{"url":"/dataset/layoutbench","name":"LayoutBench","full_name":null,"description_markdown":"LayoutBench is a diagnostic benchmark that examines 4 spatial control skills (number, position, size, shape), where each skill consists of 2 OOD layout splits, i.e., in total 8 tasks = 4 skills x 2 splits. To disentangle spatial control from other aspects of image generation, such as generating diverse objects, LayoutBench keeps the object configurations of CLEVR, and changes the spatial layouts.","description_withheld":null,"homepage":"https://layoutbench.github.io/","introduced_date":"2023-04-13","introduced_date_note":null,"introduced_by":{"paper":"/paper/diagnostic-benchmark-and-iterative-inpainting","title":"Diagnostic Benchmark and Iterative Inpainting for Layout-Guided Image Generation","first_author":"Jaemin Cho","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Layout-to-Image Generation","url":"/task/layout-to-image-generation","datasets_with_task":"/datasets/task/layout-to-image-generation"}],"languages":[],"variants":["LayoutBench"],"data_loaders":[],"num_papers_in_archive":3,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/layout-to-image-generation-on-layoutbench","task":"Layout-to-Image Generation","dataset_variant":"LayoutBench","rows":3,"metrics":["AP"],"first_row_in_archive_order":{"model":"IterInpaint","paper":"/paper/diagnostic-benchmark-and-iterative-inpainting","metrics":{"AP":"36.5"},"code_links":[{"title":"j-min/IterInpaint","url":"https://github.com/j-min/IterInpaint"},{"title":"j-min/LayoutBench-COCO","url":"https://github.com/j-min/LayoutBench-COCO"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/diagnostic-benchmark-and-iterative-inpainting","title":"Diagnostic Benchmark and Iterative Inpainting for Layout-Guided Image Generation","date":"2023-04-13","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/reco-region-controlled-text-to-image","title":"ReCo: Region-Controlled Text-to-Image Generation","date":"2022-11-23","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/high-resolution-image-synthesis-with-latent","title":"High-Resolution Image Synthesis with Latent Diffusion Models","date":"2021-12-20","rows_on_this_dataset":1,"code_links":41,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":28,"samples_ran":19,"samples_unverified":9,"pointer_only_for_licence":5,"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":28,"samples_ran":19,"samples_unverified":9,"pointer_only_for_licence":5,"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."}