electron. Engineers (IEEE), Nashville, TN, USA, 4537-4546. https://doi.org/10.1109/CVPRW53098.2021.00511
Anthony Cioppa, Silvio Giancola, Adrien Deliège, Le Kang, Xin Zhou, Cheng Zhiyu, Bernard Ghanem, and Marc Van Droogenbroeck. 2022. SoccerNet-Tracking: Multiple Object Tracking Dataset and Benchmark in Soccer Videos. In IEEE Int. Conf. Comput. Vis. and Pattern Recogn. Work. (CVPRW), CVsports. Inst. Elect. and Electron. Engineers (IEEE), New Orleans, LA, USA, 3491-3502.
Bharath Comandur. 2022. Sports Re-ID: Improving Re-Identification Of Players In Broadcast Videos Of Team Sports. arXiv abs/2206.02373 (2022), 11 pages. arXiv:2206.02373
Ekin Dogus Cubuk, Barret Zoph, Dandelion Mané, Vijay Vasudevan, and Quoc V. Le. 2018. AutoAugment: Learning Augmentation Policies from Data. arXiv abs/1805.09501 (2018), 14 pages. arXiv:1805.09501
Adrien Deliège, Anthony Cioppa, Silvio Giancola, Meisam J. Seikavandi, Jacob V. Dueholm, Kamal Nasrollahi, Bernard Ghanem, Thomas B. Moeslund, and Marc Van Droogenbroeck. 2021. SoccerNet-v2: A Dataset and Benchmarks for Holistic Understanding of Broadcast Soccer Videos. In IEEE Int. Conf. Comput. Vis. and Pattern Recogn. Work. (CVPRW), CVsports. Inst. Elect. and Electron. Engineers (IEEE), Nashville, TN, USA, 4508-4519. https://doi.org/10.1109/CVPRW53098. 2021.00508
Jiankang Deng, Jia Guo, Niannan Xue, and Stefanos Zafeiriou. 2019. ArcFace: Additive Angular Margin Loss for Deep Face Recognition. In IEEE/CVF Conf. Comput. Vis. and Pattern Recogn. (CVPR). Inst. Elect. and Electron. Engineers (IEEE), Long Beach, CA, USA, 4685-4694. https://doi.org/10.1109/cvpr.2019.00482
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, and Neil Houlsby. 2021. An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale. arXiv abs/2010.11929 (2021), 22 pages. arXiv:2010.11929
Christoph Feichtenhofer, Haoqi Fan, Jitendra Malik, and Kaiming He. 2019. Slow-Fast Networks for Video Recognition. In Int. Conf. Comput. Vis. Inst. Elect. and Electron. Engineers (IEEE), Seoul, South Korea, 6201-6210. https://doi.org/10. 1109/iccv.2019.00630
Dengpan Fu, Dongdong Chen, Jianmin Bao, Hao Yang, Lu Yuan, Lei Zhang, Houqiang Li, and Dong Chen. 2021. Unsupervised Pre-Training for Person Reidentification. In IEEE/CVF Conf. Comput. Vis. and Pattern Recogn. (CVPR). Inst. Elect. and Electron. Engineers (IEEE), Nashville, TN, USA, 14745-14754. https: //doi.org/10.1109/cvpr46437.2021.01451
Silvio Giancola, Mohieddine Amine, Tarek Dghaily, and Bernard Ghanem. 2018. SoccerNet: A Scalable Dataset for Action Spotting in Soccer Videos. In IEEE Int. Conf. Comput. Vis. and Pattern Recogn. Work. (CVPRW), CVsports. Inst. Elect. and Electron. Engineers (IEEE), Salt Lake City, UT, USA, 1711-1721. https: //doi.org/10.1109/CVPRW.2018.00223
Dan Hendrycks, Norman Mu, Ekin D. Cubuk, Barret Zoph, Justin Gilmer, and Balaji Lakshminarayanan. 2019. AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty. arXiv abs/1912.02781 (2019), 15 pages. arXiv:1912.02781
Xin Huang, Xinxin Wang, Wenyu Lv, Xiaying Bai, Xiang Long, Kaipeng Deng, Qingqing Dang, Shumin Han, Qiwen Liu, Xiaoguang Hu, et al. 2021. PP-YOLOv2: A practical object detector. arXiv abs/2104.10419 (2021), 7 pages. arXiv:2104.10419
Prannay Khosla, Piotr Teterwak, ChenWang, Aaron Sarna, Yonglong Tian, Phillip Isola, Aaron Maschinot, Ce Liu, and Dilip Krishnan. 2020. Supervised Contrastive Learning. In Advances in Neural Information Processing Systems, H. Larochelle, M. Ranzato, R. Hadsell, M.F. Balcan, and H. Lin (Eds.), Vol. 33. Curran Associates, Inc., Virtual conference, 18661-18673.
Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He, and Piotr Dollár. 2020. Focal Loss for Dense Object Detection. IEEE Trans. Pattern Anal. Mach. Intell. 42, 2 (Feb. 2020), 318-327. https://doi.org/10.1109/tpami.2018.2858826
Ze Liu, Jia Ning, Yue Cao, Yixuan Wei, Zheng Zhang, Stephen Lin, and Han Hu. 2021. Video Swin Transformer. arXiv abs/2106.13230 (2021), 12 pages. arXiv:2106.13230
Jonathon Luiten, Aljosa Osep, Patrick Dendorfer, Philip Torr, Andreas Geiger, Laura Leal-Taixé, and Bastian Leibe. 2021. HOTA: A higher order metric for evaluating multi-object tracking. Int. J. Comput. Vis. 129, 2 (Oct. 2021), 548-578. https://doi.org/10.1007/s11263-020-01375-2
Hao Luo, Pichao Wang, Yi Xu, Feng Ding, Yanxin Zhou, Fan Wang, Hao Li, and Rong Jin. 2021. Self-Supervised Pre-Training for Transformer-Based Person Re-Identification. arXiv abs/2111.12084 (2021), 15 pages. arXiv:2111.12084
Haowen Luo, Pichao Wang, Yi Xu, Feng Ding, Yanxin Zhou, Fan Wang, Hao Li, and Rong Jin. 2021. Self-Supervised Pre-Training for Transformer-Based Person Re-Identification. arXiv abs/2111.12084 (2021), 15 pages. arXiv:2111.12084
Florian Schro, Dmitry Kalenichenko, and James Philbin. 2015. FaceNet: A unified embedding for face recognition and clustering. In IEEE/CVF Conf. Comput. Vis. and Pattern Recogn. (CVPR). Inst. Elect. and Electron. Engineers (IEEE), Boston, MA, USA, 815-823. https://doi.org/10.1109/cvpr.2015.7298682
João V. B. Soares and Avijit Shah. 2022. Action Spotting using Dense Detection Anchors Revisited: Submission to the SoccerNet Challenge 2022. arXiv abs/2206.07846 (2022), 3 pages. arXiv:2206.07846
João V. B. Soares, Avijit Shah, and Topojoy Biswas. 2022. Temporally Precise Action Spotting in Soccer Videos Using Dense Detection Anchors. arXiv abs/2205.10450 (2022), 5 pages. arXiv:2205.10450
Aäron van den Oord, Yazhe Li, and Oriol Vinyals. 2018. Representation Learning with Contrastive Predictive Coding. arXiv abs/1807.03748 (2018), 13 pages. arXiv:1807.03748
XiaogangWang, Gianfranco Doretto, Thomas Sebastian, Jens Rittscher, and Peter Tu. 2007. Shape and Appearance Context Modeling. In Int. Conf. Comput. Vis. Inst. Elect. and Electron. Engineers (IEEE), Rio de Janeiro, Brazil, 1-8. https: //doi.org/10.1109/iccv.2007.4409019
Mitchell Wortsman, Gabriel Ilharco, Samir Yitzhak Gadre, Rebecca Roelofs, Raphael Gontijo-Lopes, Ari S. Morcos, Hongseok Namkoong, Ali Farhadi, Yair Carmon, Simon Kornblith, and Ludwig Schmidt. 2022. Model soups: Averaging weights of multiple ne-Tuned models improves accuracy without increasing inference time. arXiv abs/2203.05482 (2022), 34 pages. arXiv:2203.05482
Mang Ye, Jianbing Shen, Gaojie Lin, Tao Xiang, Ling Shao, and Steven C. H. Hoi. 2022. Deep Learning for Person Re-Identification: A Survey and Outlook. IEEE Trans. Pattern Anal. Mach. Intell. 44, 6 (June 2022), 2872-2893. https: //doi.org/10.1109/tpami.2021.3054775
Liang Zheng, Liyue Shen, Lu Tian, Shengjin Wang, Jingdong Wang, and Qi Tian. 2015. Scalable Person Re-identification: A Benchmark. In Int. Conf. Comput. Vis. Inst. Elect. and Electron. Engineers (IEEE), Santiago, Chile, 1116-1124. https: //doi.org/10.1109/iccv.2015.133
Zhun Zhong, Liang Zheng, Guoliang Kang, Shaozi Li, and Yi Yang. 2020. Random Erasing Data Augmentation. In AAAI, Vol. 34. Association for the Advancement of Artificial Intelligence, New York, USA, 13001-13008. https://doi.org/10.1609/aaai.v34i07.7000
Xin Zhou, Le Kang, Zhiyu Cheng, Bo He, and Jingyu Xin. 2021. Feature Combination Meets Attention: Baidu Soccer Embeddings and Transformer based Temporal Detection. arXiv abs/2106.14447 (2021), 7 pages. arXiv:2106.14447