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wangsssssss/
FlowDCN

Name: FlowDCN
Rating: 2.5 (10 reviews)

2410.22655

mit

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[NeurIPS24] FlowDCN: Exploring DCN-like Architectures for Fast Image Generation with Arbitrary Resolution

https://arxiv.org/abs/2410.22655

[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

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

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}
}

wangsssssss/FlowDCN