activity
20242026
collaborators

8 papers

cs.CV2026

BIMScript: Material-Aware Structured Scene Programs for BIM Ingestion

Prakash Kondibhau Naikade, Thomas B. Moeslund, Andreas Møgelmose

Structured-language models such as SceneScript reconstruct a scene as a short program of parametric commands, an inherently editable and semantically explicit representation. We as…

cs.CV2026

HSA: Hierarchical Slot Attention for Multi-granularity Scene-Decomposition

Neelu Madan, Rongzhen Zhao, Andreas Mogelmose +4

Slot attention is a powerful framework for object-centric learning, decomposing visual scenes into latent slots through iterative competitive attention. However, existing methods s…

cs.CV2026

A Hyperbolic Perspective on Hierarchical Structure in Object-Centric Scene Representations

Neelu Madan, Àlex Pujol, Andreas Møgelmose +4

Slot attention has emerged as a powerful framework for unsupervised object-centric learning, decomposing visual scenes into a small set of compact vector representations called \em…

cs.CV2025

Multimodal classification of forest biodiversity potential from 2D orthophotos and 3D airborne laser scanning point clouds

Simon B. Jensen, Stefan Oehmcke, Andreas Møgelmose +4

Assessment of forest biodiversity is crucial for ecosystem management and conservation. While traditional field surveys provide high-quality assessments, they are labor-intensive a…

cs.CV2025

SlotMatch: Distilling Object-Centric Representations for Unsupervised Video Segmentation

Diana-Nicoleta Grigore, Neelu Madan, Andreas Mogelmose +2

Unsupervised video segmentation is a challenging computer vision task, especially due to the lack of supervisory signals coupled with the complexity of visual scenes. To overcome t…

cs.CV2025

Towards a Multi-Agent Vision-Language System for Zero-Shot Novel Hazardous Object Detection for Autonomous Driving Safety

Shashank Shriram, Srinivasa Perisetla, Aryan Keskar +4

Detecting anomalous hazards in visual data, particularly in video streams, is a critical challenge in autonomous driving. Existing models often struggle with unpredictable, out-of-…