7 citations · 8 across the 5 of their papers we have counts for
5 papers
HaarNet: Large-scale Linear-Morphological Hybrid Network for RGB-D Semantic Segmentation
Rick Groenendijk, Leo Dorst, Theo Gevers
Signals from different modalities each have their own combination algebra which affects their sampling processing. RGB is mostly linear; depth is a geometric signal following the o…
Relational Prior Knowledge Graphs for Detection and Instance Segmentation
Osman Ülger, Yu Wang, Ysbrand Galama +3
Humans have a remarkable ability to perceive and reason about the world around them by understanding the relationships between objects. In this paper, we investigate the effectiven…
APNet: Urban-level Scene Segmentation of Aerial Images and Point Clouds
Weijie Wei, Martin R. Oswald, Fatemeh Karimi Nejadasl +1
In this paper, we focus on semantic segmentation method for point clouds of urban scenes. Our fundamental concept revolves around the collaborative utilization of diverse scene rep…
SIGNet: Intrinsic Image Decomposition by a Semantic and Invariant Gradient Driven Network for Indoor Scenes
Partha Das, Sezer Karaoglu, Arjan Gijsenij +1
Intrinsic image decomposition (IID) is an under-constrained problem. Therefore, traditional approaches use hand crafted priors to constrain the problem. However, these constraints…
Road Detection by One-Class Color Classification: Dataset and Experiments
Jose M. Alvarez, Theo Gevers, Antonio M. Lopez
Detecting traversable road areas ahead a moving vehicle is a key process for modern autonomous driving systems. A common approach to road detection consists of exploiting color fea…