面向水下场景的轻量级图像语义分割网络

郭浩然,郭继昌,汪昱东

Lightweight semantic segmentation network for underwater image

Hao-ran GUO,Ji-chang GUO,Yu-dong WANG

表 3 各网络在SUIM数据集上的精度指标对比结果

Tab.3 Comparison results of accuracy index on SUIM dataset in each network

语义分割模型 IoU/% mIoU/% PA/% BW HD PF WR RO RI FV SR 本文方法 84.62 63.99 18.46 41.84 61.93 53.44 46.00 58.42 53.55 85.32 U-Net[3] 79.46 32.25 21.85 33.94 23.65 50.28 38.16 42.16 39.85 79.44 SegNet[2] 80.63 45.67 17.45 32.24 55.72 47.62 43.92 51.51 46.85 82.19 Deeplab[4] 81.82 50.26 17.05 43.33 63.60 57.18 43.59 55.35 51.52 84.27 PSPNet[7] 82.51 65.04 28.54 46.56 62.88 55.80 46.78 55.98 55.51 86.41 GCN[24] 79.32 38.57 15.09 30.38 54.25 49.94 36.09 52.02 44.46 81.28 OCNet[15] 83.14 64.03 24.31 43.11 61.78 54.92 47.41 54.97 54.30 85.89 SUIMNet[13] 80.64 63.45 23.27 41.25 60.89 53.12 46.02 57.12 53.22 85.22 LEDNet[19] 82.96 58.47 18.02 42.86 50.96 58.13 46.13 54.99 51.36 84.25 BiseNetv2[21] 83.67 59.29 18.27 39.58 56.54 58.16 47.33 56.93 52.47 84.96 ENet[14] 80.94 50.60 16.97 36.71 51.73 49.24 41.99 50.46 47.33 82.31 ERFNet[16] 83.02 52.95 17.50 41.72 49.80 53.70 45.98 54.30 50.40 83.75 CGNet[17] 81.21 60.04 17.71 42.91 53.62 57.62 46.46 53.71 51.66 83.99