Image Question Answering on DAQUAR REDUCED (test) benchmark leaderboard · SOTA2 Research

Image Question Answering on DAQUAR REDUCED (test)

60.3AccuracyHuman

Evaluation Results

Method	Links
Human2015.11		60.3	61	79
Human Baseline2016.03		60.27	61.04	78.96
SAN(2, LSTM)2015.11		46.2	51.2	85.1
A+C+Selected-K-LSTM2016.03		46.13	51.83	83.95
Att+Cap+Know-LSTM2016.03		45.79	51.53	83.91
SAN(2, CNN)2015.11		45.5	50.2	83.6
Yang et al.2016.03		45.5	50.2	83.6
SAN(1, LSTM)2015.11		45.2	49.6	84
SAN(1, CNN)2015.11		45.2	49.6	83.7
Att+Cap-LSTM2016.03		44.78	50.07	83.85
Noh et al.2016.03		44.48	49.56	83.95
Att+Know-LSTM2016.03		41.08	46.04	82.39
Cap+Know-LSTM2016.03		40.81	45.04	82.01
Xu et al.2016.03		40.07	—	—
Att-LSTM2016.03		40.07	45.43	82.67
IMG-CNN2015.11		39.7	44.9	83.1
Ma et al.2016.03		39.66	44.86	83.06
VggNet+ft-LSTM2016.03		39.13	44.03	83.33
VggNet-LSTM2016.03		38.72	43.97	83.01
2-VIS+BLSTM2015.11		35.8	46.8	82.2
2-VIS+BLSTM2016.03		35.78	46.83	82.15
Language + IMG2015.11		34.7	40.8	79.5
Askneuron2016.03		34.68	40.76	79.54
VIS+LSTM2016.03		34.41	46.05	82.23
VIS+LSTM2015.11		34.4	46.1	82.2
IMG+BOW2015.11		34.2	45	81.5
VIS+BOW2016.03		34.17	44.99	81.48
BOW2015.11		32.7	43.2	81.3
LSTM2015.11		32.7	43.5	81.6
Language2015.11		31.7	38.4	80.1
GUESS2016.03		18.24	29.65	77.59
GUESS2015.11		18.2	29.7	77.6
Multi-World2015.11		12.7	18.2	51.5