Graph-Structured Referring Expression Reasoning in The Wild
Table 2: Comparison with state-of-the-art methods on RefCOCO, RefCOCO+ and RefCOCOg. We use * to indicate that this model uses resnet101 features. None-superscript indicates that model uses vgg16 features. The best performing method is marked in bold.
['[EMPTY]', 'RefCOCO testA', 'RefCOCO testB', 'RefCOCO+ testA', 'RefCOCO+ testB', 'RefCOCOg test']
The proposed SGMN consistently outperforms existing structured methods across all the datasets, and it improves the average accuracy over the testing sets achieved by the best performing existing structured method by 0.92%, 2.54% and 2.96% respectively on the RefCOCO, RefCOCO+ and RefCOCOg datasets. Moreover, it also surpasses all the existing models on the RefCOCOg dataset which has relatively longer complex expressions with an average length 8.43, and achieves a performance comparable to the best performing holistic method on the other two common benchmark datasets. In addition, the inference mechanism of holistic methods has poor interpretability.