Luca Bertinetto

Publications25
h-index16
Citations5,535
Highly Influential Citations1,430
Author pages are created from data sourced from our academic publisher partnerships and public sources.

Recommended Authors

  • P. Torr
  • 380 Publications, 35,238 Citations
  • Jiri Matas
  • 374 Publications, 37,621 Citations
  • M. Kristan
  • 131 Publications, 5,255 Citations
  • M. Felsberg
  • 224 Publications, 13,576 Citations
  • Publications
  • Influence
Fully-Convolutional Siamese Networks for Object Tracking
TLDR
The problem of arbitrary object tracking has traditionally been tackled by learning a model of the object’s appearance exclusively online, using as sole training data the video itself. Expand
  • 1,562
  • 435
  • PDF
Staple: Complementary Learners for Real-Time Tracking
TLDR
A simple tracker combining complementary cues in a ridge regression framework can operate faster than 80 FPS and outperform not only all entries in the popular VOT14 competition, but also recent and far more sophisticated trackers according to multiple benchmarks. Expand
  • 969
  • 290
  • PDF
End-to-End Representation Learning for Correlation Filter Based Tracking
TLDR
We interpret the Correlation Filter learner, which has a closed-form solution, as a differentiable layer in a deep neural network. Expand
  • 799
  • 188
  • PDF
The Visual Object Tracking VOT2016 Challenge Results
TLDR
The Visual Object Tracking challenge VOT2016 aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance. Expand
  • 500
  • 165
  • PDF
The Sixth Visual Object Tracking VOT2018 Challenge Results
TLDR
The Visual Object Tracking challenge VOT2018 is the sixth annual tracker benchmarking activity organized by the VOT initiative. Expand
  • 249
  • 71
  • PDF
Fast Online Object Tracking and Segmentation: A Unifying Approach
TLDR
SiamMask improves the offline training procedure of popular fully-convolutional Siamese approaches for object tracking by augmenting their loss with a binary segmentation task. Expand
  • 296
  • 70
  • PDF
The Visual Object Tracking VOT2017 Challenge Results
TLDR
The Visual Object Tracking challenge VOT2017 is the fifth annual tracker benchmarking activity organized by the VOT initiative. Expand
  • 286
  • 66
  • PDF
Meta-learning with differentiable closed-form solvers
TLDR
In this paper, we propose to use these fast convergent methods as the main adaptation mechanism for few-shot learning. Expand
  • 211
  • 65
  • PDF
Learning feed-forward one-shot learners
TLDR
In this paper, we propose a method to learn the parameters of a deep model from a single exemplar in a learning to learn formulation. Expand
  • 261
  • 20
  • PDF
The Seventh Visual Object Tracking VOT2019 Challenge Results
TLDR
The Visual Object Tracking challenge VOT2019 is the seventh annual tracker benchmarking activity organized by the VOT initiative. Expand
  • 85
  • 19
  • PDF