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cs.CV2026

LGTM: Training-Free Light-Guided Text-to-Image Diffusion Model via Initial Noise Manipulation

Ryugo Morita, Stanislav Frolov, Brian Bernhard Moser +3

Diffusion models have demonstrated high-quality performance in conditional text-to-image generation, particularly with structural cues such as edges, layouts, and depth. However, l…

cs.CV2025

Towards Facilitated Fairness Assessment of AI-based Skin Lesion Classifiers Through GenAI-based Image Synthesis

Ko Watanabe, Stanislav Frolov, Aya Hassan +3

Recent advances in deep learning and on-device inference could transform routine screening for skin cancers. Along with the anticipated benefits of this technology, potential dange…

cs.CV2025

EMF: Event Meta Formers for Event-based Real-time Traffic Object Detection

Muhammad Ahmed Ullah Khan, Abdul Hannan Khan, Andreas Dengel

Event cameras have higher temporal resolution, and require less storage and bandwidth compared to traditional RGB cameras. However, due to relatively lagging performance of event-b…

cs.CV2025

Spherical Dense Text-to-Image Synthesis

Timon Winter, Stanislav Frolov, Brian Bernhard Moser +1

Recent advancements in text-to-image (T2I) have improved synthesis results, but challenges remain in layout control and generating omnidirectional panoramic images. Dense T2I (DT2I…

cs.CV2025

A Study in Dataset Distillation for Image Super-Resolution

Tobias Dietz, Brian B. Moser, Tobias Nauen +3

Dataset distillation aims to compress large datasets into compact yet highly informative subsets that preserve the training behavior of the original data. While this concept has ga…

cs.CV2025

Multi-Label Scene Classification in Remote Sensing Benefits from Image Super-Resolution

Ashitha Mudraje, Brian B. Moser, Stanislav Frolov +1

Satellite imagery is a cornerstone for numerous Remote Sensing (RS) applications; however, limited spatial resolution frequently hinders the precision of such systems, especially i…