{"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/joint-distribution-matters-deep-brownian","title":"Joint Distribution Matters: Deep Brownian Distance Covariance for Few-Shot Classification","arxiv_id":"2204.04567","date":"2022-04-09","proceeding":"CVPR 2022 1","authors":["Jiangtao Xie","Fei Long","Jiaming Lv","Qilong Wang","Peihua Li"],"abstract":"Few-shot classification is a challenging problem as only very few training examples are given for each new task. One of the effective research lines to address this challenge focuses on learning deep representations driven by a similarity measure between a query image and few support images of some class. Statistically, this amounts to measure the dependency of image features, viewed as random vectors in a high-dimensional embedding space. Previous methods either only use marginal distributions without considering joint distributions, suffering from limited representation capability, or are computationally expensive though harnessing joint distributions. In this paper, we propose a deep Brownian Distance Covariance (DeepBDC) method for few-shot classification. The central idea of DeepBDC is to learn image representations by measuring the discrepancy between joint characteristic functions of embedded features and product of the marginals. As the BDC metric is decoupled, we formulate it as a highly modular and efficient layer. Furthermore, we instantiate DeepBDC in two different few-shot classification frameworks. We make experiments on six standard few-shot image benchmarks, covering general object recognition, fine-grained categorization and cross-domain classification. Extensive evaluations show our DeepBDC significantly outperforms the counterparts, while establishing new state-of-the-art results. The source code is available at http://www.peihuali.org/DeepBDC","url_abs":"https://arxiv.org/abs/2204.04567v1","url_pdf":"https://arxiv.org/pdf/2204.04567v1.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":"joint-distribution-matters-deep-brownian","repo_url":"https://github.com/Fei-Long121/DeepBDC","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"classification-1","task_name":"Classification"},{"task_slug":"few-shot-image-classification","task_name":"Few-Shot Image Classification"},{"task_slug":"few-shot-learning","task_name":"Few-Shot Learning"},{"task_slug":"object-recognition","task_name":"Object Recognition"},{"task_slug":"domain-classification","task_name":"domain classification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/few-shot-image-classification-on-mini-2","task":"Few-Shot Image Classification","dataset":"Mini-Imagenet 5-way (1-shot)","model":"STL DeepBDC (Inductive)","rank_in_archive_order":42,"of":105,"metrics":{"Accuracy":"67.83"},"uses_additional_data":false},{"leaderboard":"/sota/few-shot-image-classification-on-mini-2","task":"Few-Shot Image Classification","dataset":"Mini-Imagenet 5-way (1-shot)","model":"Meta DeepBDC  (Inductive)","rank_in_archive_order":45,"of":105,"metrics":{"Accuracy":"67.34"},"uses_additional_data":false}],"syntology":{"syntology_url":"https://syntology.ai/paper/2204.04567","atlas_url":"https://app.syntology.ai/?focus=2204.04567","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2204.04567"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-25T09:33:49+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/Fei-Long121/DeepBDC","reach":null}],"summary":{"ran":1,"ran_fixture":2},"by_repo_kind":{"official":{"samples":3,"ran":3,"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":3,"samples":[{"code_sha256_prefix":"cf01694722384443","entry":"BDC","repo":"Fei-Long121/DeepBDC","repo_kind":"official","path":"methods/bdc_module.py","file_url":"https://github.com/Fei-Long121/DeepBDC/blob/HEAD/methods/bdc_module.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":true,"licence":"NOASSERTION","inline_ok":false,"mcp_get_code":{"code_sha256":"cf01694722384443"}},{"code_sha256_prefix":"2c55f8e06fc05150","entry":"BDCovpool","repo":"Fei-Long121/DeepBDC","repo_kind":"official","path":"methods/bdc_module.py","file_url":"https://github.com/Fei-Long121/DeepBDC/blob/HEAD/methods/bdc_module.py","link_basis":"first_harvest_node","language":"python","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"NOASSERTION","inline_ok":false,"mcp_get_code":{"code_sha256":"2c55f8e06fc05150"}},{"code_sha256_prefix":"2ddde45c1a7c378e","entry":"Triuvec","repo":"Fei-Long121/DeepBDC","repo_kind":"official","path":"methods/bdc_module.py","file_url":"https://github.com/Fei-Long121/DeepBDC/blob/HEAD/methods/bdc_module.py","link_basis":"first_harvest_node","language":"python","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"NOASSERTION","inline_ok":false,"mcp_get_code":{"code_sha256":"2ddde45c1a7c378e"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}