Energy-Guided Flow Matching (EG-FM)
Official checkpoints for Energy-Guided Flow Matching (EG-FM) on class-conditional ImageNet-1K generation at 256×256 and 512×512 resolutions.
EG-FM introduces an image-specific, energy-guided moving endpoint to construct an explicit coarse-to-fine generation trajectory while requiring no changes to the backbone or training data.
- Paper: Energy-Guided Flow Matching
- Code and usage: ysng123/EG-FM
Released models
| Model | Resolution | Training | FID |
|---|---|---|---|
| PixelDiT-200 | 256×256 | 200 epochs | 1.55 |
| PixelDiT-600 | 256×256 | 600 epochs | 1.45 |
| PixelDiT-220 | 512×512 | 200+20 epochs | 1.72 |
| PixelDiT-240 | 512×512 | 200+40 epochs | 1.68 |
All FID values use the ADM evaluation suite. The 512×512 models continue from the 200-epoch 256×256 checkpoint; 200+20 and 200+40 denote the initial training followed by additional high-resolution adaptation epochs.
For installation, checkpoint loading, inference, and evaluation commands, see the official GitHub repository.
License
The model weights are released under CC BY-NC 4.0. Commercial use is not permitted under this license.
Citation
@article{tong2026energy,
title = {Energy-Guided Flow Matching},
author = {Tong, Haoyang and He, Yu and Li, Fang and Ma, Lichen and Fu, Jingling and Chen, Dong and Chen, Zhen and Huang, Junshi and Cao, Jie},
journal = {arXiv preprint arXiv:2608.05811},
year = {2026}
}