Neural Image Inpainting Guided with Descriptive Text
Table 1: Quantitative comparison with state-of-the-art on CUB and COCO dataset. ↓ means lower is better, ↑ means higher is better.
['Mask', 'Model', 'ℓ1↓', 'PSNR↑', 'TV loss↓', 'SSIM↑']
On CUB and COCO dataset with the center mask, our model achieves comparable performance than these two inpainting models but does not exceed these models on two pixel-wise independence measures, which also explain our assumption because not all regions under the center mask are unique to surroundings and mentioned in the text. It is worth noting that the performance of all evaluated models decreases on object masked samples, while our model has the least performance degradation.