{"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/metric-learning-with-horde-high-order","title":"Metric Learning With HORDE: High-Order Regularizer for Deep Embeddings","arxiv_id":"1908.02735","date":"2019-08-07","proceeding":"ICCV 2019 10","authors":["Pierre Jacob","David Picard","Aymeric Histace","Edouard Klein"],"abstract":"Learning an effective similarity measure between image representations is key to the success of recent advances in visual search tasks (e.g. verification or zero-shot learning). Although the metric learning part is well addressed, this metric is usually computed over the average of the extracted deep features. This representation is then trained to be discriminative. However, these deep features tend to be scattered across the feature space. Consequently, the representations are not robust to outliers, object occlusions, background variations, etc. In this paper, we tackle this scattering problem with a distribution-aware regularization named HORDE. This regularizer enforces visually-close images to have deep features with the same distribution which are well localized in the feature space. We provide a theoretical analysis supporting this regularization effect. We also show the effectiveness of our approach by obtaining state-of-the-art results on 4 well-known datasets (Cub-200-2011, Cars-196, Stanford Online Products and Inshop Clothes Retrieval).","url_abs":"https://arxiv.org/abs/1908.02735v1","url_pdf":"https://arxiv.org/pdf/1908.02735v1.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":"metric-learning-with-horde-high-order","repo_url":"https://github.com/pierre-jacob/ICCV2019-Horde","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"image-retrieval","task_name":"Image Retrieval"},{"task_slug":"metric-learning","task_name":"Metric Learning"},{"task_slug":"retrieval","task_name":"Retrieval"},{"task_slug":"high","task_name":"Vocal Bursts Intensity Prediction"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/metric-learning-on-cars196","task":"Metric Learning","dataset":"CARS196","model":"ABE + HORDE","rank_in_archive_order":19,"of":36,"metrics":{"R@1":"88.0"},"uses_additional_data":true},{"leaderboard":"/sota/metric-learning-on-cub-200-2011","task":"Metric Learning","dataset":"CUB-200-2011","model":"ABE + HORDE","rank_in_archive_order":18,"of":30,"metrics":{"R@1":"66.8"},"uses_additional_data":true}],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=1908.02735","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1908.02735"}},"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/pierre-jacob/ICCV2019-Horde","reach":{"status":"ok","spdx":"MIT"}}],"summary":{"unverified":8},"by_repo_kind":{"official":{"samples":8,"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":"4082f06b7564e711","entry":"Baseline","repo":"pierre-jacob/ICCV2019-Horde","repo_kind":"official","path":"kerastools/models/dml_models.py","file_url":"https://github.com/pierre-jacob/ICCV2019-Horde/blob/HEAD/kerastools/models/dml_models.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":"4082f06b7564e711"}},{"code_sha256_prefix":"fcf67fbb104154cd","entry":"CascadedABE","repo":"pierre-jacob/ICCV2019-Horde","repo_kind":"official","path":"kerastools/models/horde_models.py","file_url":"https://github.com/pierre-jacob/ICCV2019-Horde/blob/HEAD/kerastools/models/horde_models.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":"fcf67fbb104154cd"}},{"code_sha256_prefix":"1afe4d22baeab5b8","entry":"CascadedKOrder","repo":"pierre-jacob/ICCV2019-Horde","repo_kind":"official","path":"kerastools/models/horde_models.py","file_url":"https://github.com/pierre-jacob/ICCV2019-Horde/blob/HEAD/kerastools/models/horde_models.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":"1afe4d22baeab5b8"}},{"code_sha256_prefix":"beade91d807dec03","entry":"KOrderModel","repo":"pierre-jacob/ICCV2019-Horde","repo_kind":"official","path":"kerastools/models/horde_models.py","file_url":"https://github.com/pierre-jacob/ICCV2019-Horde/blob/HEAD/kerastools/models/horde_models.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":"beade91d807dec03"}},{"code_sha256_prefix":"7d92a9a1e0d8d375","entry":"make_abe_loss","repo":"pierre-jacob/ICCV2019-Horde","repo_kind":"official","path":"kerastools/losses/iccv2019_loss.py","file_url":"https://github.com/pierre-jacob/ICCV2019-Horde/blob/HEAD/kerastools/losses/iccv2019_loss.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":"7d92a9a1e0d8d375"}},{"code_sha256_prefix":"e10c8512e9f6e59a","entry":"make_multi_class_binomial_deviance","repo":"pierre-jacob/ICCV2019-Horde","repo_kind":"official","path":"kerastools/losses/dml_loss.py","file_url":"https://github.com/pierre-jacob/ICCV2019-Horde/blob/HEAD/kerastools/losses/dml_loss.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":"e10c8512e9f6e59a"}},{"code_sha256_prefix":"4f26b26e102be680","entry":"make_multi_class_contrastive_loss","repo":"pierre-jacob/ICCV2019-Horde","repo_kind":"official","path":"kerastools/losses/dml_loss.py","file_url":"https://github.com/pierre-jacob/ICCV2019-Horde/blob/HEAD/kerastools/losses/dml_loss.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":"4f26b26e102be680"}},{"code_sha256_prefix":"83696e652600803a","entry":"make_multi_class_triplet_loss","repo":"pierre-jacob/ICCV2019-Horde","repo_kind":"official","path":"kerastools/losses/dml_loss.py","file_url":"https://github.com/pierre-jacob/ICCV2019-Horde/blob/HEAD/kerastools/losses/dml_loss.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":"83696e652600803a"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}