activity
20162024
most citedBeyond Correlation Filters: Learning Continuous Convolution Operators for Visual Tracking

1.8k citations · 3.8k across the 19 of their papers we have counts for

collaborators
Showing 2018Show all

5 papers · 1 filter

cs.CV2018

A Generative Appearance Model for End-to-end Video Object Segmentation

Joakim Johnander, Martin Danelljan, Emil Brissman +2

One of the fundamental challenges in video object segmentation is to find an effective representation of the target and background appearance. The best performing approaches resort…

cs.CV2018

ATOM: Accurate Tracking by Overlap Maximization

Martin Danelljan, Goutam Bhat, Fahad Shahbaz Khan +1

While recent years have witnessed astonishing improvements in visual tracking robustness, the advancements in tracking accuracy have been limited. As the focus has been directed to…

cs.CV2018

Synthetic data generation for end-to-end thermal infrared tracking

Lichao Zhang, Abel Gonzalez-Garcia, Joost van de Weijer +2

The usage of both off-the-shelf and end-to-end trained deep networks have significantly improved performance of visual tracking on RGB videos. However, the lack of large labeled da…

cs.CV2018

Unveiling the Power of Deep Tracking

Goutam Bhat, Joakim Johnander, Martin Danelljan +2

In the field of generic object tracking numerous attempts have been made to exploit deep features. Despite all expectations, deep trackers are yet to reach an outstanding level of…

cs.CV2018

Density Adaptive Point Set Registration

Felix Järemo Lawin, Martin Danelljan, Fahad Shahbaz Khan +2

Probabilistic methods for point set registration have demonstrated competitive results in recent years. These techniques estimate a probability distribution model of the point clou…