Semantic Segmentation on NYU v2 (Detailed Class Metrics) benchmark leaderboard · SOTA2 Research

Semantic Segmentation on NYU v2 (Detailed Class Metrics)

83.26Wall AccuracyHN pre-training

Evaluation Results

Method	Links
HN pre-training2020.02		83.26	90.63	58.81	58.4	38.79	37.05	14.24	26.16	18.24	52.92
ImageNet pre-train2020.02		81.54	86.1	58.86	37.76	35.05	38.25	4.35	25.4	17.34	50.58
No pre-training2020.02		77.57	74.91	42.36	13.25	6.58	22.42	3.17	13.73	8.78	38.74
CIFAR100 pre-train2020.02		66.33	66.96	19.84	0.03	0.01	0.05	0	10.7	6.23	31.9
HN pre-training2020.02		32	77.64	87.45	60.15	55.67	60.51	53.69	56.04	33.49	62.98
ImageNet pre-train2020.02		28.85	74.69	87.98	64.4	56.22	59.1	50.78	57.84	34.27	61.7
No pre-training2020.02		18.7	66.72	60.78	22.3	20.7	15.24	12.49	24.77	6.73	31.41