{"url":"/dataset/pascal-voc-2011","name":"PASCAL VOC 2011","full_name":"PASCAL VOC 2011","description_markdown":"**PASCAL VOC 2011** is an image segmentation dataset. It contains around 2,223 images for training, consisting of 5,034 objects. Testing consists of 1,111 images with 2,028 objects. In total there are over 5,000 precisely segmented objects for training.\r\n\r\nSource: [Scene Parsing with Integration of Parametric and Non-parametric Models](https://arxiv.org/abs/1604.05848)\r\nImage Source: [http://host.robots.ox.ac.uk:8080/pascal/VOC/voc2011/index.html](http://host.robots.ox.ac.uk:8080/pascal/VOC/voc2011/index.html)","description_withheld":null,"homepage":"http://host.robots.ox.ac.uk:8080/pascal/VOC/voc2011/index.html","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":null,"title":"The PASCAL Visual Object Classes Challenge 2011 (VOC2011) Results","first_author":null,"url":"http://www.pascal-network.org/challenges/VOC/voc2011/workshop/index.html"},"license":{"name":"Custom","url":"http://host.robots.ox.ac.uk:8080/pascal/VOC/voc2011/index.html"},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Semantic Segmentation","url":"/task/semantic-segmentation","datasets_with_task":"/datasets/task/semantic-segmentation"}],"languages":[],"variants":["PASCAL VOC 2011 test","PASCAL VOC 2011"],"data_loaders":[{"repo":"https://github.com/open-mmlab/mmdetection","url":"https://github.com/open-mmlab/mmdetection/blob/master/docs/1_exist_data_model.md","frameworks":["pytorch"]},{"repo":"https://github.com/rusty1s/pytorch_geometric","url":"https://pytorch-geometric.readthedocs.io/en/latest/modules/datasets.html","frameworks":["pytorch"]},{"repo":"https://github.com/open-mmlab/mmsegmentation","url":"https://github.com/open-mmlab/mmsegmentation/blob/master/docs/dataset_prepare.md","frameworks":["pytorch"]}],"num_papers_in_archive":20,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/semantic-segmentation-on-pascal-voc-2011-test","task":"Semantic Segmentation","dataset_variant":"PASCAL VOC 2011 test","rows":3,"metrics":["Mean IoU"],"first_row_in_archive_order":{"model":"Plugin network","paper":"/paper/plugin-networks-for-inference-under-partial","metrics":{"Mean IoU":"72.2"},"code_links":[{"title":"tooploox/plugin-networks","url":"https://github.com/tooploox/plugin-networks"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/semantic-segmentation-on-pascal-voc-2011","task":"Semantic Segmentation","dataset_variant":"PASCAL VOC 2011","rows":1,"metrics":["Mean IoU"],"first_row_in_archive_order":{"model":"DLDL-8s+CRF","paper":"/paper/deep-label-distribution-learning-with-label","metrics":{"Mean IoU":"67.6"},"code_links":[{"title":"gaobb/DLDL","url":"https://github.com/gaobb/DLDL"},{"title":"paplhjak/facial-age-estimation-benchmark","url":"https://github.com/paplhjak/facial-age-estimation-benchmark"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/plugin-networks-for-inference-under-partial","title":"Plugin Networks for Inference under Partial Evidence","date":"2019-01-02","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/deep-label-distribution-learning-with-label","title":"Deep Label Distribution Learning with Label Ambiguity","date":"2016-11-06","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/fully-convolutional-networks-for-semantic","title":"Fully Convolutional Networks for Semantic Segmentation","date":"2016-05-20","rows_on_this_dataset":2,"code_links":37,"syntology":null}],"syntology_totals":{"read_at":"2026-09-25T09:33:49+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}