5 citations · 9 across the 16 of their papers we have counts for
4 papers · 1 filter
Lang3DSG: Language-based contrastive pre-training for 3D Scene Graph prediction
Sebastian Koch, Pedro Hermosilla, Narunas Vaskevicius +2
D scene graphs are an emerging 3D scene representation, that models both the objects present in the scene as well as their relationships. However, learning 3D scene graphs is a cha…
SGRec3D: Self-Supervised 3D Scene Graph Learning via Object-Level Scene Reconstruction
Sebastian Koch, Pedro Hermosilla, Narunas Vaskevicius +2
In the field of 3D scene understanding, 3D scene graphs have emerged as a new scene representation that combines geometric and semantic information about objects and their relation…
Unsupervised Semantic Segmentation Through Depth-Guided Feature Correlation and Sampling
Leon Sick, Dominik Engel, Pedro Hermosilla +1
Traditionally, training neural networks to perform semantic segmentation required expensive human-made annotations. But more recently, advances in the field of unsupervised learnin…
Leveraging Self-Supervised Vision Transformers for Segmentation-based Transfer Function Design
Dominik Engel, Leon Sick, Timo Ropinski
In volume rendering, transfer functions are used to classify structures of interest, and to assign optical properties such as color and opacity. They are commonly defined as 1D or…