{"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/meta-album-multi-domain-meta-dataset-for-few-1","title":"Meta-Album: Multi-domain Meta-Dataset for Few-Shot Image Classification","arxiv_id":"2302.08909","date":"2023-02-16","proceeding":"NeurIPS 2022 9","authors":["Ihsan Ullah","Dustin Carrión-Ojeda","Sergio Escalera","Isabelle Guyon","Mike Huisman","Felix Mohr","Jan N van Rijn","Haozhe Sun","Joaquin Vanschoren","Phan Anh Vu"],"abstract":"We introduce Meta-Album, an image classification meta-dataset designed to facilitate few-shot learning, transfer learning, meta-learning, among other tasks. It includes 40 open datasets, each having at least 20 classes with 40 examples per class, with verified licences. They stem from diverse domains, such as ecology (fauna and flora), manufacturing (textures, vehicles), human actions, and optical character recognition, featuring various image scales (microscopic, human scales, remote sensing). All datasets are preprocessed, annotated, and formatted uniformly, and come in 3 versions (Micro $\\subset$ Mini $\\subset$ Extended) to match users' computational resources. We showcase the utility of the first 30 datasets on few-shot learning problems. The other 10 will be released shortly after. Meta-Album is already more diverse and larger (in number of datasets) than similar efforts, and we are committed to keep enlarging it via a series of competitions. As competitions terminate, their test data are released, thus creating a rolling benchmark, available through OpenML.org. Our website https://meta-album.github.io/ contains the source code of challenge winning methods, baseline methods, data loaders, and instructions for contributing either new datasets or algorithms to our expandable meta-dataset.","url_abs":"https://arxiv.org/abs/2302.08909v1","url_pdf":"https://arxiv.org/pdf/2302.08909v1.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":"meta-album-multi-domain-meta-dataset-for-few-1","repo_url":"https://github.com/dustincarrion/cd-metadl","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok","spdx":"Apache-2.0"}},{"paper_slug":"meta-album-multi-domain-meta-dataset-for-few-1","repo_url":"https://github.com/ihsaan-ullah/meta-album","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"meta-album-multi-domain-meta-dataset-for-few-1","repo_url":"https://github.com/ihsanullah2131/meta-album","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok"}}],"tasks":[{"task_slug":"few-shot-image-classification","task_name":"Few-Shot Image Classification"},{"task_slug":"few-shot-learning","task_name":"Few-Shot Learning"},{"task_slug":"image-classification","task_name":"Image Classification"},{"task_slug":"meta-learning","task_name":"Meta-Learning"},{"task_slug":"optical-character-recognition","task_name":"Optical Character Recognition"},{"task_slug":"optical-character-recognition","task_name":"Optical Character Recognition (OCR)"},{"task_slug":"transfer-learning","task_name":"Transfer Learning"},{"task_slug":"image-classification","task_name":"image-classification"}],"methods":[{"method_slug":"test","method_name":"Test"}],"datasets_introduced":[{"slug":"meta-album","name":"Meta-Album","full_name":"Multi-domain Meta-Dataset for Few-Shot Image Classification"}],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2302.08909","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2302.08909"}},"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/ihsaan-ullah/meta-album","reach":{"status":"ok"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/ihsanullah2131/meta-album","reach":{"status":"ok"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/dustincarrion/cd-metadl","reach":{"status":"ok","spdx":"Apache-2.0"}}],"summary":{"unverified":4},"by_repo_kind":{"official":{"samples":4,"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":"4cbf490dc725d7b0","entry":"get_batch","repo":"dustincarrion/cd-metadl","repo_kind":"official","path":"baselines/finetuning/helpers_finetuning.py","file_url":"https://github.com/dustincarrion/cd-metadl/blob/HEAD/baselines/finetuning/helpers_finetuning.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"4cbf490dc725d7b0"}},{"code_sha256_prefix":"3844fa96f245e128","entry":"optimize","repo":"dustincarrion/cd-metadl","repo_kind":"official","path":"baselines/finetuning_episodic/helpers_finetuning.py","file_url":"https://github.com/dustincarrion/cd-metadl/blob/HEAD/baselines/finetuning_episodic/helpers_finetuning.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"3844fa96f245e128"}},{"code_sha256_prefix":"47510b198c988efd","entry":"optimize_linear","repo":"dustincarrion/cd-metadl","repo_kind":"official","path":"baselines/finetuning/helpers_finetuning.py","file_url":"https://github.com/dustincarrion/cd-metadl/blob/HEAD/baselines/finetuning/helpers_finetuning.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"47510b198c988efd"}},{"code_sha256_prefix":"0f841af7e4646c70","entry":"process_support_set","repo":"dustincarrion/cd-metadl","repo_kind":"official","path":"baselines/finetuning/helpers_finetuning.py","file_url":"https://github.com/dustincarrion/cd-metadl/blob/HEAD/baselines/finetuning/helpers_finetuning.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"0f841af7e4646c70"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}