3 papers
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…
cs.GR2026
DreamAnywhere: Object-Centric Panoramic 3D Scene Generation
Edoardo Alberto Dominici, Jozef Hladky, Floor Verhoeven +9
Recent advances in text-to-3D scene generation have demonstrated significant potential to transform content creation across multiple industries. Although the research community has…