Heedless Backbones

Slimmable ConvNeXt 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

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Results

Parameters (M)

Images / Second

GFLOPs

Publication Date

Filters

Legend

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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
Slimmable ConvNeXt-T	28.6	IN-1k : Sup. : 600	— : — : —	4.5	80.8
Slimmable ConvNeXt-S	50.2	IN-1k : Sup. : 600	— : — : —	8.7	82.2
Slimmable ConvNeXt-B	88.6	IN-1k : Sup. : 600	— : — : —	15.35	82.8

model	params (m)	pretrain	finetune	gflops	IN-1k
Slimmable ConvNeXt-T	28.6	IN-1k : Sup. : 600	— : — : —	4.5	80.8/—
Slimmable ConvNeXt-S	50.2	IN-1k : Sup. : 600	— : — : —	8.7	82.2/—
Slimmable ConvNeXt-B	88.6	IN-1k : Sup. : 600	— : — : —	15.35	82.8/—