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A Probabilistic Perspective on Wasserstein-Based Evidential Uncertainty for Out-of-Distribution Segmentation
Arnold Brosch, Abdelrahman Eldesokey, Michael Felsberg +1
Semantic segmentation networks operate on a fixed set of classes and therefore fail when out-of-distribution (OOD) objects appear during deployment, a critical limitation for safet…
HMR-Net: Hierarchical Modular Routing for Cross-Domain Object Detection in Aerial Images
Pourya Shamsolmoali, Masoumeh Zareapoor, Michael Felsberg +3
Despite advances in object detection, aerial imagery remains a challenging domain, as models often fail to generalize across variations in spatial resolution, scene composition, an…
DisasterInsight: A Building-Centric Benchmark for Evaluating Vision--Language Models in Disaster Response
Sara Tehrani, Yonghao Xu, Leif Haglund +3
Vision--language models (VLMs) show promise for disaster-response remote sensing, but existing benchmarks mainly emphasize scene-level or damage-centric assessment. To study this b…
VLM2GeoVec: Toward Universal Multimodal Embeddings for Remote Sensing
Emanuel Sánchez Aimar, Gulnaz Zhambulova, Fahad Shahbaz Khan +2
Satellite imagery differs from natural images in viewpoint, resolution, scale variation, and the prevalence of small objects -- demanding both region-level spatial reasoning and ho…
Out-of-Distribution Segmentation via Wasserstein-Based Evidential Uncertainty
Arnold Brosch, Abdelrahman Eldesokey, Michael Felsberg +1
Deep neural networks achieve superior performance in semantic segmentation, but are limited to a predefined set of classes, which leads to failures when they encounter unknown obje…
R3D2: Realistic 3D Asset Insertion via Diffusion for Autonomous Driving Simulation
William Ljungbergh, Bernardo Taveira, Wenzhao Zheng +8
Validating autonomous driving (AD) systems requires diverse and safety-critical testing, making photorealistic virtual environments essential. Traditional simulation platforms, whi…
From Missing Pieces to Masterpieces: Image Completion with Context-Adaptive Diffusion
Pourya Shamsolmoali, Masoumeh Zareapoor, Huiyu Zhou +3
Image completion is a challenging task, particularly when ensuring that generated content seamlessly integrates with existing parts of an image. While recent diffusion models have…
All Languages Matter: Evaluating LMMs on Culturally Diverse 100 Languages
Ashmal Vayani, Dinura Dissanayake, Hasindri Watawana +66
Existing Large Multimodal Models (LMMs) generally focus on only a few regions and languages. As LMMs continue to improve, it is increasingly important to ensure they understand cul…