FGVC-Aircraft

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FGVC-Aircraft contains 10,200 images of aircraft, with 100 images for each of 102 different aircraft model variants, most of which are airplanes. The (main) aircraft in each image is annotated with a tight bounding box and a hierarchical airplane model label. Aircraft models are organized in a four-levels hierarchy. The four levels, from finer to coarser, are: * Model, e.g. Boeing 737-76J. Since certain models are nearly visually indistinguishable, this level is not used in the evaluation. * Variant, e.g. Boeing 737-700. A variant collapses all the models that are visually indistinguishable into one class. The dataset comprises 102 different variants. * Family, e.g. Boeing 737. The dataset comprises 70 different families. * Manufacturer, e.g. Boeing. The dataset comprises 41 different manufacturers. The data is divided into three equally-sized training, validation and test subsets. Source: https://www.robots.ox.ac.uk/~vgg/data/fgvc-aircraft/ Image Source: Fine-Grained Visual Classification of Aircraft

Images

벤치마크

Fine-Grained Image Classification on FGVC Aircraft 결과 114개

Prompt Engineering on FGVC-Aircraft 결과 14개

Few-Shot Learning on FGVC Aircraft 결과 8개

Neural Architecture Search on FGVC Aircraft 결과 8개

Mitigating Contextual Bias on FGVC Aircraft 결과 4개

Fine-Grained Image Classification on FGVC-Aircraft 결과 2개

Zero-Shot Learning on FGVC-Aircraft 결과 2개

Fine-Grained Visual Recognition on FGVC-Aircraft 결과 1개

Image Classification on FGVC Aircraft 결과 1개

Image Classification on FGVC-Aircraft 결과 1개

Image Clustering on FGVC Aircraft 결과 1개

Transductive Zero-Shot Classification on FGVC-Aircraft 결과 1개