61 citations · 112 across the 4 of their papers we have counts for
10 papers · 1 filter
TripletTrack: 3D Object Tracking using Triplet Embeddings and LSTM
Nicola Marinello, Marc Proesmans, Luc Van Gool
3D object tracking is a critical task in autonomous driving systems. It plays an essential role for the system's awareness about the surrounding environment. At the same time there…
Weakly-Supervised Semantic Segmentation by Learning Label Uncertainty
Robby Neven, Davy Neven, Bert De Brabandere +2
Since the rise of deep learning, many computer vision tasks have seen significant advancements. However, the downside of deep learning is that it is very data-hungry. Especially fo…
MonoCInIS: Camera Independent Monocular 3D Object Detection using Instance Segmentation
Jonas Heylen, Mark De Wolf, Bruno Dawagne +5
Monocular 3D object detection has recently shown promising results, however there remain challenging problems. One of those is the lack of invariance to different camera intrinsic…
Context-aware Padding for Semantic Segmentation
Yu-Hui Huang, Marc Proesmans, Luc Van Gool
Zero padding is widely used in convolutional neural networks to prevent the size of feature maps diminishing too fast. However, it has been claimed to disturb the statistics at the…
SCAN: Learning to Classify Images without Labels
Wouter Van Gansbeke, Simon Vandenhende, Stamatios Georgoulis +2
Can we automatically group images into semantically meaningful clusters when ground-truth annotations are absent? The task of unsupervised image classification remains an important…
Multi-Task Learning for Dense Prediction Tasks: A Survey
Simon Vandenhende, Stamatios Georgoulis, Wouter Van Gansbeke +3
With the advent of deep learning, many dense prediction tasks, i.e. tasks that produce pixel-level predictions, have seen significant performance improvements. The typical approach…