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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.

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}
}
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Dataset used to train ysng/EG-FM-ImageNet

Paper for ysng/EG-FM-ImageNet