2 citations · 3 across the 4 of their papers we have counts for
4 papers
A step towards understanding why classification helps regression
Silvia L. Pintea, Yancong Lin, Jouke Dijkstra +1
A number of computer vision deep regression approaches report improved results when adding a classification loss to the regression loss. Here, we explore why this is useful in prac…
Is there progress in activity progress prediction?
Frans de Boer, Jan C. van Gemert, Jouke Dijkstra +1
Activity progress prediction aims to estimate what percentage of an activity has been completed. Currently this is done with machine learning approaches, trained and evaluated on c…
Objects do not disappear: Video object detection by single-frame object location anticipation
Xin Liu, Fatemeh Karimi Nejadasl, Jan C. van Gemert +2
Objects in videos are typically characterized by continuous smooth motion. We exploit continuous smooth motion in three ways. 1) Improved accuracy by using object motion as an addi…
Making a Case for Learning Motion Representations with Phase
S. L. Pintea, J. C. van Gemert
This work advocates Eulerian motion representation learning over the current standard Lagrangian optical flow model. Eulerian motion is well captured by using phase, as obtained by…