Language-Based Image Editing with Recurrent Attentive Models
Table 2: The average IoU of two models, without attention at T=1 and with attention at T=1,4. Performance varies among datasets with different ratios of direct to relational descriptions.
['[ITALIC] T', 'Attention', 'Number of direct descriptions 4', 'Number of direct descriptions 6', 'Number of direct descriptions 8']
When there are more direct descriptions, the two models achieve similar performance. This demonstrates the framework’s capability of interpreting multiple-sentence descriptions and associating them with their source image.