activity
20232026
most citedSGRec3D: Self-Supervised 3D Scene Graph Learning via Object-Level Scene Reconstruction

1 citations · 1 across the 8 of their papers we have counts for

collaborators

9 papers

cs.CV2026

GraphWrit3R: End-to-End 3D Scene Graph Writing

Luka Milivojevic, Nikola Popovic, Sayan Deb Sarkar +4

3D scene graphs provide a structured representation of complex environments by encoding objects, their semantic attributes, and the spatial and functional relationships between the…

cs.CV2026

GESTO: Human-Centric Spatio-Temporal Memory for Reasoning in Dynamic Scenes

Ermanno Bartoli, Buwei He, Dennis Rotondi +6

Robots operating in human environments need memories that capture not only what objects exist and where, but also how people use them over time and how individual interactions comp…

cs.RO2026

3D Scene Graphs: Open Challenges and Future Directions

Dennis Rotondi, Francesco Argenziano, Sebastian Koch +10

3D Scene Graphs (3DSGs) have emerged as a powerful representation for spatial AI by combining geometric grounding with semantic and relational abstractions of the environment. Thei…

cs.CV2025

Unified Semantic Transformer for 3D Scene Understanding

Sebastian Koch, Johanna Wald, Hidenobu Matsuki +3

Holistic 3D scene understanding involves capturing and parsing unstructured 3D environments. Due to the inherent complexity of the real world, existing models have predominantly be…

cs.CV2025

OpenHype: Hyperbolic Embeddings for Hierarchical Open-Vocabulary Radiance Fields

Lisa Weijler, Sebastian Koch, Fabio Poiesi +2

Modeling the inherent hierarchical structure of 3D objects and 3D scenes is highly desirable, as it enables a more holistic understanding of environments for autonomous agents. Acc…

cs.CV2024

RelationField: Relate Anything in Radiance Fields

Sebastian Koch, Johanna Wald, Mirco Colosi +4

Neural radiance fields are an emerging 3D scene representation and recently even been extended to learn features for scene understanding by distilling open-vocabulary features from…

cs.CV2024

Open3DSG: Open-Vocabulary 3D Scene Graphs from Point Clouds with Queryable Objects and Open-Set Relationships

Sebastian Koch, Narunas Vaskevicius, Mirco Colosi +2

Current approaches for 3D scene graph prediction rely on labeled datasets to train models for a fixed set of known object classes and relationship categories. We present Open3DSG,…

cs.CV2023

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…

cs.CV2023★ 1 cited

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…