CONFLUX: A Latent Diusion Model for 3D Chest-CT Synthesis with RL Post-Training
A 3D latent diffusion model for chest CT generation that achieves high-fidelity results while enabling control over clinical attributes through metadata conditioning and reinforcem…
Hugging Face · Daily Papers
·Max Van Puyvelde, Halil Ibrahim Gulluk
·
·▲ 1 upvotes
Este artigo está em destaque na seleção diária de papers do Hugging Face, curada pela comunidade de pesquisa em IA.
Autores: Max Van Puyvelde, Halil Ibrahim Gulluk, Wim Van Criekinge, Olivier Gevaert
- 1 upvotes da comunidade
- Temas: latent diffusion model, 3D variational autoencoder, rectified-flow transformer, adaptive layer normalization, tri-planar Frechet distance, FID
Resumo
Resumo original (em inglês), extraído do paper:
A 3D latent diffusion model for chest CT generation that achieves high-fidelity results while enabling control over clinical attributes through metadata conditioning and reinforcement learning refinement.Onde ler
// relacionados
Leia também
Blog
How AI could enable autonomous robot workers in workplaces—and maybe homes
Blog
NVIDIA and Hugging Face Bring New Models and Frameworks to LeRobot for the Open Robotics Community
Blog
HiMe: Hierarchical Embodied Memory for Long-Horizon Vision-Language-Action Control
Blog