SwePub
Tyck till om SwePub Sök här!
Sök i SwePub databas

  Utökad sökning

Träfflista för sökning "WFRF:(Marvasti Zadeh S.M.) "

Sökning: WFRF:(Marvasti Zadeh S.M.)

  • Resultat 1-1 av 1
Sortera/gruppera träfflistan
   
NumreringReferensOmslagsbildHitta
1.
  • Kristan, M., et al. (författare)
  • The Eighth Visual Object Tracking VOT2020 Challenge Results
  • 2020
  • Ingår i: Computer Vision. - Cham : Springer International Publishing. - 9783030682378 ; , s. 547-601
  • Konferensbidrag (refereegranskat)abstract
    • The Visual Object Tracking challenge VOT2020 is the eighth annual tracker benchmarking activity organized by the VOT initiative. Results of 58 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years. The VOT2020 challenge was composed of five sub-challenges focusing on different tracking domains: (i) VOT-ST2020 challenge focused on short-term tracking in RGB, (ii) VOT-RT2020 challenge focused on “real-time” short-term tracking in RGB, (iii) VOT-LT2020 focused on long-term tracking namely coping with target disappearance and reappearance, (iv) VOT-RGBT2020 challenge focused on short-term tracking in RGB and thermal imagery and (v) VOT-RGBD2020 challenge focused on long-term tracking in RGB and depth imagery. Only the VOT-ST2020 datasets were refreshed. A significant novelty is introduction of a new VOT short-term tracking evaluation methodology, and introduction of segmentation ground truth in the VOT-ST2020 challenge – bounding boxes will no longer be used in the VOT-ST challenges. A new VOT Python toolkit that implements all these novelites was introduced. Performance of the tested trackers typically by far exceeds standard baselines. The source code for most of the trackers is publicly available from the VOT page. The dataset, the evaluation kit and the results are publicly available at the challenge website (http://votchallenge.net ). 
  •  
Skapa referenser, mejla, bekava och länka
  • Resultat 1-1 av 1
Typ av publikation
konferensbidrag (1)
Typ av innehåll
refereegranskat (1)
Författare/redaktör
Chen, S. (1)
Chen, Y. (1)
Jiang, Y. (1)
Li, B. (1)
Li, H. (1)
Li, Y. (1)
visa fler...
Liu, K. (1)
Peng, H. (1)
Wang, F. (1)
Yu, J. (1)
Zhang, H. (1)
Zhang, L. (1)
Zhang, X. (1)
Zhang, Z. (1)
Yao, Y. (1)
Li, J. (1)
Chen, G. (1)
Choi, S. (1)
Wu, Z. (1)
Wang, D. (1)
Wang, Y. (1)
Zhu, X. (1)
Wang, Z. (1)
Wang, L (1)
Yang, X. (1)
Zhang, P (1)
Lee, J. (1)
Yang, J. (1)
Wang, N. (1)
Wang, Q. (1)
Xu, J (1)
Tang, Z. (1)
Zhao, S (1)
Fernandez, G (1)
Gu, Y. (1)
Cheng, L (1)
Lu, W (1)
Fan, H (1)
Zhao, H (1)
Yu, K (1)
Lu, H (1)
Ye, Y. (1)
Xu, T. (1)
Ma, Z (1)
Zhou, W. (1)
Gustafsson, F. (1)
Lee, Y (1)
Fu, J. (1)
Yang, K (1)
Yan, B. (1)
visa färre...
Lärosäte
Linköpings universitet (1)
Språk
Engelska (1)
Forskningsämne (UKÄ/SCB)
Naturvetenskap (1)
År
2020 (1)

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Stäng

Kopiera och spara länken för att återkomma till aktuell vy