collaborators
Showing cs.CVShow all

13 papers · 1 filter

cs.CV2026

OvDSGG: End-to-End Open-Vocabulary Dynamic Scene Graph Generation

John Helsby, Yi Yang, Bodo Rosenhahn +1

Dynamic scene graphs (DSGs) capture spatio-temporal interactions across videos as subject, predicate, object triplets, and underpin downstream tasks such as video…

cs.CV2026

Seeing Before Answering: Training-Free Visual Layer Profiling for Vision-Language Models

Ruchen Liu, Yi Yang, Yiming Xu +3

LLaVA-style Vision-Language Models (VLMs) pass visual tokens from a fixed late layer of the vision backbone, typically the penultimate one, to the language model. We first show tha…

cs.CV2026

PUF: Plug-and-Play Uncertainty-Aware Fusion for Online 3D Scene Graph Generation

Yi Yang, Myrna Castillo, Bodo Rosenhahn +1

Online 3D scene graph generation builds a persistent, structured representation of a scene by incrementally fusing 2D observations into a global 3D graph. Existing online methods t…

cs.CV2026

MATCH: Flow Matching for Multi-View Anomaly Detection

Mathis Kruse, Melissa Schween, Bodo Rosenhahn

Detecting anomalies in industrial objects is an important topic for increasing production efficiency. More complex objects often require the analysis of several view points, which…

cs.CV2026

DINO-QPM: Adapting Visual Foundation Models for Globally Interpretable Image Classification

Robert Zimmermann, Thomas Norrenbrock, Bodo Rosenhahn

Although visual foundation models like DINOv2 provide state-of-the-art performance as feature extractors, their complex, high-dimensional representations create substantial hurdles…

cs.CV2026

Video Patch Pruning: Efficient Video Instance Segmentation via Early Token Reduction

Patrick Glandorf, Thomas Norrenbrock, Bodo Rosenhahn

Vision Transformers (ViTs) have demonstrated state-ofthe-art performance in several benchmarks, yet their high computational costs hinders their practical deployment. Patch Pruning…