ImageNet Detection (commonly called ILSVRC DET) is the object detection track of the ImageNet Large Scale Visual Recognition Challenge (ILSVRC). It provides bounding-box annotations for images across 200 object categories and was used as a large-scale benchmark for object detection in ILSVRC competitions (2012–2017). Models are evaluated with detection metrics (mean Average Precision, commonly reported at IoU = 0.5 / mAP@0.5, following the ILSVRC evaluation protocol). The dataset and challenge are described in the ILSVRC overview paper (Russakovsky et al., 2014) and on the ImageNet challenge website, which hosts the list of 200 detection synsets, development kits and per-year results.
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