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cs.CV2026
The Domain Is a Residue: Adapting Self-Supervised Features, Not Generators
Thomas Deixelberger, Markus Steinberger
Clearing fog, rain or snow from footage, or turning renders into photographs, must remove the source domain and keep the scene. Unpaired translators carry it through because their…
cs.CV2026
Control-DINO: Feature Space Conditioning for Controllable Image-to-Video Diffusion
Edoardo A. Dominici, Thomas Deixelberger, Konstantinos Vardis +1
Video diffusion models have recently been applied with success to problems in content generation, novel view synthesis, and, more broadly, world simulation. Many applications in ge…
cs.CV2026
Scene Generation at Absolute Scale: Utilizing Semantic and Geometric Guidance From Text for Accurate and Interpretable 3D Indoor Scene Generation
Stefan Ainetter, Thomas Deixelberger, Edoardo A. Dominici +3
We present GuidedSceneGen, a text-to-3D generation framework that produces metrically accurate, globally consistent, and semantically interpretable indoor scenes. Unlike prior text…