{"url":"/dataset/sun360","name":"SUN360","full_name":"Scene UNderstanding 360° panorama","description_markdown":"The goal of the **SUN360** panorama database is to provide academic researchers in computer vision, computer graphics and computational photography, cognition and neuroscience, human perception, machine learning and data mining, with a comprehensive collection of annotated panoramas covering 360x180-degree full view for a large variety of environmental scenes, places and the objects within. To build the core of the dataset, the authors download a huge number of high-resolution panorama images from the Internet, and group them into different place categories. Then, they designed a WebGL annotation tool for annotating the polygons and cuboids for objects in the scene.\r\n\r\nSource: [Scene UNderstanding 360° panorama](https://vision.cs.princeton.edu/projects/2012/SUN360/data/)\r\nImage Source: [http://3dvision.princeton.edu/projects/2012/SUN360/](http://3dvision.princeton.edu/projects/2012/SUN360/)","description_withheld":null,"homepage":"http://3dvision.princeton.edu/projects/2012/SUN360/","introduced_date":"2012-01-01","introduced_date_note":null,"introduced_by":{"paper":null,"title":"Recognizing scene viewpoint using panoramic place representation","first_author":null,"url":"https://doi.org/10.1109/CVPR.2012.6247991"},"license":{"name":"Custom (research-only)","url":"http://3dvision.princeton.edu/projects/2012/SUN360/"},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Outdoor Light Source Estimation","url":"/task/light-source-estimation","datasets_with_task":"/datasets/task/light-source-estimation"}],"languages":[],"variants":["SUN360"],"data_loaders":[],"num_papers_in_archive":93,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/light-source-estimation-on-sun360","task":"Outdoor Light Source Estimation","dataset_variant":"SUN360","rows":1,"metrics":["Median Relighting Error"],"first_row_in_archive_order":{"model":"ÇuNNy","paper":"/paper/deep-outdoor-illumination-estimation","metrics":{"Median Relighting Error":"1.25"},"code_links":[{"title":"CyxFTS/Scenne-illumination-estimation-from-single-image","url":"https://github.com/CyxFTS/Scenne-illumination-estimation-from-single-image"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/deep-outdoor-illumination-estimation","title":"Deep Outdoor Illumination Estimation","date":"2016-11-19","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":12,"samples_ran":2,"samples_unverified":10,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":1,"samples_harvested":12,"samples_ran":2,"samples_unverified":10,"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."}