Table 4 Performance comparison of the proposed method on MSCOCO dataset. (-) indicates ‘metric is not reported’. The best two models having larger values of the metrics are shown in red and green
Method | B@1 | B@2 | B@3 | B@4 | MT | R | CD |
|---|---|---|---|---|---|---|---|
Deep VS [25] | 62.5 | 45.0 | 32.1 | 23.0 | 19.5 | - | 66.0 |
emb-gLSTM [5] | 67.0 | 49.1 | 35.8 | 26.4 | 22.74 | - | 81.25 |
Soft attn [17] | 70.7 | 49.2 | 34.4 | 24.3 | 23.9 | - | - |
Hard attn [17] | 71.8 | 50.4 | 35.7 | 25.0 | 23.04 | - | - |
ATT [55] | 70.9 | 53.7 | 40.2 | 30.4 | 24.3 | - | - |
SCA-CNN [14] | 71.9 | 54.8 | 41.1 | 31.1 | 25.0 | - | - |
LSTM-A [56] | 75.4 | – | – | 35.2 | 26.9 | 55.8 | 108.8 |
Up-down [7] | 77.2 | – | – | 36.2 | 27.0 | 56.4 | 113.5 |
SCST [42] | – | – | – | 34.2 | 26.7 | 55.7 | 114.0 |
RFNet [20] | 76.4 | 60.4 | 46.6 | 35.8 | 27.4 | 56.5 | 112.5 |
GCN-LSTM [57] | 77.4 | – | – | 37.1 | 28.1 | 57.2 | 117.1 |
avtmNet [58] | – | – | – | 33.2 | 27.3 | 56.7 | 112.6 |
ERNN [59] | 73.2 | 56.9 | 42.9 | 32.2 | 25.2 | - | 101.4 |
Tri-LSTM [62] | – | – | – | 37.3 | 28.4 | 58.1 | 123.5 |
TDA+GLD [61] | 78.8 | 62.6 | 48.0 | 36.1 | 27.8 | 57.1 | 121.1 |
Ours | 78.5 | 62.0 | 49.1 | 38.2 | 28.9 | 58.3 | 124.2 |