62 citations · 62 across the 3 of their papers we have counts for
6 papers
No frame left behind: Full Video Action Recognition
Xin Liu, Silvia L. Pintea, Fatemeh Karimi Nejadasl +2
Not all video frames are equally informative for recognizing an action. It is computationally infeasible to train deep networks on all video frames when actions develop over hundre…
Adversarial Self-Supervised Scene Flow Estimation
Victor Zuanazzi, Joris van Vugt, Olaf Booij +1
This work proposes a metric learning approach for self-supervised scene flow estimation. Scene flow estimation is the task of estimating 3D flow vectors for consecutive 3D point cl…
KPRNet: Improving projection-based LiDAR semantic segmentation
Deyvid Kochanov, Fatemeh Karimi Nejadasl, Olaf Booij
Semantic segmentation is an important component in the perception systems of autonomous vehicles. In this work, we adopt recent advances in both image and point cloud segmentation…
Exploiting Temporality for Semi-Supervised Video Segmentation
Radu Sibechi, Olaf Booij, Nora Baka +1
In recent years, there has been remarkable progress in supervised image segmentation. Video segmentation is less explored, despite the temporal dimension being highly informative.…
I Bet You Are Wrong: Gambling Adversarial Networks for Structured Semantic Segmentation
Laurens Samson, Nanne van Noord, Olaf Booij +3
Adversarial training has been recently employed for realizing structured semantic segmentation, in which the aim is to preserve higher-level scene structural consistencies in dense…
EL-GAN: Embedding Loss Driven Generative Adversarial Networks for Lane Detection
Mohsen Ghafoorian, Cedric Nugteren, Nóra Baka +2
Convolutional neural networks have been successfully applied to semantic segmentation problems. However, there are many problems that are inherently not pixel-wise classification p…