45 citations · 57 across the 4 of their papers we have counts for
5 papers
Improved Block Merging for 3D Point Cloud Instance Segmentation
Leon Denis, Remco Royen, Adrian Munteanu
This paper proposes a novel block merging algorithm suitable for any block-based 3D instance segmentation technique. The proposed work improves over the state-of-the-art by allowin…
RESSCAL3D: Resolution Scalable 3D Semantic Segmentation of Point Clouds
Remco Royen, Adrian Munteanu
While deep learning-based methods have demonstrated outstanding results in numerous domains, some important functionalities are missing. Resolution scalability is one of them. In t…
ExpPoint-MAE: Better interpretability and performance for self-supervised point cloud transformers
Ioannis Romanelis, Vlassis Fotis, Konstantinos Moustakas +1
In this paper we delve into the properties of transformers, attained through self-supervision, in the point cloud domain. Specifically, we evaluate the effectiveness of Masked Auto…
Graph Convolutional Neural Networks with Node Transition Probability-based Message Passing and DropNode Regularization
Tien Huu Do, Duc Minh Nguyen, Giannis Bekoulis +2
Graph convolutional neural networks (GCNNs) have received much attention recently, owing to their capability in handling graph-structured data. Among the existing GCNNs, many metho…
Binary Rate Distortion With Side Information: The Asymmetric Correlation Channel Case
Andrei Sechelea, Samuel Cheng, Adrian Munteanu +1
Advancing over up-to-date information theoretic results that assume symmetric correlation models, in this work we consider the problem of lossy binary source coding with side infor…