ImageNet ReaL (often written ImageNet-ReaL) is the set of cleaned-up/reassessed labels for the ImageNet ILSVRC2012 validation split produced by Beyer et al. (2020) to provide a more reliable evaluation benchmark. The authors collected new human annotations for the original 50,000 validation images (the ILSVRC2012 val split), allowed discovery of valid multi-labels and corrected many original labeling errors, and released the reassessed labels and supporting files (e.g. real.json) in the google-research/reassessed-imagenet repository. The reassessed labels are intended to be used in place of (or alongside) the original ImageNet validation labels when reporting model accuracy; evaluations are commonly reported on the validation split.
No results indexed yet — be the first to submit a score.
Submit a checkpoint and a reproduction script. We will run it, publish the score, and — if it takes the top — annotate the step on the progress chart with your name.