{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/a-large-scale-film-style-dataset-for-learning","title":"A Large-scale Film Style Dataset for Learning Multi-frequency Driven Film Enhancement","arxiv_id":"2301.08880","date":"2023-01-21","proceeding":null,"authors":["Zinuo Li","Xuhang Chen","Shuqiang Wang","Chi-Man Pun"],"abstract":"Film, a classic image style, is culturally significant to the whole photographic industry since it marks the birth of photography. However, film photography is time-consuming and expensive, necessitating a more efficient method for collecting film-style photographs. Numerous datasets that have emerged in the field of image enhancement so far are not film-specific. In order to facilitate film-based image stylization research, we construct FilmSet, a large-scale and high-quality film style dataset. Our dataset includes three different film types and more than 5000 in-the-wild high resolution images. Inspired by the features of FilmSet images, we propose a novel framework called FilmNet based on Laplacian Pyramid for stylizing images across frequency bands and achieving film style outcomes. Experiments reveal that the performance of our model is superior than state-of-the-art techniques. The link of code and data is \\url{https://github.com/CXH-Research/FilmNet}.","url_abs":"https://arxiv.org/abs/2301.08880v3","url_pdf":"https://arxiv.org/pdf/2301.08880v3.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"a-large-scale-film-style-dataset-for-learning","repo_url":"https://github.com/CXH-Research/FilmNet","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"film-simulation","task_name":"Film Simulation"},{"task_slug":"image-enhancement","task_name":"Image Enhancement"},{"task_slug":"image-stylization","task_name":"Image Stylization"}],"methods":[],"datasets_introduced":[{"slug":"filmset","name":"FilmSet","full_name":""}],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2301.08880","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2301.08880"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"deterministic:regex_extraction","url":"https://github.com/CXH-Research/FilmNet","reach":null}],"summary":{"ran":5,"ran_draft_wrong":1,"ran_honours":1,"unverified":4},"by_repo_kind":{"official":{"samples":11,"ran":7,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":0,"samples":[{"code_sha256_prefix":"76fad11374ea4b1a","entry":"Classifier","repo":"CXH-Research/FilmNet","repo_kind":"official","path":"models/filmnet.py","file_url":"https://github.com/CXH-Research/FilmNet/blob/HEAD/models/filmnet.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"76fad11374ea4b1a"}},{"code_sha256_prefix":"a22934d1d407edcd","entry":"LFNet","repo":"CXH-Research/FilmNet","repo_kind":"official","path":"models/filmnet.py","file_url":"https://github.com/CXH-Research/FilmNet/blob/HEAD/models/filmnet.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"a22934d1d407edcd"}},{"code_sha256_prefix":"f6c76a285c482463","entry":"LUT3D","repo":"CXH-Research/FilmNet","repo_kind":"official","path":"models/filmnet.py","file_url":"https://github.com/CXH-Research/FilmNet/blob/HEAD/models/filmnet.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"f6c76a285c482463"}},{"code_sha256_prefix":"26dfac8684139704","entry":"NSRBlock","repo":"CXH-Research/FilmNet","repo_kind":"official","path":"models/filmnet.py","file_url":"https://github.com/CXH-Research/FilmNet/blob/HEAD/models/filmnet.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"26dfac8684139704"}},{"code_sha256_prefix":"6668c8f3b3a04df0","entry":"discriminator_block","repo":"CXH-Research/FilmNet","repo_kind":"official","path":"models/filmnet.py","file_url":"https://github.com/CXH-Research/FilmNet/blob/HEAD/models/filmnet.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"6668c8f3b3a04df0"}},{"code_sha256_prefix":"650511897d732139","entry":"gauss_kernel","repo":"CXH-Research/FilmNet","repo_kind":"official","path":"models/filmnet.py","file_url":"https://github.com/CXH-Research/FilmNet/blob/HEAD/models/filmnet.py","link_basis":"first_harvest_node","language":"python","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"650511897d732139"}},{"code_sha256_prefix":"03758e3b7e0b48e6","entry":"trilinear","repo":"CXH-Research/FilmNet","repo_kind":"official","path":"models/filmnet.py","file_url":"https://github.com/CXH-Research/FilmNet/blob/HEAD/models/filmnet.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"03758e3b7e0b48e6"}},{"code_sha256_prefix":"8f596f83960db595","entry":"FilmNet","repo":"CXH-Research/FilmNet","repo_kind":"official","path":"models/filmnet.py","file_url":"https://github.com/CXH-Research/FilmNet/blob/HEAD/models/filmnet.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"8f596f83960db595"}},{"code_sha256_prefix":"f691bdf303105b72","entry":"LapPyramidConv","repo":"CXH-Research/FilmNet","repo_kind":"official","path":"models/filmnet.py","file_url":"https://github.com/CXH-Research/FilmNet/blob/HEAD/models/filmnet.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"f691bdf303105b72"}},{"code_sha256_prefix":"f35c3d60f00bf72b","entry":"TTR","repo":"CXH-Research/FilmNet","repo_kind":"official","path":"models/filmnet.py","file_url":"https://github.com/CXH-Research/FilmNet/blob/HEAD/models/filmnet.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"f35c3d60f00bf72b"}},{"code_sha256_prefix":"baea583855ccfbb0","entry":"TransHigh","repo":"CXH-Research/FilmNet","repo_kind":"official","path":"models/filmnet.py","file_url":"https://github.com/CXH-Research/FilmNet/blob/HEAD/models/filmnet.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"baea583855ccfbb0"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}