Research Article
Weakly Supervised Deep Semantic Segmentation Using CNN and ELM with Semantic Candidate Regions
Table 3
Results on PASCAL VOC 2012 (mIoU in %) for weakly-supervised semantic segmentation with only per-image labels.
| PASCAL | background | aeroplane | bicycle | bird | boat | bottle | bus | car | cat | chair | cow | Dining table | dog | horse | motorbike | person | Potted plant | sheep | sofa | train | tv/montir | average | VOC 2012 |
| CCNN [20] | 69 | 26 | 18 | 25 | 20 | 36 | 47 | 47 | 48 | 16 | 38 | 21 | 44 | 35 | 46 | 41 | 30 | 36 | 22 | 39 | 37 | 35.3 | MIL+ILP+SP-sppxly [21] | 77 | 37 | 18 | 25 | 28 | 32 | 42 | 48 | 51 | 13 | 46 | 15 | 51 | 44 | 39 | 38 | 28 | 44 | 20 | 38 | 35 | 36.6 | STC [19] | 82 | 63 | 26 | 62 | 28 | 38 | 67 | 63 | 75 | 22 | 53 | 28 | 66 | 58 | 62 | 53 | 33 | 63 | 32 | 45 | 45 | 50.7 | AE [22] | 78 | 72 | 29 | 64 | 40 | 58 | 58 | 54 | 63 | 10 | 61 | 36 | 62 | 56 | 63 | 43 | 37 | 65 | 32 | 50 | 39 | 50.9 | Ours | 84 | 68 | 26 | 58 | 47 | 41 | 57 | 67 | 74 | 23 | 73 | 26 | 53 | 57 | 74 | 38 | 43 | 63 | 37 | 40 | 48 | 52.2 |
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