Zero-Shot Grounding of Objects from Natural Language Queries
Table 3: Category-wise performance with the default split of Flickr30k Entities.
['Method', 'Overall', 'people', 'clothing', 'bodyparts', 'animals', 'vehicles', 'instruments', 'scene', 'other']
For Flickr30k we also note entity-wise accuracy in Table 3 and compare against [7, 34]. [CONTINUE] As these models use object detectors pretrained on Pascal-VOC , they have somewhat higher performance on classes that are common to both Flickr30k and Pascal-VOC ("animals", "people" and "vehicles"). However, on the classes like "clothing" and "bodyparts" our model ZSGNet shows much better performance; likely because both "clothing" and "bodyparts" are present along with "people" category and so the other methods choose the "people" category.