---
license: mit
---

## [NeurIPS24] FlowDCN: Exploring DCN-like Architectures for Fast Image Generation with Arbitrary Resolution
[https://arxiv.org/abs/2410.22655](https://arxiv.org/abs/2410.22655)

![caps](./viscaption5.png)


### [NEWS] [9.26] 💐💐 Our FlowDCN is accepted by NeurIPS 2024! 💐💐
### [NEWS] [11.22] 🍺 Our FlowDCN models and code are now available in the official repo!

## Pretrained Models
Our Models consistently achieve state-of-the-art results on the sFID metrics compared to SiT/DiT.

### Metrics 
Our Models consistently has fewer parameters and GFLOPS compared to Transformer counterparts. 
Our code also support LogNorm and VAR(Various Aspect Ratio Training)

|    Model-iters     | Resolution |     Solver      | NFE-CFG | FID  | sFID | Params |
|:------------------:|:----------:|:---------------:|:-------:|:----:|:----:|:------:|
|   FlowDCN-S-400k   |  256x256   |  EulerSDE-250   |  250x2  | 54.6 | 8.8  | 30.3M  |
|   FlowDCN-B-400k   |  256x256   |  EulerSDE-250   |  250x2  | 28.5 | 6.09 |  120M  |
| VAR-FlowDCN-B-400k |  256x256   |  EulerSDE-250   |  250x2  | 23.6 | 7.72 |  120M  |
|   FlowDCN-L-400k   |  256x256   |  EulerSDE-250   |  250x2  | 13.8 | 4.69 |  421M  |
|   FlowDCN-XL-2M    |  256x256   |  EulerODE-250   |  250x2  | 2.01 | 4.33 |  618M  |
|   FlowDCN-XL-2M    |  256x256   |  EulerSDE-250   |  250x2  | 2.00 | 4.37 |  618M  |
|   FlowDCN-XL-2M    |  256x256   | NeuralSolver-10 |  10x2   | 2.35 | 5.07 |  618M  |
|  FlowDCN-XL-100k   |  512x512   |   EulerODE-50   |  50x2   | 2.76 | 5.29 |  618M  |
|  FlowDCN-XL-100k   |  512x512   |  EulerSDE-250   |  250x2  | 2.44 | 4.53 |  618M  |
|  FlowDCN-XL-100k   |  512x512   | NeuralSolver-10 |  10x2   | 2.77 | 4.68 |  618M  |

### Visualizations

![caps](./vis_ode.png)

### Various Resolution Extension
| Models | 256x256 FID      | sFID  | IS    | 320x320 FID | sFID  | IS     | 224x448 FID | sFID  | IS     | 160x480 FID | sFID  | IS     |
|------------------|-------|-------|-------------|-------|--------|-------------|-------|--------|-------------|-------|--------|-------|
| DiT-B            | 44.83 | 8.49  | 32.05       | 95.47 | 108.68 | 18.38       | 109.1 | 110.71 | 14.00       | 143.8 | 122.81 | 8.93  |
| with EI          | 44.83 | 8.49  | 32.05       | 81.48 | 62.25  | 20.97       | 133.2 | 72.53  | 11.11       | 160.4 | 93.91  | 7.30  |
| with PI          | 44.83 | 8.49  | 32.05       | 72.47 | 54.02  | 24.15       | 133.4 | 70.29  | 11.73       | 156.5 | 93.80  | 7.80  |
| FiT-B (+VAR)     | 36.36 | 11.08 | 40.69       | 61.35 | 30.71  | 31.01       | 44.67 | 24.09  | 37.1        | 56.81 | 22.07  | 25.25 |
| with VisionYaRN  | 36.36 | 11.08 | 40.69       | 44.76 | 38.04  | 44.70       | 41.92 | 42.79  | 45.87       | 62.84 | 44.82  | 27.84 |
| with VisionNTK   | 36.36 | 11.08 | 40.69       | 57.31 | 31.31  | 33.97       | 43.84 | 26.25  | 39.22       | 56.76 | 24.18  | 26.40 |
| FlowDCN-B        | 28.5  | 6.09  | 51          | 34.4  | 27.2   | 52.2        | 71.7  | 62.0   | 23.7        | 211   | 111    | 5.83  |
| FlowDCN-B (+VAR) | 23.6  | 7.72  | 62.8        | 29.1  | 15.8   | 69.5        | 31.4  | 17.0   | 62.4        | 44.7  | 17.8   | 35.8  |


[//]: # ()
[//]: # (![caps](./figs/var_fid.png))


## Citation
```bibtex
@inproceedings{
wang2024exploring,
title={Exploring {DCN}-like architecture for fast image generation with arbitrary resolution},
author={Shuai Wang and Zexian Li and Tianhui Song and Xubin Li and Tiezheng Ge and Bo Zheng and Limin Wang},
booktitle={The Thirty-eighth Annual Conference on Neural Information Processing Systems},
year={2024},
url={https://openreview.net/forum?id=e57B7BfA2B}
}
```