Dynamic MLP for Fine-Grained Image Classification by Leveraging Geographical and Temporal Information

Fine-grained image classification is a challenging computer vision task where various species share similar visual appearances, resulting in misclassification if merely based on visual clues. Therefore, it is helpful to lever- age additional information, e.g., the locations and dates for data shooting, which can be easily accessible but rarely exploited.