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Predicting the Best of N Visual Trackers

Predicting the Best of N Visual Trackers

22 July 2024
B. Alawode
S. Javed
Arif Mahmood
Jirí Matas
ArXivPDFHTML

Papers citing "Predicting the Best of N Visual Trackers"

6 / 6 papers shown
Title
Transforming Model Prediction for Tracking
Transforming Model Prediction for Tracking
Christoph Mayer
Martin Danelljan
Goutam Bhat
M. Paul
D. Paudel
F. I. F. Richard Yu
Luc Van Gool
55
160
0
21 Mar 2022
WebUAV-3M: A Benchmark for Unveiling the Power of Million-Scale Deep UAV
  Tracking
WebUAV-3M: A Benchmark for Unveiling the Power of Million-Scale Deep UAV Tracking
Chunhui Zhang
Guanjie Huang
Li Liu
Shan Huang
Yinan Yang
Xiang Wan
Shiming Ge
Dacheng Tao
22
22
0
19 Jan 2022
Visual Object Tracking with Discriminative Filters and Siamese Networks:
  A Survey and Outlook
Visual Object Tracking with Discriminative Filters and Siamese Networks: A Survey and Outlook
S. Javed
Martin Danelljan
F. Khan
Muhammad Haris Khan
M. Felsberg
Jirí Matas
32
126
0
06 Dec 2021
Emerging Properties in Self-Supervised Vision Transformers
Emerging Properties in Self-Supervised Vision Transformers
Mathilde Caron
Hugo Touvron
Ishan Misra
Hervé Jégou
Julien Mairal
Piotr Bojanowski
Armand Joulin
283
5,723
0
29 Apr 2021
Improved Baselines with Momentum Contrastive Learning
Improved Baselines with Momentum Contrastive Learning
Xinlei Chen
Haoqi Fan
Ross B. Girshick
Kaiming He
SSL
229
3,029
0
09 Mar 2020
TrackingNet: A Large-Scale Dataset and Benchmark for Object Tracking in
  the Wild
TrackingNet: A Large-Scale Dataset and Benchmark for Object Tracking in the Wild
Matthias Muller
Adel Bibi
Silvio Giancola
Salman Al-Subaihi
Bernard Ghanem
192
785
0
28 Mar 2018
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