Heedless Backbones

CoCA ViT 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)

Cityscapes (val)

Cityscapes (test)

ADE20K (val)

ADE20K (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

Mask2Former

HTC++

HTC

Panoptic FPN

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

No Results

model	params (m)	pretrain	finetune	gflops	IN-1k	IN-ReaL	IN-V2	IN-A	IN-R	IN-Sketch
CoCA ViT-11M	11.4	IN-1k : Sup. : 300	— : — : —	2.2	82.7/—	87.8/—	72.9/—	34.1/—	47.8/—	35.5/—
CoCA ViT-21M	20.6	IN-1k : Sup. : 300	— : — : —	4.1	83.6/—	88.3/—	73.7/—	38.9/—	50.1/—	39.6/—
CoCA ViT-28M	27.8	IN-1k : Sup. : 300	— : — : —	4.9	84.0/—	88.4/—	74.0/—	39.8/—	51.1/—	40.2/—

COCO (val)

model	pretrain	head	train	gflops	mAP^b	AP^b₅₀	AP^b₇₅	mAP^b_s	mAP^b_m	mAP^b_l
CoCA ViT-21M	IN-1k : Sup. : 300	Cascade Mask R-CNN	COCO (train) : 36	None	51.8	70.5	56.1	—	—	—
CoCA ViT-28M	IN-1k : Sup. : 300	Cascade Mask R-CNN	COCO (train) : 36	None	52.2	71.0	56.8	—	—	—

COCO (val)

model	pretrain	head	train	gflops	mAP^m	AP^m₅₀	AP^m₇₅	mAP^m_s	mAP^m_m	mAP^m_l
CoCA ViT-21M	IN-1k : Sup. : 300	Cascade Mask R-CNN	COCO (train) : 36	None	44.9	67.8	48.2	—	—	—
CoCA ViT-28M	IN-1k : Sup. : 300	Cascade Mask R-CNN	COCO (train) : 36	None	45.2	68.9	48.8	—	—	—

ADE20K (val)

model	pretrain	head	train	gflops	mIoU^ms	pAcc^ms	mAcc^ms	mIoU^ss	pAcc^ss	mAcc^ss
CoCA ViT-21M	IN-1k : Sup. : 300	UPerNet	ADE20K (train) : 128 : 512	None	50.8	—	—	—	—	—
CoCA ViT-28M	IN-1k : Sup. : 300	UPerNet	ADE20K (train) : 128 : 512	None	51.3	—	—	—	—	—