Tag-sensitive Features for Large-scale Scene Classification
نویسنده
چکیده
Scene classification is a fundamental research problem in computer vision. However, performances of state-of-theart systems are still far from acceptable. This motivates the search for improved descriptors and features to represent the scene. Multimodal learning approaches provide a way of building meaningful dictionaries that can take into account not only the visual structure, but also the tags associated to example scenes. In this work, we experiment with a ‘Yshaped network’, and get encouraging preliminary results, comparable to very complex hand-crafted descriptors. Future work will explore promising new architectures, taking into account the full content of images.
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