Heedless Backbones

MambaOut Family

Paper | GitHub

axis

Select an option

Results

Parameters (M)

Images / Second

Publication Date

task

Select an option

---------

Object Detection

Instance Segmentation

Classification

Semantic Segmentation

Panoptic Segmentation

dataset

Select an option

---------

COCO (val)

COCO (test)

PASCAL VOC 2007 (val)

PASCAL VOC 2007 (test)

metric

Select an option

----------

mAP

AP₅₀

AP₇₅

mAP_s

mAP_m

mAP_l

GFLOPs

head

Select an option

---------

Mask R-CNN

Cascade Mask R-CNN

RetinaNet

DINO

HTC++

HTC

FCOS

Faster R-CNN

axis

Select an option

Results

Parameters (M)

Images / Second

GFLOPs

Publication Date

Filters

pretrain dataset

Select an option

---------

ImageNet-1k

ImageNet-22k

JFT-300M

JFT-3B

MegData73M

pretrain method

Select an option

----------

Supervised

Sup. + TL

FCMAE

MAE

CL

MAP

Legend

Legend attribute

Select an option

Family

Pretrain Dataset

Instance Head

Instance Training Epochs

Legend attribute (second)

Select an option

----------

Family

Pretrain Method

Instance Head

Instance Training Epochs

model	params (m)	pretrain	head	train	GFLOPs	mAP
MambaOut-T	26.5	IN-1k : Sup. : 300	Mask R-CNN	COCO (train) : 12	262.0	45.1
MambaOut-S	48.5	IN-1k : Sup. : 300	Mask R-CNN	COCO (train) : 12	354.0	47.4
MambaOut-B	84.8	IN-1k : Sup. : 300	Mask R-CNN	COCO (train) : 12	495.0	47.4

model	params (m)	pretrain	finetune	gflops	IN-1k
MambaOut-Femto	7.3	IN-1k : Sup. : 300	— : — : —	1.2	78.9/—
MambaOut-T	26.5	IN-1k : Sup. : 300	— : — : —	4.5	82.7/—
MambaOut-S	48.5	IN-1k : Sup. : 300	— : — : —	9.0	84.1/—
MambaOut-B	84.8	IN-1k : Sup. : 300	— : — : —	15.8	84.2/—

COCO (val)

model	pretrain	head	train	gflops	mAP^b	AP^b₅₀	AP^b₇₅	mAP^b_s	mAP^b_m	mAP^b_l
MambaOut-T	IN-1k : Sup. : 300	Mask R-CNN	COCO (train) : 12	262.0	45.1	67.3	49.6	—	—	—
MambaOut-S	IN-1k : Sup. : 300	Mask R-CNN	COCO (train) : 12	354.0	47.4	69.1	52.4	—	—	—
MambaOut-B	IN-1k : Sup. : 300	Mask R-CNN	COCO (train) : 12	495.0	47.4	69.3	52.2	—	—	—

COCO (val)

model	pretrain	head	train	gflops	mAP^m	AP^m₅₀	AP^m₇₅	mAP^m_s	mAP^m_m	mAP^m_l
MambaOut-T	IN-1k : Sup. : 300	Mask R-CNN	COCO (train) : 12	262.0	41.0	64.1	44.1	—	—	—
MambaOut-S	IN-1k : Sup. : 300	Mask R-CNN	COCO (train) : 12	354.0	42.7	66.1	46.2	—	—	—
MambaOut-B	IN-1k : Sup. : 300	Mask R-CNN	COCO (train) : 12	495.0	43.0	66.4	46.3	—	—	—

ADE20K (val)

model	pretrain	head	train	gflops	mIoU^ms	pAcc^ms	mAcc^ms	mIoU^ss	pAcc^ss	mAcc^ss
MambaOut-T	IN-1k : Sup. : 300	UPerNet	ADE20K (train) : 128 : 512	938.0	48.6	—	—	47.4	—	—
MambaOut-S	IN-1k : Sup. : 300	UPerNet	ADE20K (train) : 128 : 512	1032.0	50.6	—	—	49.5	—	—
MambaOut-B	IN-1k : Sup. : 300	UPerNet	ADE20K (train) : 128 : 512	1178.0	51.0	—	—	49.6	—	—