notesum.ai

Published at November 26

TinyViM: Frequency Decoupling for Tiny Hybrid Vision Mamba

cs.CV

Released Date: November 26, 2024

Authors: Xiaowen Ma¹, Zhenliang Ni¹, Xinghao Chen¹

Aff.: ¹Huawei Noah's Ark Lab

Arxiv: http://arxiv.org/abs/2411.17473v1

Refer to caption

Model	Conference	Type	Params $\downarrow$ (M)	GMACs $\downarrow$	Throughput $\uparrow$ (im/s)	Epochs	Top-1 $\uparrow$ (%)
MobileOne-S1 [45]	CVPR’23	CNN	4.8	0.8	3545	300	75.9
SwiftFormer-S [39]	ICCV’23	Hybrid	6.1	1.0	2626	300	78.5
EfficientVMamba-T [36]	Arxiv’24	Mamba	6.1	1.0	1396	300	76.5
Vim-Ti [54]	ICML’24	Mamba	7.0	1.5	-	300	76.1
QuadMamba-Li [47]	NeurIPS’24	Mamba	5.4	0.8	1190	300	74.2
MSVMamba-N [40]	NeurIPS’24	Mamba	7.0	0.9	1283	300	77.3
TinyViM-S	-	CNN+Mamba	5.6	0.9	2563	300	79.2
PoolFormer-S12 [50]	CVPR’22	Pool	12.0	2.0	1902	300	77.2
MobileOne-S3 [45]	CVPR’23	CNN	10.1	1.9	1900	300	78.1
MobileOne-S4 [45]	CVPR’23	CNN	14.8	3.0	1223	300	79.4
Agent-PVT-T [15]	ECCV’24	ViT	11.6	2.0	1447	300	78.4
EfficientVMamba-S [36]	Arxiv’24	Mamba	11.0	1.3	674	300	78.7
QuadMamba-T [47]	NeurIPS’24	Mamba	10.0	2.0	585	300	78.2
MSVMamba-M [40]	NeurIPS’24	Mamba	12.0	1.5	957	300	79.8
TinyViM-B	-	CNN+Mamba	11.0	1.5	1851	300	81.2
PoolFormer-S36 [50]	CVPR’22	Pool	31.0	5.2	667	300	81.4
InceptionNext-T [51]	CVPR’24	CNN	28.0	4.2	987	300	82.3
Agent-PVT-S [15]	ECCV’24	ViT	20.6	4.0	686	300	82.4
FastViT-SA24 [44]	ICCV’23	Hybrid	20.6	3.8	861	300	82.6
EfficientVMamba-B [36]	Arxiv’24	Mamba	33.0	4.0	580	300	81.8
LocalVmamba-T [23]	Arxiv’24	Mamba	26.0	5.7	-	300	82.7
ViM-S [54]	ICML’24	Mamba	26.0	5.1	-	300	80.5
VMamba-T [30]	NeurIPS’24	Mamba	30.0	4.9	383	300	82.6
QuadMamba-S [47]	NeurIPS’24	Mamba	31.0	5.5	541	300	82.4
MSVmamba-T [40]	NeurIPS’24	Mamba	33.0	4.6	452	300	82.8
TinyViM-L	-	CNN+Mamba	31.7	4.7	843	300	83.3