{"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/zero-shot-object-detection-learning-to","title":"Zero-Shot Object Detection: Learning to Simultaneously Recognize and Localize Novel Concepts","arxiv_id":"1803.06049","date":"2018-03-16","proceeding":null,"authors":["Shafin Rahman","Salman Khan","Fatih Porikli"],"abstract":"Current Zero-Shot Learning (ZSL) approaches are restricted to recognition of\na single dominant unseen object category in a test image. We hypothesize that\nthis setting is ill-suited for real-world applications where unseen objects\nappear only as a part of a complex scene, warranting both the `recognition' and\n`localization' of an unseen category. To address this limitation, we introduce\na new \\emph{`Zero-Shot Detection'} (ZSD) problem setting, which aims at\nsimultaneously recognizing and locating object instances belonging to novel\ncategories without any training examples. We also propose a new experimental\nprotocol for ZSD based on the highly challenging ILSVRC dataset, adhering to\npractical issues, e.g., the rarity of unseen objects. To the best of our\nknowledge, this is the first end-to-end deep network for ZSD that jointly\nmodels the interplay between visual and semantic domain information. To\novercome the noise in the automatically derived semantic descriptions, we\nutilize the concept of meta-classes to design an original loss function that\nachieves synergy between max-margin class separation and semantic space\nclustering. Furthermore, we present a baseline approach extended from\nrecognition to detection setting. Our extensive experiments show significant\nperformance boost over the baseline on the imperative yet difficult ZSD\nproblem.","url_abs":"http://arxiv.org/abs/1803.06049v1","url_pdf":"http://arxiv.org/pdf/1803.06049v1.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":"zero-shot-object-detection-learning-to","repo_url":"https://github.com/salman-h-khan/ZSD_Release","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[{"task_slug":"clustering","task_name":"Clustering"},{"task_slug":"novel-concepts","task_name":"Novel Concepts"},{"task_slug":"object-detection","task_name":"Object Detection"},{"task_slug":"zero-shot-learning","task_name":"Zero-Shot Learning"},{"task_slug":"zero-shot-object-detection","task_name":"Zero-Shot Object Detection"},{"task_slug":"object-detection-1","task_name":"object-detection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1803.06049","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1803.06049"}},"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/salman-h-khan/ZSD_Release","reach":null}],"summary":{"ran_fixture":1},"by_repo_kind":{"listed":{"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":0,"samples":[{"code_sha256_prefix":"97c089faf96725d6","entry":"format_img_channels","repo":"salman-h-khan/ZSD_Release","repo_kind":"listed","path":"detect.py","file_url":"https://github.com/salman-h-khan/ZSD_Release/blob/HEAD/detect.py","link_basis":"first_harvest_node","language":"python","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":"invariant","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"97c089faf96725d6"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}