{"url":"/dataset/chinese-traditional-painting-dataset","name":"Chinese Traditional Painting dataset","full_name":null,"description_markdown":"The **Chinese Traditional Painting dataset** for style transfer contains 1000 content images and 100 style images.\nThe content images are mostly the photorealistic scenes of mountain, lake, river, bridge, and buildings in regions south of the Yangtze River. It includes not only the scenes of China, but also beautiful pictures of Rhine, Alps, Yellow Stone, Grand Canyon, etc. The content images include diverse types of Chinese traditional paintings.\n\nSource: [https://github.com/lbsswu/Chinese_style_transfer](https://github.com/lbsswu/Chinese_style_transfer)\nImage Source: [https://github.com/lbsswu/Chinese_style_transfer](https://github.com/lbsswu/Chinese_style_transfer)","description_withheld":null,"homepage":"https://github.com/lbsswu/Chinese_style_transfer","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/neural-abstract-style-transfer-for-chinese","title":"Neural Abstract Style Transfer for Chinese Traditional Painting","first_author":"Bo Li","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Style Transfer","url":"/task/style-transfer","datasets_with_task":"/datasets/task/style-transfer"}],"languages":[{"name":"Chinese","url":"/datasets/language/chinese"}],"variants":["Chinese Traditional Painting dataset"],"data_loaders":[{"repo":"https://github.com/lbsswu/Chinese_style_transfer","url":"https://github.com/lbsswu/Chinese_style_transfer","frameworks":[]}],"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."}