collaborators

6 papers

cs.CV2024

ProtoSeg: A Prototype-Based Point Cloud Instance Segmentation Method

Remco Royen, Leon Denis, Adrian Munteanu

3D instance segmentation is crucial for obtaining an understanding of a point cloud scene. This paper presents a novel neural network architecture for performing instance segmentat…

cs.CV2024

RESSCAL3D++: Joint Acquisition and Semantic Segmentation of 3D Point Clouds

Remco Royen, Kostas Pataridis, Ward van der Tempel +1

3D scene understanding is crucial for facilitating seamless interaction between digital devices and the physical world. Real-time capturing and processing of the 3D scene are essen…

cs.CV2024

RT-GS2: Real-Time Generalizable Semantic Segmentation for 3D Gaussian Representations of Radiance Fields

Mihnea-Bogdan Jurca, Remco Royen, Ion Giosan +1

Gaussian Splatting has revolutionized the world of novel view synthesis by achieving high rendering performance in real-time. Recently, studies have focused on enriching these 3D r…

cs.CV2024

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…

cs.CV2024

Joint prototype and coefficient prediction for 3D instance segmentation

Remco Royen, Leon Denis, Adrian Munteanu

3D instance segmentation is crucial for applications demanding comprehensive 3D scene understanding. In this paper, we introduce a novel method that simultaneously learns coefficie…

cs.CV2024

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…