Heedless Backbones

SW Family

Paper | GitHub

axis

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Results

Parameters (M)

Images / Second

Publication Date

task

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Object Detection

Instance Segmentation

Classification

Semantic Segmentation

Panoptic Segmentation

dataset

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COCO (val)

COCO (test)

Cityscapes (val)

Cityscapes (test)

ADE20K (val)

ADE20K (test)

metric

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mAP

AP₅₀

AP₇₅

mAP_s

mAP_m

mAP_l

GFLOPs

head

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Mask R-CNN

Cascade Mask R-CNN

Mask2Former

HTC++

HTC

Panoptic FPN

axis

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Results

Parameters (M)

Images / Second

GFLOPs

Publication Date

Filters

Legend

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Family

Pretrain Dataset

Instance Head

Instance Training Epochs

Legend attribute (second)

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Family

Pretrain Method

Instance Head

Instance Training Epochs

model	params (m)	pretrain	head	train	GFLOPs	mAP
SW-tiny	31.0	IN-1k : Sup. : 300	Cascade Mask R-CNN	COCO (train) : 36	751.0	45.19
SW-small	56.0	IN-1k : Sup. : 300	Cascade Mask R-CNN	COCO (train) : 36	839.0	45.67

model	params (m)	pretrain	finetune	gflops	IN-1k
SW-tiny	31.0	IN-1k : Sup. : 300	— : — : —	5.0	83.4/—
SW-small	56.0	IN-1k : Sup. : 300	— : — : —	9.4	83.9/—

COCO (val)

model	pretrain	head	train	gflops	mAP^b	AP^b₅₀	AP^b₇₅	mAP^b_s	mAP^b_m	mAP^b_l
SW-tiny	IN-1k : Sup. : 300	Cascade Mask R-CNN	COCO (train) : 36	751.0	52.21	—	—	—	—	—
SW-small	IN-1k : Sup. : 300	Cascade Mask R-CNN	COCO (train) : 36	839.0	52.7	—	—	—	—	—

COCO (val)

model	pretrain	head	train	gflops	mAP^m	AP^m₅₀	AP^m₇₅	mAP^m_s	mAP^m_m	mAP^m_l
SW-tiny	IN-1k : Sup. : 300	Cascade Mask R-CNN	COCO (train) : 36	751.0	45.19	—	—	—	—	—
SW-small	IN-1k : Sup. : 300	Cascade Mask R-CNN	COCO (train) : 36	839.0	45.67	—	—	—	—	—

ADE20K (val)

model	pretrain	head	train	gflops	mIoU^ms	pAcc^ms	mAcc^ms	mIoU^ss	pAcc^ss	mAcc^ss
SW-tiny	IN-1k : Sup. : 300	UPerNet	ADE20K (train) : 128 : 512	948.0	50.06	—	—	49.22	—	—
SW-small	IN-1k : Sup. : 300	UPerNet	ADE20K (train) : 128 : 512	1039.0	50.83	—	—	49.79	—	—