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cs.CV2026

DSFlash: Comprehensive Panoptic Scene Graph Generation in Realtime

Julian Lorenz, Vladyslav Kovganko, Elias Kohout +3

Scene Graph Generation (SGG) aims to extract a detailed graph structure from an image, a representation that holds significant promise as a robust intermediate step for complex dow…

cs.CV2025

Uplifting Table Tennis: A Robust, Real-World Application for 3D Trajectory and Spin Estimation

Daniel Kienzle, Katja Ludwig, Julian Lorenz +2

Obtaining the precise 3D motion of a table tennis ball from standard monocular videos is a challenging problem, as existing methods trained on synthetic data struggle to generalize…

cs.CV2025

SkipClick: Combining Quick Responses and Low-Level Features for Interactive Segmentation in Winter Sports Contexts

Robin Schön, Julian Lorenz, Daniel Kienzle +1

In this paper, we present a novel architecture for interactive segmentation in winter sports contexts. The field of interactive segmentation deals with the prediction of high-quali…

cs.CV2025

MMMS: Multi-Modal Multi-Surface Interactive Segmentation

Robin Schön, Julian Lorenz, Katja Ludwig +2

In this paper, we present a method to interactively create segmentation masks on the basis of user clicks. We pay particular attention to the segmentation of multiple surfaces that…

cs.CV2025

CoPa-SG: Dense Scene Graphs with Parametric and Proto-Relations

Julian Lorenz, Mrunmai Phatak, Robin Schön +4

2D scene graphs provide a structural and explainable framework for scene understanding. However, current work still struggles with the lack of accurate scene graph data. To overcom…

cs.CV2025

HOIverse: A Synthetic Scene Graph Dataset With Human Object Interactions

Mrunmai Vivek Phatak, Julian Lorenz, Nico Hörmann +2

When humans and robotic agents coexist in an environment, scene understanding becomes crucial for the agents to carry out various downstream tasks like navigation and planning. Hen…