Heedless Backbones

FLatten-CSwin 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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ImageNet-1k

ImageNet-A

ImageNet-R

ImageNet-Sketch

ImageNet-C

ImageNet-C-bar

ImageNet-V2

ImageNet-ReaL

PASCAL VOC 2007 (val)

PASCAL VOC 2007 (test)

metric

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Top-1

Top-5

GFLOPs

resolution

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224x224

384x384

512x512

axis

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Results

Parameters (M)

Images / Second

GFLOPs

Publication Date

Filters

Legend

Legend attribute

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Family

Pretrain Dataset

Classification Resolution

Legend attribute (second)

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Family

Pretrain Method

Classification Resolution

model	params (m)	pretrain	finetune	GFLOPs	Top-1
FLatten-CSwin-T	21.0	IN-1k : Sup. : 300	— : — : —	4.3	83.1
FLatten-CSwin-S	35.0	IN-1k : Sup. : 300	— : — : —	6.9	83.8
FLatten-CSwin-B	75.0	IN-1k : Sup. : 300	— : — : —	15.0	84.5
FLatten-CSwin-B	75.0	IN-1k : Sup. : 300	IN-1k : 30 : 384	46.4	85.5

model	params (m)	pretrain	finetune	gflops	IN-1k
FLatten-CSwin-T	21.0	IN-1k : Sup. : 300	— : — : —	4.3	83.1/96.376
FLatten-CSwin-S	35.0	IN-1k : Sup. : 300	— : — : —	6.9	83.8/—
FLatten-CSwin-B	75.0	IN-1k : Sup. : 300	— : — : —	15.0	84.5/—
FLatten-CSwin-B	75.0	IN-1k : Sup. : 300	IN-1k : 30 : 384	46.4	85.5/—