6 papers · 1 filter
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…
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…
Confidence-Based Mesh Extraction from 3D Gaussians
Lukas Radl, Felix Windisch, Andreas Kurz +3
Recently, 3D Gaussian Splatting (3DGS) greatly accelerated mesh extraction from posed images due to its explicit representation and fast software rasterization. While the addition…
Autoregressive Appearance Prediction for 3D Gaussian Avatars
Michael Steiner, Zhang Chen, Alexander Richard +3
A photorealistic and immersive human avatar experience demands capturing fine, person-specific details such as cloth and hair dynamics, subtle facial expressions, and characteristi…
Taming 3DGS: High-Quality Radiance Fields with Limited Resources
Saswat Subhajyoti Mallick, Rahul Goel, Bernhard Kerbl +3
3D Gaussian Splatting (3DGS) has transformed novel-view synthesis with its fast, interpretable, and high-fidelity rendering. However, its resource requirements limit its usability.…
LAENeRF: Local Appearance Editing for Neural Radiance Fields
Lukas Radl, Michael Steiner, Andreas Kurz +1
Due to the omnipresence of Neural Radiance Fields (NeRFs), the interest towards editable implicit 3D representations has surged over the last years. However, editing implicit or hy…