Karsten Kreis
Papers
2
Total Citations
48
H-Index
2
About
Karsten Kreis is a leading researcher at the forefront of generative AI, with a primary focus on 3D scene generation and diffusion-based modeling. His most impactful work, "NeuralField-LDM: Scene Generation with Hierarchical Latent Diffusion Models" (2023, 43 citations), introduces a groundbreaking generative model that synthesizes complex, high-quality real-world 3D environments. By leveraging Latent Diffusion Models (LDMs) within a hierarchical framework, Kreis addresses a critical challenge in computer vision and graphics—automatically creating realistic 3D scenes for applications like virtual reality and robotics simulation. This contribution bridges the gap between 2D generative advances and 3D content creation, offering a scalable solution that combines neural fields with probabilistic diffusion. With additional citations (5) for related work, his research demonstrates growing influence in the field. Kreis’s work is notable for its practical impact, enabling immersive digital experiences and autonomous system training. His achievements position him as a key figure in advancing generative models for spatial intelligence, inspiring students and researchers to explore the intersection of deep learning and 3D world modeling.
Research Focus
Key Achievements
Top Papers
- 1NeuralField-LDM: Scene Generation with Hierarchical Latent Diffusion Models43 citations · 2023
- 2