{"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/image-composition-assessment-with-saliency","title":"Image Composition Assessment with Saliency-augmented Multi-pattern Pooling","arxiv_id":"2104.03133","date":"2021-04-07","proceeding":null,"authors":["Bo Zhang","Li Niu","Liqing Zhang"],"abstract":"Image composition assessment is crucial in aesthetic assessment, which aims to assess the overall composition quality of a given image. However, to the best of our knowledge, there is neither dataset nor method specifically proposed for this task. In this paper, we contribute the first composition assessment dataset CADB with composition scores for each image provided by multiple professional raters. Besides, we propose a composition assessment network SAMP-Net with a novel Saliency-Augmented Multi-pattern Pooling (SAMP) module, which analyses visual layout from the perspectives of multiple composition patterns. We also leverage composition-relevant attributes to further boost the performance, and extend Earth Mover's Distance (EMD) loss to weighted EMD loss to eliminate the content bias. The experimental results show that our SAMP-Net can perform more favorably than previous aesthetic assessment approaches.","url_abs":"https://arxiv.org/abs/2104.03133v2","url_pdf":"https://arxiv.org/pdf/2104.03133v2.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":"image-composition-assessment-with-saliency","repo_url":"https://github.com/bcmi/Image-Composition-Assessment-Dataset-CADB","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"aesthetics-quality-assessment","task_name":"Aesthetics Quality Assessment"}],"methods":[],"datasets_introduced":[{"slug":"cadb","name":"CADB","full_name":"Composition Assessment DataBase"}],"methods_introduced":[],"results":[{"leaderboard":"/sota/aesthetics-quality-assessment-on-cadb","task":"Aesthetics Quality Assessment","dataset":"CADB","model":"SAMP-Net (Ours)","rank_in_archive_order":1,"of":1,"metrics":{"EMD":"0.1798","LCCAll":"0.6709","MSE":"0.3867","SRCC":"0.6564"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2104.03133","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.03133"}},"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":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/bcmi/Image-Composition-Assessment-Dataset-CADB","reach":{"status":"ok","spdx":"MIT"}}],"summary":{"unverified":3},"by_repo_kind":{"official":{"samples":3,"ran":0,"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":"c62f2b0d078c933f","entry":"build_resnet","repo":"bcmi/Image-Composition-Assessment-Dataset-CADB","repo_kind":"official","path":"SAMPNet/samp_net.py","file_url":"https://github.com/bcmi/Image-Composition-Assessment-Dataset-CADB/blob/HEAD/SAMPNet/samp_net.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":"c62f2b0d078c933f"}},{"code_sha256_prefix":"f6a80930baed0869","entry":"detect_saliency","repo":"bcmi/Image-Composition-Assessment-Dataset-CADB","repo_kind":"official","path":"SAMPNet/cadb_dataset.py","file_url":"https://github.com/bcmi/Image-Composition-Assessment-Dataset-CADB/blob/HEAD/SAMPNet/cadb_dataset.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":"f6a80930baed0869"}},{"code_sha256_prefix":"cbb96c1d0826496d","entry":"resize","repo":"bcmi/Image-Composition-Assessment-Dataset-CADB","repo_kind":"official","path":"SAMPNet/cadb_dataset.py","file_url":"https://github.com/bcmi/Image-Composition-Assessment-Dataset-CADB/blob/HEAD/SAMPNet/cadb_dataset.py","link_basis":"harvester_set","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":"cbb96c1d0826496d"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}