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The First Visual Object Tracking Segmentation VOTS2023 Challenge Results.

M. Kristan, J. Matas, M. Danelljan, M. Felsberg, H. Chang, L. Zajc, A. Lukezic, O. Drbohlav, Z. Zhang, K. Tran, X. Vu, J. Björklund, C. Mayer, Y. Zhang, L. Ke, J. Zhao, G. Fernández, N. Al-Shakarji, D. An, M. Arens, S. Becker, G. Bhat, S. Bullinger, A. Chan, S. Chang, H. Chen, X. Chen, Y. Chen, Z. Chen, Y. Cheng, Y. Cui, C. Deng, J. Dong, M. Dunnhofer, W. Feng, J. Fu, J. Gao, R. Han, Z. Hao, J. He, K. He, Z. He, X. Hu, K. Huang, Y. Huang, Y. Jiang, B. Kang, J. Lan, H. Lee, C. Li, J. Li, N. Li, W. Li, X. Li, X. Li, P. Liu, Y. Liu, H. Lu, B. Luo, P. Luo, Y. Ma, D. Miao, C. Micheloni, K. Palaniappan, H. Park, M. Paul, H. Peng, Z. Qian, G. Rahmon, N. Scherer-Negenborn, P. Shao, W. Shin, E. Kazemi, T. Song, R. Stiefelhagen, R. Sun, C. Tang, Z. Tang, I. Toubal, J. Valmadre, J. van de Weijer, L. Gool, J. Vira, S. Vujasinovic, C. Wan, J. Wan, D. Wang, F. Wang, F. Wang, H. Wang, L. Wang, S. Wang, Y. Wang, Z. Wang, G. Wu, J. Wu, Q. Wu, X. Wu, A. Xiao, J. Xie, C. Xu, M. Xu, T. Xu, Y. Xu, B. Yan, D. Yang, M. Yang, T. Yang, Y. Yang, Z. Yang, X. Yin, F. Yu, H. Yu, Q. Yu, W. Yu, Y. Yuan, Z. Yuan, J. Zhang, L. Zhang, T. Zhang, G. Zhao, S. Zhao, Y. Zheng, B. Zhong, J. Zhu, X. Zhu, Y. Zhuang, C. Zong, and K. Zuo. ICCV (Workshops), page 1788-1810. IEEE, (2023)

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Martin Danelljan

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How Reliable is Your Regression Model's Uncertainty Under Real-World Distribution Shifts?F. Gustafsson, M. Danelljan, and T. Schön. CoRR, (2023)AVisT: A Benchmark for Visual Object Tracking in Adverse Visibility.M. Noman, W. Ghallabi, D. Najiha, C. Mayer, A. Dudhane, M. Danelljan, H. Cholakkal, S. Khan, L. Gool, and F. Khan. CoRR, (2022)Accurate 3D Object Detection using Energy-Based Models.F. Gustafsson, M. Danelljan, and T. Schön. CoRR, (2020)GOCor: Bringing Globally Optimized Correspondence Volumes into Your Neural Network.P. Truong, M. Danelljan, L. Gool, and R. Timofte. NeurIPS, (2020)Dense Gaussian Processes for Few-Shot Segmentation.J. Johnander, J. Edstedt, M. Felsberg, F. Khan, and M. Danelljan. ECCV (29), volume 13689 of Lecture Notes in Computer Science, page 217-234. Springer, (2022)The Eighth Visual Object Tracking VOT2020 Challenge Results.M. Kristan, A. Leonardis, J. Matas, M. Felsberg, R. Pflugfelder, J. Kämäräinen, M. Danelljan, L. Zajc, A. Lukezic, O. Drbohlav and 98 other author(s). ECCV Workshops (5), volume 12539 of Lecture Notes in Computer Science, page 547-601. Springer, (2020)Evaluating Scalable Bayesian Deep Learning Methods for Robust Computer Vision.F. Gustafsson, M. Danelljan, and T. Schön. CVPR Workshops, page 1289-1298. Computer Vision Foundation / IEEE, (2020)NTIRE 2022 Challenge on Learning the Super-Resolution Space.A. Lugmayr, M. Danelljan, R. Timofte, K. Kim, Y. Kim, J. Lee, Z. Li, J. Pan, D. Shim, K. Song and 3 other author(s). CVPR Workshops, page 785-796. IEEE, (2022)Probabilistic Regression for Visual Tracking.M. Danelljan, L. Gool, and R. Timofte. CVPR, page 7181-7190. Computer Vision Foundation / IEEE, (2020)Mask Transfiner for High-Quality Instance Segmentation.L. Ke, M. Danelljan, X. Li, Y. Tai, C. Tang, and F. Yu. CVPR, page 4402-4411. IEEE, (2022)

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Disambiguation of "Danelljan, Martin"

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The First Visual Object Tracking Segmentation VOTS2023 Challenge Results.

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Martin Danelljan

Martin Klug

Martin Brückner

Martin Breitenfeldt

Martin Faes

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Disambiguation of "Danelljan, Martin"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML The First Visual Object Tracking Segmentation VOTS2023 Challenge Results.

Please choose a person to relate this publication to

Martin Danelljan

Martin Klug

Martin Brückner

Martin Breitenfeldt

Martin Faes

Other publications of authors with the same name

Disambiguation

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The First Visual Object Tracking Segmentation VOTS2023 Challenge Results.