Official PyTorch implementation of DiffiT: Diffusion Vision Transformers for Image Generation.

Code and pretrained DiffiT models will be released soon !

DiffiT achieves a new SOTA FID score of 1.73 on ImageNet-256 dataset !

In addition, DiffiT sets a new SOTA FID score of 2.22 on FFHQ-64 dataset !

We introduce a new Time-dependent Multihead Self-Attention (TMSA) mechanism that jointly learns spatial and temporal dependencies and allows for attention conditioning with finegrained control.

• [07.01.2024] 🔥🔥 DiffiT has been accepted to ECCV 2024 !
• [04.02.2024] Updated manuscript now available on arXiv !
• [12.04.2023] 🔥 Paper is published on arXiv !

@inproceedings{hatamizadeh2025diffit,
  title={Diffit: Diffusion vision transformers for image generation},
  author={Hatamizadeh, Ali and Song, Jiaming and Liu, Guilin and Kautz, Jan and Vahdat, Arash},
  booktitle={European Conference on Computer Vision},
  pages={37--55},
  year={2025},
  organization={Springer}
}

Copyright © 2024, NVIDIA Corporation. All rights reserved.