474 citations · 977 across the 6 of their papers we have counts for
5 papers · 1 filter
Instance Segmentation by Jointly Optimizing Spatial Embeddings and Clustering Bandwidth
Davy Neven, Bert De Brabandere, Marc Proesmans +1
Current state-of-the-art instance segmentation methods are not suited for real-time applications like autonomous driving, which require fast execution times at high accuracy. Altho…
Branched Multi-Task Networks: Deciding What Layers To Share
Simon Vandenhende, Stamatios Georgoulis, Bert De Brabandere +1
In the context of multi-task learning, neural networks with branched architectures have often been employed to jointly tackle the tasks at hand. Such ramified networks typically st…
A Three-Player GAN: Generating Hard Samples To Improve Classification Networks
Simon Vandenhende, Bert De Brabandere, Davy Neven +1
We propose a Three-Player Generative Adversarial Network to improve classification networks. In addition to the game played between the discriminator and generator, a competition i…
Sparse and noisy LiDAR completion with RGB guidance and uncertainty
Wouter Van Gansbeke, Davy Neven, Bert De Brabandere +1
This work proposes a new method to accurately complete sparse LiDAR maps guided by RGB images. For autonomous vehicles and robotics the use of LiDAR is indispensable in order to ac…
End-to-end Lane Detection through Differentiable Least-Squares Fitting
Wouter Van Gansbeke, Bert De Brabandere, Davy Neven +2
Lane detection is typically tackled with a two-step pipeline in which a segmentation mask of the lane markings is predicted first, and a lane line model (like a parabola or spline)…