474 citations · 977 across the 6 of their papers we have counts for
10 papers
A Simple Latent Diffusion Approach for Panoptic Segmentation and Mask Inpainting
Wouter Van Gansbeke, Bert De Brabandere
Panoptic and instance segmentation networks are often trained with specialized object detection modules, complex loss functions, and ad-hoc post-processing steps to manage the perm…
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)…