{"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/one-shot-unsupervised-cross-domain","title":"One-Shot Unsupervised Cross Domain Translation","arxiv_id":"1806.06029","date":"2018-06-15","proceeding":"NeurIPS 2018 12","authors":["Sagie Benaim","Lior Wolf"],"abstract":"Given a single image x from domain A and a set of images from domain B, our\ntask is to generate the analogous of x in B. We argue that this task could be a\nkey AI capability that underlines the ability of cognitive agents to act in the\nworld and present empirical evidence that the existing unsupervised domain\ntranslation methods fail on this task. Our method follows a two step process.\nFirst, a variational autoencoder for domain B is trained. Then, given the new\nsample x, we create a variational autoencoder for domain A by adapting the\nlayers that are close to the image in order to directly fit x, and only\nindirectly adapt the other layers. Our experiments indicate that the new method\ndoes as well, when trained on one sample x, as the existing domain transfer\nmethods, when these enjoy a multitude of training samples from domain A. Our\ncode is made publicly available at\nhttps://github.com/sagiebenaim/OneShotTranslation","url_abs":"http://arxiv.org/abs/1806.06029v2","url_pdf":"http://arxiv.org/pdf/1806.06029v2.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":"one-shot-unsupervised-cross-domain","repo_url":"https://github.com/sagiebenaim/OneShotTranslation","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"NOASSERTION"}},{"paper_slug":"one-shot-unsupervised-cross-domain","repo_url":"https://github.com/guy-oren/OneShotTranslationExt","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"NOASSERTION"}}],"tasks":[{"task_slug":"translation","task_name":"Translation"},{"task_slug":"unsupervised-image-to-image-translation","task_name":"Unsupervised Image-To-Image Translation"},{"task_slug":"zero-shot-learning","task_name":"Zero-Shot Learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1806.06029","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1806.06029"}},"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/guy-oren/OneShotTranslationExt","reach":{"status":"ok","spdx":"NOASSERTION"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/sagiebenaim/OneShotTranslation","reach":{"status":"ok","spdx":"NOASSERTION"}}],"summary":{"ran_violates":1},"by_repo_kind":{"official":{"samples":1,"ran":1,"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":1,"samples":[{"code_sha256_prefix":"e5b1aff86a339d0e","entry":"str2bool","repo":"sagiebenaim/OneShotTranslation","repo_kind":"official","path":"mnist_to_svhn/main_autoencoder.py","file_url":"https://github.com/sagiebenaim/OneShotTranslation/blob/HEAD/mnist_to_svhn/main_autoencoder.py","link_basis":"plan_row","language":"python","status":"ran_violates","verification_level":1,"contract_check":"VIOLATES","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"e5b1aff86a339d0e"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}