{"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/deep-structured-energy-based-image-inpainting","title":"Deep Structured Energy-Based Image Inpainting","arxiv_id":"1801.07939","date":"2018-01-24","proceeding":null,"authors":["Fazil Altinel","Mete Ozay","Takayuki Okatani"],"abstract":"In this paper, we propose a structured image inpainting method employing an\nenergy based model. In order to learn structural relationship between patterns\nobserved in images and missing regions of the images, we employ an energy-based\nstructured prediction method. The structural relationship is learned by\nminimizing an energy function which is defined by a simple convolutional neural\nnetwork. The experimental results on various benchmark datasets show that our\nproposed method significantly outperforms the state-of-the-art methods which\nuse Generative Adversarial Networks (GANs). We obtained 497.35 mean squared\nerror (MSE) on the Olivetti face dataset compared to 833.0 MSE provided by the\nstate-of-the-art method. Moreover, we obtained 28.4 dB peak signal to noise\nratio (PSNR) on the SVHN dataset and 23.53 dB on the CelebA dataset, compared\nto 22.3 dB and 21.3 dB, provided by the state-of-the-art methods, respectively.\nThe code is publicly available.","url_abs":"http://arxiv.org/abs/1801.07939v2","url_pdf":"http://arxiv.org/pdf/1801.07939v2.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":"deep-structured-energy-based-image-inpainting","repo_url":"https://github.com/cvlab-tohoku/DSEBImageInpainting","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":"image-inpainting","task_name":"Image Inpainting"},{"task_slug":"structured-prediction","task_name":"Structured Prediction"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1801.07939","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1801.07939"}},"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/cvlab-tohoku/DSEBImageInpainting","reach":null}],"summary":{"ran_draft_wrong":1,"ran_fixture":1},"by_repo_kind":{"official":{"samples":2,"ran":2,"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":2,"samples":[{"code_sha256_prefix":"b0e3c7e1afbc8f53","entry":"createBatchSpec","repo":"cvlab-tohoku/DSEBImageInpainting","repo_kind":"official","path":"utils.py","file_url":"https://github.com/cvlab-tohoku/DSEBImageInpainting/blob/HEAD/utils.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"GPL-3.0","inline_ok":false,"mcp_get_code":{"code_sha256":"b0e3c7e1afbc8f53"}},{"code_sha256_prefix":"8e429c99a8c6d662","entry":"cropCenter","repo":"cvlab-tohoku/DSEBImageInpainting","repo_kind":"official","path":"utils.py","file_url":"https://github.com/cvlab-tohoku/DSEBImageInpainting/blob/HEAD/utils.py","link_basis":"first_harvest_node","language":"python","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"GPL-3.0","inline_ok":false,"mcp_get_code":{"code_sha256":"8e429c99a8c6d662"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}