Semantic Segmentation on SELMA

Metric: mIoU (higher is better)

LeaderboardDataset

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#	Model↕	mIoU▼	Extra Data	Paper	Date↕	Code
1	CMX	91.7	No	CMX: Cross-Modal Fusion for RGB-X Semantic Segme...	2022-03-09	Code
2	SegFormer	77.2	No	SegFormer: Simple and Efficient Design for Seman...	2021-05-31	Code
3	DeepLabV3	70.7	No	Rethinking Atrous Convolution for Semantic Image...	2017-06-17	Code
4	DeepLabV2	68.9	No	DeepLab: Semantic Image Segmentation with Deep C...	2016-06-02	Code
5	PSPNet	68.4	No	Pyramid Scene Parsing Network	2016-12-04	Code
6	FCN	68.2	No	Fully Convolutional Networks for Semantic Segmen...	2014-11-14	Code
7	UNet	36.2	No	U-Net: Convolutional Networks for Biomedical Ima...	2015-05-18	Code

#1CMXSOTA
91.7
mIoU· 2022-03-09
CMX: Cross-Modal Fusion for RGB-X Semantic Segmentation with Transformers Code
#2SegFormerSOTA
77.2
mIoU· 2021-05-31
SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers Code
#3DeepLabV3SOTA
70.7
mIoU· 2017-06-17
Rethinking Atrous Convolution for Semantic Image Segmentation Code
#4DeepLabV2SOTA
68.9
mIoU· 2016-06-02
DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs Code
#5PSPNet
68.4
mIoU· 2016-12-04
Pyramid Scene Parsing Network Code
#6FCNSOTA
68.2
mIoU· 2014-11-14
Fully Convolutional Networks for Semantic Segmentation Code
#7UNet
36.2
mIoU· 2015-05-18
U-Net: Convolutional Networks for Biomedical Image Segmentation Code