{"url":"/dataset/noisy-ade20k-ds","name":"noisy-ADE20K-DS","full_name":null,"description_markdown":"A new SIS benchmark designed to assess generation performance under noisy conditions, simulating human error that can occur during real-world applications. [DS] employs downsampled semantic maps that are resized by nearest-neighbor interpolation, simulating human errors e.g., jagged edges and coarse/low resolution user inputs.","description_withheld":null,"homepage":"","introduced_date":"2024-02-26","introduced_date_note":null,"introduced_by":{"paper":"/paper/stochastic-conditional-diffusion-models-for","title":"Stochastic Conditional Diffusion Models for Robust Semantic Image Synthesis","first_author":"Juyeon Ko","url":null},"license":null,"modalities":[],"tasks":[{"name":"Noisy Semantic Image Synthesis","url":"/task/noisy-semantic-image-synthesis","datasets_with_task":"/datasets/task/noisy-semantic-image-synthesis"}],"languages":[],"variants":["noisy-ADE20K-DS"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/noisy-semantic-image-synthesis-on-noisy","task":"Noisy Semantic Image Synthesis","dataset_variant":"noisy-ADE20K-DS","rows":1,"metrics":["FID","mIoU"],"first_row_in_archive_order":{"model":"SCDM","paper":"/paper/stochastic-conditional-diffusion-models-for","metrics":{"FID":"32.4","mIoU":"44.7"},"code_links":[{"title":"mlvlab/scdm","url":"https://github.com/mlvlab/scdm"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/stochastic-conditional-diffusion-models-for","title":"Stochastic Conditional Diffusion Models for Robust Semantic Image Synthesis","date":"2024-02-26","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":4,"samples_ran":1,"samples_unverified":3,"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":4,"samples_ran":1,"samples_unverified":3,"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."}