Part-Stacked CNN for Fine-Grained Visual Categorization
Part-Stacked CNN for Fine-Grained Visual Categorization
In the context of fine-grained visual categorization, the ability to interpret models as human-understandable visual manuals is sometimes as important as achieving high classification accuracy. In this paper, we propose a novel Part-Stacked CNN architecture that explicitly explains the finegrained recognition process by modeling subtle differences from object parts. Based …