Abstract: This paper presents a novel methodology for generating synthetic images that adhere accurately to provided semantic segmentation maps using the Stable Diffusion model with the ControlNet ...

[2024.09.26] 👏👏👏 Our paper has been accepted to NeurIPS 2024!!! [2024.06.06] 🔥🔥🔥 We are excited to release the code for Open-Sora Plan v1.1.0. Thanks to the authors for open-sourcing the awesome ...

If you find this code useful in your research, please cite: @article{cohan2024flexible, title={Flexible Motion In-betweening with Diffusion Models}, author={Cohan, Setareh and Tevet, Guy and Reda, ...

Abstract: We explore a new class of diffusion models based on the transformer architecture. We train latent diffusion models of images, replacing the commonly-used U-Net backbone with a transformer ...