Skip to main content

2023 | OriginalPaper | Buchkapitel

The Tenth Visual Object Tracking VOT2022 Challenge Results

verfasst von : Matej Kristan, Aleš Leonardis, Jiří Matas, Michael Felsberg, Roman Pflugfelder, Joni-Kristian Kämäräinen, Hyung Jin Chang, Martin Danelljan, Luka Čehovin Zajc, Alan Lukežič, Ondrej Drbohlav, Johanna Björklund, Yushan Zhang, Zhongqun Zhang, Song Yan, Wenyan Yang, Dingding Cai, Christoph Mayer, Gustavo Fernández, Kang Ben, Goutam Bhat, Hong Chang, Guangqi Chen, Jiaye Chen, Shengyong Chen, Xilin Chen, Xin Chen, Xiuyi Chen, Yiwei Chen, Yu-Hsi Chen, Zhixing Chen, Yangming Cheng, Angelo Ciaramella, Yutao Cui, Benjamin Džubur, Mohana Murali Dasari, Qili Deng, Debajyoti Dhar, Shangzhe Di, Emanuel Di Nardo, Daniel K. Du, Matteo Dunnhofer, Heng Fan, Zhenhua Feng, Zhihong Fu, Shang Gao, Rama Krishna Gorthi, Eric Granger, Q. H. Gu, Himanshu Gupta, Jianfeng He, Keji He, Yan Huang, Deepak Jangid, Rongrong Ji, Cheng Jiang, Yingjie Jiang, Felix Järemo Lawin, Ze Kang, Madhu Kiran, Josef Kittler, Simiao Lai, Xiangyuan Lan, Dongwook Lee, Hyunjeong Lee, Seohyung Lee, Hui Li, Ming Li, Wangkai Li, Xi Li, Xianxian Li, Xiao Li, Zhe Li, Liting Lin, Haibin Ling, Bo Liu, Chang Liu, Si Liu, Huchuan Lu, Rafael M. O. Cruz, Bingpeng Ma, Chao Ma, Jie Ma, Yinchao Ma, Niki Martinel, Alireza Memarmoghadam, Christian Micheloni, Payman Moallem, Le Thanh Nguyen-Meidine, Siyang Pan, ChangBeom Park, Danda Paudel, Matthieu Paul, Houwen Peng, Andreas Robinson, Litu Rout, Shiguang Shan, Kristian Simonato, Tianhui Song, Xiaoning Song, Chao Sun, Jingna Sun, Zhangyong Tang, Radu Timofte, Chi-Yi Tsai, Luc Van Gool, Om Prakash Verma, Dong Wang, Fei Wang, Liang Wang, Liangliang Wang, Lijun Wang, Limin Wang, Qiang Wang, Gangshan Wu, Jinlin Wu, Xiaojun Wu, Fei Xie, Tianyang Xu, Wei Xu, Yong Xu, Yuanyou Xu, Wanli Xue, Zizheng Xun, Bin Yan, Dawei Yang, Jinyu Yang, Wankou Yang, Xiaoyun Yang, Yi Yang, Yichun Yang, Zongxin Yang, Botao Ye, Fisher Yu, Hongyuan Yu, Jiaqian Yu, Qianjin Yu, Weichen Yu, Kang Ze, Jiang Zhai, Chengwei Zhang, Chunhu Zhang, Kaihua Zhang, Tianzhu Zhang, Wenkang Zhang, Zhibin Zhang, Zhipeng Zhang, Jie Zhao, Shaochuan Zhao, Feng Zheng, Haixia Zheng, Min Zheng, Bineng Zhong, Jiawen Zhu, Xuefeng Zhu, Yueting Zhuang

Erschienen in: Computer Vision – ECCV 2022 Workshops

Verlag: Springer Nature Switzerland

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

The Visual Object Tracking challenge VOT2022 is the tenth annual tracker benchmarking activity organized by the VOT initiative. Results of 93 entries are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in recent years. The VOT2022 challenge was composed of seven sub-challenges focusing on different tracking domains: (i) VOT-STs2022 challenge focused on short-term tracking in RGB by segmentation, (ii) VOT-STb2022 challenge focused on short-term tracking in RGB by bounding boxes, (iii) VOT-RTs2022 challenge focused on “real-time” short-term tracking in RGB by segmentation, (iv) VOT-RTb2022 challenge focused on “real-time” short-term tracking in RGB by bounding boxes, (v) VOT-LT2022 focused on long-term tracking, namely coping with target disappearance and reappearance, (vi) VOT-RGBD2022 challenge focused on short-term tracking in RGB and depth imagery, and (vii) VOT-D2022 challenge focused on short-term tracking in depth-only imagery. New datasets were introduced in VOT-LT2022 and VOT-RGBD2022, VOT-ST2022 dataset was refreshed, and a training dataset was introduced for VOT-LT2022. The source code for most of the trackers, the datasets, the evaluation kit and the results are publicly available at the challenge website (http://​votchallenge.​net).

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Fußnoten
3
The target was sought in a window centered at its estimated position in the previous frame. This is the simplest dynamic model that assumes all positions within a search region containing the target have an equal prior probability.
 
Literatur
1.
Zurück zum Zitat Bhat, G., Danelljan, M., Gool, L.V., Timofte, R.: Learning discriminative model prediction for tracking. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 6182–6191 (2019) Bhat, G., Danelljan, M., Gool, L.V., Timofte, R.: Learning discriminative model prediction for tracking. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 6182–6191 (2019)
2.
Zurück zum Zitat Chen, X., Yan, B., Zhu, J., Wang, D., Yang, X., Lu, H.: Transformer tracking. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 8126–8135 (2021) Chen, X., Yan, B., Zhu, J., Wang, D., Yang, X., Lu, H.: Transformer tracking. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 8126–8135 (2021)
3.
Zurück zum Zitat Cui, Y., Jiang, C., Wang, L., Wu, G.: Mixformer: End-to-end tracking with iterative mixed attention. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 13608–13618 (2022) Cui, Y., Jiang, C., Wang, L., Wu, G.: Mixformer: End-to-end tracking with iterative mixed attention. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 13608–13618 (2022)
4.
Zurück zum Zitat Dosovitskiy, A., et al.: An image is worth 16x16 words: Transformers for image recognition at scale. arXiv preprint arXiv:2010.11929 (2020) Dosovitskiy, A., et al.: An image is worth 16x16 words: Transformers for image recognition at scale. arXiv preprint arXiv:​2010.​11929 (2020)
5.
Zurück zum Zitat Kristan, M., et. al.: Appendix of the tenth visual object tracking vot2022 challenge results. In: European Conference on Computer Vision ECCV2022 Workshops (2022) Kristan, M., et. al.: Appendix of the tenth visual object tracking vot2022 challenge results. In: European Conference on Computer Vision ECCV2022 Workshops (2022)
6.
Zurück zum Zitat Kristan, M., et al.: The seventh visual object tracking vot2019 challenge results. In: ICCV2019 Workshops, Workshop on Visual Object Tracking Challenge (2019) Kristan, M., et al.: The seventh visual object tracking vot2019 challenge results. In: ICCV2019 Workshops, Workshop on Visual Object Tracking Challenge (2019)
8.
Zurück zum Zitat Kristan, M., et al.: The visual object tracking vot2018 challenge results. In: ECCV2018 Workshops, Workshop on Visual Object Tracking Challenge (2018) Kristan, M., et al.: The visual object tracking vot2018 challenge results. In: ECCV2018 Workshops, Workshop on Visual Object Tracking Challenge (2018)
9.
Zurück zum Zitat Kristan, M., et al.: The visual object tracking vot2017 challenge results. In: ICCV2017 Workshops, Workshop on Visual Object Tracking Challenge (2017) Kristan, M., et al.: The visual object tracking vot2017 challenge results. In: ICCV2017 Workshops, Workshop on Visual Object Tracking Challenge (2017)
11.
Zurück zum Zitat Kristan, M., et. al.: The ninth visual object tracking vot2021 challenge results. In: Proceedings of the IEEE/CVF International Conference on Computer Vision ICCV2021 Workshops, Workshop On Visual Object Tracking Challenge, pp. 2711–2738 (2021) Kristan, M., et. al.: The ninth visual object tracking vot2021 challenge results. In: Proceedings of the IEEE/CVF International Conference on Computer Vision ICCV2021 Workshops, Workshop On Visual Object Tracking Challenge, pp. 2711–2738 (2021)
12.
Zurück zum Zitat Kristan, M., et al.: The visual object tracking vot2015 challenge results. In: ICCV2015 Workshops, Workshop on Visual Object Tracking Challenge (2015) Kristan, M., et al.: The visual object tracking vot2015 challenge results. In: ICCV2015 Workshops, Workshop on Visual Object Tracking Challenge (2015)
13.
Zurück zum Zitat Kristan, M., et al.: The visual object tracking vot2013 challenge results. In: ICCV2013 Workshops, Workshop on Visual Object Tracking Challenge, pp. 98–111 (2013) Kristan, M., et al.: The visual object tracking vot2013 challenge results. In: ICCV2013 Workshops, Workshop on Visual Object Tracking Challenge, pp. 98–111 (2013)
15.
Zurück zum Zitat Lukežič, A., Kart, U., Kämäräinen, J., Matas, J., Kristan, M.: CDTB: A Color and Depth Visual Object Tracking Dataset and Benchmark. In: ICCV (2019) Lukežič, A., Kart, U., Kämäräinen, J., Matas, J., Kristan, M.: CDTB: A Color and Depth Visual Object Tracking Dataset and Benchmark. In: ICCV (2019)
16.
Zurück zum Zitat Lukežič, A., Čehovin Zajc, L., Vojír̃, T., Matas, J., Kristan, M.: Sperformance evaluation methodology for long-term single object tracking. IEEE Trans. Cybern. (2020) Lukežič, A., Čehovin Zajc, L., Vojír̃, T., Matas, J., Kristan, M.: Sperformance evaluation methodology for long-term single object tracking. IEEE Trans. Cybern. (2020)
18.
Zurück zum Zitat Mayer, C., Danelljan, M., Paudel, D.P., Van Gool, L.: Learning target candidate association to keep track of what not to track. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 13444–13454 (2021) Mayer, C., Danelljan, M., Paudel, D.P., Van Gool, L.: Learning target candidate association to keep track of what not to track. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 13444–13454 (2021)
19.
Zurück zum Zitat Nam, H., Han, B.: Learning multi-domain convolutional neural networks for visual tracking. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4293–4302 (2016) Nam, H., Han, B.: Learning multi-domain convolutional neural networks for visual tracking. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4293–4302 (2016)
20.
Zurück zum Zitat Touvron, H., Cord, M., Douze, M., Massa, F., Sablayrolles, A., Jégou, H.: Training data-efficient image transformers & distillation through attention. arXiv preprint arXiv:2012.12877 (2020) Touvron, H., Cord, M., Douze, M., Massa, F., Sablayrolles, A., Jégou, H.: Training data-efficient image transformers & distillation through attention. arXiv preprint arXiv:​2012.​12877 (2020)
22.
Zurück zum Zitat Wu, Y., Lim, J., Yang, M.H.: Online object tracking: A benchmark. Comp. Vis. Patt. Recogn. (2013) Wu, Y., Lim, J., Yang, M.H.: Online object tracking: A benchmark. Comp. Vis. Patt. Recogn. (2013)
23.
Zurück zum Zitat Yan, B., Peng, H., Fu, J., Wang, D., Lu, H.: Learning spatio-temporal transformer for visual tracking. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 10448–10457 (2021) Yan, B., Peng, H., Fu, J., Wang, D., Lu, H.: Learning spatio-temporal transformer for visual tracking. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 10448–10457 (2021)
24.
Zurück zum Zitat Yan, B., Zhang, X., Wang, D., Lu, H., Yang, X.: Alpha-refine: Boosting tracking performance by precise bounding box estimation. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 5289–5298 (2021) Yan, B., Zhang, X., Wang, D., Lu, H., Yang, X.: Alpha-refine: Boosting tracking performance by precise bounding box estimation. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 5289–5298 (2021)
25.
Zurück zum Zitat Yan, S., Yang, J., Käpylä, J., Zheng, F., Leonardis, A., Kämäräinen, J.K.: DepthTrack: Unveiling the power of RGBD tracking. In: Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), pp. 10725–10733 (2021) Yan, S., Yang, J., Käpylä, J., Zheng, F., Leonardis, A., Kämäräinen, J.K.: DepthTrack: Unveiling the power of RGBD tracking. In: Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), pp. 10725–10733 (2021)
26.
Zurück zum Zitat Yan, S., Yang, J., Leonardis, A., Kämäräinen, J.K.: Depth-only object tracking. In: British Machine Vision Conference (BMVC) (2021) Yan, S., Yang, J., Leonardis, A., Kämäräinen, J.K.: Depth-only object tracking. In: British Machine Vision Conference (BMVC) (2021)
27.
Zurück zum Zitat Yang, Z., Liu, S., Hu, H., Wang, L., Lin, S.: Reppoints: Point set representation for object detection. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9657–9666 (October 2019) Yang, Z., Liu, S., Hu, H., Wang, L., Lin, S.: Reppoints: Point set representation for object detection. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9657–9666 (October 2019)
28.
Zurück zum Zitat Yang, Z., Miao, J., Wang, X., Wei, Y., Yang, Y.: Associating objects with scalable transformers for video object segmentation. arXiv preprint arXiv:2203.11442 (2022) Yang, Z., Miao, J., Wang, X., Wei, Y., Yang, Y.: Associating objects with scalable transformers for video object segmentation. arXiv preprint arXiv:​2203.​11442 (2022)
29.
Zurück zum Zitat Ye, B., Chang, H., Ma, B., Shan, S.: Joint feature learning and relation modeling for tracking: A one-stream framework. arXiv preprint arXiv:2203.11991 (2022) Ye, B., Chang, H., Ma, B., Shan, S.: Joint feature learning and relation modeling for tracking: A one-stream framework. arXiv preprint arXiv:​2203.​11991 (2022)
Metadaten
Titel
The Tenth Visual Object Tracking VOT2022 Challenge Results
verfasst von
Matej Kristan
Aleš Leonardis
Jiří Matas
Michael Felsberg
Roman Pflugfelder
Joni-Kristian Kämäräinen
Hyung Jin Chang
Martin Danelljan
Luka Čehovin Zajc
Alan Lukežič
Ondrej Drbohlav
Johanna Björklund
Yushan Zhang
Zhongqun Zhang
Song Yan
Wenyan Yang
Dingding Cai
Christoph Mayer
Gustavo Fernández
Kang Ben
Goutam Bhat
Hong Chang
Guangqi Chen
Jiaye Chen
Shengyong Chen
Xilin Chen
Xin Chen
Xiuyi Chen
Yiwei Chen
Yu-Hsi Chen
Zhixing Chen
Yangming Cheng
Angelo Ciaramella
Yutao Cui
Benjamin Džubur
Mohana Murali Dasari
Qili Deng
Debajyoti Dhar
Shangzhe Di
Emanuel Di Nardo
Daniel K. Du
Matteo Dunnhofer
Heng Fan
Zhenhua Feng
Zhihong Fu
Shang Gao
Rama Krishna Gorthi
Eric Granger
Q. H. Gu
Himanshu Gupta
Jianfeng He
Keji He
Yan Huang
Deepak Jangid
Rongrong Ji
Cheng Jiang
Yingjie Jiang
Felix Järemo Lawin
Ze Kang
Madhu Kiran
Josef Kittler
Simiao Lai
Xiangyuan Lan
Dongwook Lee
Hyunjeong Lee
Seohyung Lee
Hui Li
Ming Li
Wangkai Li
Xi Li
Xianxian Li
Xiao Li
Zhe Li
Liting Lin
Haibin Ling
Bo Liu
Chang Liu
Si Liu
Huchuan Lu
Rafael M. O. Cruz
Bingpeng Ma
Chao Ma
Jie Ma
Yinchao Ma
Niki Martinel
Alireza Memarmoghadam
Christian Micheloni
Payman Moallem
Le Thanh Nguyen-Meidine
Siyang Pan
ChangBeom Park
Danda Paudel
Matthieu Paul
Houwen Peng
Andreas Robinson
Litu Rout
Shiguang Shan
Kristian Simonato
Tianhui Song
Xiaoning Song
Chao Sun
Jingna Sun
Zhangyong Tang
Radu Timofte
Chi-Yi Tsai
Luc Van Gool
Om Prakash Verma
Dong Wang
Fei Wang
Liang Wang
Liangliang Wang
Lijun Wang
Limin Wang
Qiang Wang
Gangshan Wu
Jinlin Wu
Xiaojun Wu
Fei Xie
Tianyang Xu
Wei Xu
Yong Xu
Yuanyou Xu
Wanli Xue
Zizheng Xun
Bin Yan
Dawei Yang
Jinyu Yang
Wankou Yang
Xiaoyun Yang
Yi Yang
Yichun Yang
Zongxin Yang
Botao Ye
Fisher Yu
Hongyuan Yu
Jiaqian Yu
Qianjin Yu
Weichen Yu
Kang Ze
Jiang Zhai
Chengwei Zhang
Chunhu Zhang
Kaihua Zhang
Tianzhu Zhang
Wenkang Zhang
Zhibin Zhang
Zhipeng Zhang
Jie Zhao
Shaochuan Zhao
Feng Zheng
Haixia Zheng
Min Zheng
Bineng Zhong
Jiawen Zhu
Xuefeng Zhu
Yueting Zhuang
Copyright-Jahr
2023
DOI
https://doi.org/10.1007/978-3-031-25085-9_25

Premium Partner