{"url":"/dataset/autoposter-dataset","name":"AutoPoster dataset","full_name":null,"description_markdown":"Dataset proposed by ACM MM 2023 paper \"AutoPoster: A Highly Automatic and Content-aware Design System for Advertising Poster Generation\"\r\n\r\nWe gather 76537 advertising posters from an e-commerce advertising platform. The posters are designed manually and cover a broad range of product categories, resulting in a diverse set of layouts, taglines, and visual styles.","description_withheld":null,"homepage":"https://tianchi.aliyun.com/dataset/159829","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":{"name":"CC BY-SA 4.0","url":null},"modalities":[],"tasks":[],"languages":[],"variants":["AutoPoster dataset"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+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."}