# Image Classification on ImageNet 1k (val) (VOC-style Accuracy Metrics) Source: [Image Classification on ImageNet 1k (val) (VOC-style Accuracy Metrics)]() Collection index: [llms.txt]() Data updated: 2026-02-26T05:34:34.196Z Evaluation of Image Classification performance on the ImageNet 1k validation set, focusing specifically on accuracy metrics derived from VOC evaluation standards (equal, in, voc-prior). A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. | Scope | Recorded value | | --- | --- | | Task | Image Classification | | Dataset (including any stated split) | ImageNet 1k (val) | | Metric | Accuracy (voc-prior) | | Unit | PERCENT | | Direction | Higher is better | | Results loaded | 0 of 0 | | Coverage | All results currently returned for this benchmark | Evaluation settings may differ between results. The original papers and recorded configurations are needed to establish comparability. A shared metric name alone does not establish an identical protocol. ## Metrics - [Accuracy (voc-prior)](): Higher is better; unit: PERCENT. - [Accuracy (equal)](): Higher is better; unit: PERCENT. - [Accuracy (in)](): Higher is better; unit: PERCENT. ## Recorded results | Method | Accuracy (voc-prior) | Result date | Report paper | | --- | --- | --- | --- | Page 1 of 1. This is an index page, not the full collection.