Semantic Segmentation on Chesapeake Bay watershed 1-m images and 30-m labels (test) benchmark leaderboard · SOTA2 Research

Semantic Segmentation on Chesapeake Bay watershed 1-m images and 30-m labels (test)

65.57Accuracy (Delaware)Paraformer

Evaluation Results

Method	Links
Paraformer2024.03		65.57	71.43	70.2	60.04	68.01	52.62	64.65
L2HNet2024.03		61.77	68.12	65.24	58.52	69.39	55.43	63.08
SkipFCN2024.03		60.97	64.83	59.44	55.37	64.72	54.66	60
DC-Swin2024.03		59.65	65.99	58.6	58.06	64.11	48.15	59.09
RF2024.03		59.35	55.03	55.26	51.07	52.29	54.36	54.56
UNetFormer2024.03		58.85	65.11	61.34	59.1	60.84	47.2	58.74
LinkNet2024.03		58.27	62.05	52.96	52.11	48.71	48.93	53.84
MobileViT2024.03		58.03	61.32	61.84	55.53	57.04	48.64	57.07
SSDA2024.03		57.91	61.54	54.85	51.71	57.71	47.15	55.15
CoAtNet2024.03		56.89	62.83	61.25	53.57	65.67	51.34	58.59
ConViT2024.03		55.26	60.71	61.58	53.94	59.8	49.11	56.73
UNet2024.03		54.16	58.79	56.42	53.21	57.34	46.11	54.34
EfficientViT2024.03		53.72	61.28	59.48	51.38	57.34	48.76	55.33
TransUNet2024.03		53.15	60.53	60.42	51.08	66.21	47.52	56.49
HRNet2024.03		52.11	56.21	50.76	50.03	57.48	45.42	52