Relationship-Embedded Representation Learning for Grounding Referring Expressions
TABLE VII: Comparison with the state-of-the-art methods on RefCOCO, RefCOCO+ and RefCOCOg when using detected proposals. The best performing method is marked in bold.
['[EMPTY]', 'RefCOCO testA', 'RefCOCO testB', 'RefCOCO+ testA', 'RefCOCO+ testB', 'RefCOCOg test']
We have also evaluated the performance of the proposed CMRIN for grounding referring expressions using automatically detected objects in the three datasets. The proposed CMRIN outperforms existing state-of-the-art models, which demonstrates the robustness of CMRIN with respect to object detection results. Specifically, CMRIN improves the average precision in the person category achieved with the existing best-performing method by 3.80%, and it improves the Precision@1 on RefCOCO+’s test A and test B by 5.50% and 1.27%, respectively.