Semantic Segmentation on Cityscapes test

Metric: Mean IoU (class) (higher is better)

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#	Model↕	Mean IoU (class)▼	Extra Data	Paper	Date↕	Code
1	VLTSeg	86.4	No	Strong but simple: A Baseline for Domain General...	2023-12-04	Code
2	MetaPrompt-SD	86.2	No	Harnessing Diffusion Models for Visual Perceptio...	2023-12-22	Code
3	SERNet-Former	84.83	No	SERNet-Former: Semantic Segmentation by Efficien...	2024-01-28	Code
4	RPCNet	81.8	No	Joint Semantic Segmentation and Boundary Detecti...	2020-04-16	-
5	SaGe	76.9	No	Semantic-Aware Generation for Self-Supervised Vi...	2021-11-25	Code
6	LDFNet	71.3	No	Incorporating Luminance, Depth and Color Informa...	2018-09-24	Code
7	EDANet	67.3	No	Efficient Dense Modules of Asymmetric Convolutio...	2018-09-17	Code

#1VLTSegSOTA
86.4
Mean IoU (class)· 2023-12-04
Strong but simple: A Baseline for Domain Generalized Dense Perception by CLIP-based Transfer Learning Code
#2MetaPrompt-SD
86.2
Mean IoU (class)· 2023-12-22
Harnessing Diffusion Models for Visual Perception with Meta Prompts Code
#3SERNet-Former
84.83
Mean IoU (class)· 2024-01-28
SERNet-Former: Semantic Segmentation by Efficient Residual Network with Attention-Boosting Gates and Attention-Fusion Networks Code
#4RPCNetSOTA
81.8
Mean IoU (class)· 2020-04-16
Joint Semantic Segmentation and Boundary Detection using Iterative Pyramid Contexts
#5SaGe
76.9
Mean IoU (class)· 2021-11-25
Semantic-Aware Generation for Self-Supervised Visual Representation Learning Code
#6LDFNetSOTA
71.3
Mean IoU (class)· 2018-09-24
Incorporating Luminance, Depth and Color Information by a Fusion-based Network for Semantic Segmentation Code
#7EDANetSOTA
67.3
Mean IoU (class)· 2018-09-17
Efficient Dense Modules of Asymmetric Convolution for Real-Time Semantic Segmentation Code