Deep Multimodal Neural Architecture Search
Table 4. Accuracies (with IoU>0.5) on RefCOCO, RefCOCO+ and RefCOCOg to compare with the state-of-the-art methods. All methods use detected objects to extract visual features.
['Method', 'Size', 'Object Detector Dataset', 'Object Detector Model', 'Object Detector Backbone', 'RefCOCO TestA', 'RefCOCO TestB', 'RefCOCO Val', 'RefCOCO+ TestA', 'RefCOCO+ TestB', 'RefCOCO+ Val', 'RefCOCOg Test', 'RefCOCOg Val']
Be equipped with the powerful visual features (i.e., FRCN pre-trained on Visual Genome), MMnasNet (1×) obtains remarkable improvement and delivers the new state-of-the-art performance across all datasets.