Heedless Backbones

HTC++

Paper | GitHub

axis

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Results

Parameters (M)

Images / Second

Publication Date

task

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Object Detection

Instance Segmentation

dataset

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COCO (val)

COCO (test)

metric

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mAP

AP₅₀

AP₇₅

mAP_s

mAP_m

mAP_l

GFLOPs

axis

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Results

Parameters (M)

Images / Second

GFLOPs

Publication Date

Filters

pretrain dataset

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JFT-3B

ImageNet-1k

ImageNet-22k

JFT-300M

pretrain method

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Supervised

FCMAE

MAE

CL

Legend

Legend attribute

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Family

Pretrain Dataset

Pretrain Method

Instance Head

Instance Training Epochs

Legend attribute (second)

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Pretrain Dataset

Pretrain Method

Instance Head

Instance Training Epochs

family	model	params (m)	pretrain	head	train	GFLOPs	mAP
Swin	Swin-B	88.0	IN-22k : Sup. : 90	HTC++	COCO (train) : 72	1043.0	56.4
Swin	Swin-L	197.0	IN-22k : Sup. : 90	HTC++	COCO (train) : 72	1470.0	57.1

COCO (test)

family	model	pretrain	train	gflops	mAP^b	AP^b₅₀	AP^b₇₅	mAP^b_s	mAP^b_m	mAP^b_l
Swin	Swin-L	IN-22k : Sup. : 90	COCO (train) : 72	1470.0	57.7	—	—	—	—	—

COCO (val)

family	model	pretrain	train	gflops	mAP^b	AP^b₅₀	AP^b₇₅	mAP^b_s	mAP^b_m	mAP^b_l
Swin	Swin-B	IN-22k : Sup. : 90	COCO (train) : 72	1043.0	56.4	—	—	—	—	—
Swin	Swin-L	IN-22k : Sup. : 90	COCO (train) : 72	1470.0	57.1	—	—	—	—	—

COCO (test)

family	model	pretrain	train	gflops	mAP^m	AP^m₅₀	AP^m₇₅	mAP^m_s	mAP^m_m	mAP^m_l
Swin	Swin-L	IN-22k : Sup. : 90	COCO (train) : 72	1470.0	50.2	—	—	—	—	—

COCO (val)

family	model	pretrain	train	gflops	mAP^m	AP^m₅₀	AP^m₇₅	mAP^m_s	mAP^m_m	mAP^m_l
Swin	Swin-B	IN-22k : Sup. : 90	COCO (train) : 72	1043.0	49.1	—	—	—	—	—
Swin	Swin-L	IN-22k : Sup. : 90	COCO (train) : 72	1470.0	49.5	—	—	—	—	—