{"url":"/dataset/fc100","name":"FC100","full_name":"Fewshot-CIFAR100","description_markdown":"The **FC100** dataset (**Fewshot-CIFAR100**) is a newly split dataset based on CIFAR-100 for few-shot learning. It contains 20 high-level categories which are divided into 12, 4, 4 categories for training, validation and test. There are 60, 20, 20 low-level classes in the corresponding split containing 600 images of size 32 × 32 per class. Smaller image size makes it more challenging for few-shot learning.\r\n\r\nSource: [Prototype Rectification for Few-Shot Learning](https://arxiv.org/abs/1911.10713)","description_withheld":null,"homepage":"https://github.com/ElementAI/TADAM","introduced_date":"2018-01-01","introduced_date_note":null,"introduced_by":{"paper":"/paper/tadam-task-dependent-adaptive-metric-for","title":"TADAM: Task dependent adaptive metric for improved few-shot learning","first_author":"Boris N. Oreshkin","url":null},"license":{"name":"Unknown","url":null},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Few-Shot Image Classification","url":"/task/few-shot-image-classification","datasets_with_task":"/datasets/task/few-shot-image-classification"}],"languages":[],"variants":["Fewshot-CIFAR100 - 1-Shot Learning","Fewshot-CIFAR100 - 5-Shot Learning","Fewshot-CIFAR100 - 10-Shot Learning","FC100 5-way (1-shot)","FC100 5-way (5-shot)","FC100 5-way (10-shot)","FC100"],"data_loaders":[{"repo":"https://github.com/learnables/learn2learn","url":"http://learn2learn.net","frameworks":["pytorch"]},{"repo":"https://github.com/ElementAI/TADAM","url":"https://github.com/ElementAI/TADAM","frameworks":[]}],"num_papers_in_archive":137,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/few-shot-image-classification-on-fc100-5-way","task":"Few-Shot Image Classification","dataset_variant":"FC100 5-way (1-shot)","rows":22,"metrics":["Accuracy"],"first_row_in_archive_order":{"model":"BAVARDAGE","paper":"/paper/adaptive-dimension-reduction-and-variational","metrics":{"Accuracy":"57.27"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/few-shot-image-classification-on-fc100-5-way-1","task":"Few-Shot Image Classification","dataset_variant":"FC100 5-way (5-shot)","rows":22,"metrics":["Accuracy"],"first_row_in_archive_order":{"model":"BAVARDAGE","paper":"/paper/adaptive-dimension-reduction-and-variational","metrics":{"Accuracy":"70.60"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/few-shot-image-classification-on-fc100-5-way-2","task":"Few-Shot Image Classification","dataset_variant":"FC100 5-way (10-shot)","rows":1,"metrics":["Accuracy"],"first_row_in_archive_order":{"model":"MTL","paper":"/paper/meta-transfer-learning-for-few-shot-learning","metrics":{"Accuracy":"63.4"},"code_links":[{"title":"yaoyao-liu/meta-transfer-learning","url":"https://github.com/yaoyao-liu/meta-transfer-learning"},{"title":"yaoyao-liu/mini-imagenet-tools","url":"https://github.com/yaoyao-liu/mini-imagenet-tools"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/few-shot-image-classification-on-fewshot","task":"Few-Shot Image Classification","dataset_variant":"Fewshot-CIFAR100 - 1-Shot Learning","rows":1,"metrics":["Accuracy"],"first_row_in_archive_order":{"model":"pseudo-shots","paper":"/paper/pseudo-shots-few-shot-learning-with-auxiliary","metrics":{"Accuracy":"50.57%"},"code_links":[{"title":"BatsResearch/efsl","url":"https://github.com/BatsResearch/efsl"},{"title":"Reza-esfandiarpoor/pseudo-shots","url":"https://github.com/Reza-esfandiarpoor/pseudo-shots"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/few-shot-image-classification-on-fewshot-1","task":"Few-Shot Image Classification","dataset_variant":"Fewshot-CIFAR100 - 5-Shot Learning","rows":1,"metrics":["Accuracy"],"first_row_in_archive_order":{"model":"pseudo-shots","paper":"/paper/pseudo-shots-few-shot-learning-with-auxiliary","metrics":{"Accuracy":"61.58%"},"code_links":[{"title":"BatsResearch/efsl","url":"https://github.com/BatsResearch/efsl"},{"title":"Reza-esfandiarpoor/pseudo-shots","url":"https://github.com/Reza-esfandiarpoor/pseudo-shots"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/enhancing-few-shot-image-classification","title":"Enhancing Few-Shot Image Classification through Learnable Multi-Scale Embedding and Attention Mechanisms","date":"2024-09-12","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/adaptive-dimension-reduction-and-variational","title":"Adaptive Dimension Reduction and Variational Inference for Transductive Few-Shot Classification","date":"2022-09-18","rows_on_this_dataset":2,"code_links":0,"syntology":null},{"paper":"/paper/rethinking-generalization-in-few-shot-1","title":"Rethinking Generalization in Few-Shot Classification","date":"2022-06-15","rows_on_this_dataset":2,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":3,"samples_ran":2,"samples_unverified":1,"pointer_only_for_licence":3,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/attribute-surrogates-learning-and-spectral","title":"Attribute Surrogates Learning and Spectral Tokens Pooling in Transformers for Few-shot Learning","date":"2022-03-17","rows_on_this_dataset":2,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":5,"samples_ran":4,"samples_unverified":1,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/easy-ensemble-augmented-shot-y-shaped","title":"EASY: Ensemble Augmented-Shot Y-shaped Learning: State-Of-The-Art Few-Shot Classification with Simple Ingredients","date":"2022-01-24","rows_on_this_dataset":8,"code_links":3,"syntology":null},{"paper":"/paper/sparse-spatial-transformers-for-few-shot","title":"Sparse Spatial Transformers for Few-Shot Learning","date":"2021-09-27","rows_on_this_dataset":2,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":6,"samples_ran":0,"samples_unverified":6,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/bridging-multi-task-learning-and-meta","title":"Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective Adaptation","date":"2021-06-16","rows_on_this_dataset":2,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":10,"samples_ran":1,"samples_unverified":9,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/exploring-complementary-strengths-of","title":"Exploring Complementary Strengths of Invariant and Equivariant Representations for Few-Shot Learning","date":"2021-03-01","rows_on_this_dataset":2,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":1,"samples_ran":1,"samples_unverified":0,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/constellation-nets-for-few-shot-learning","title":"Constellation Nets for Few-Shot Learning","date":"2021-01-01","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/pseudo-shots-few-shot-learning-with-auxiliary","title":"Extended Few-Shot Learning: Exploiting Existing Resources for Novel Tasks","date":"2020-12-13","rows_on_this_dataset":4,"code_links":2,"syntology":null},{"paper":"/paper/complementing-representation-deficiency-in","title":"Complementing Representation Deficiency in Few-shot Image Classification: A Meta-Learning Approach","date":"2020-07-21","rows_on_this_dataset":4,"code_links":1,"syntology":null},{"paper":"/paper/self-supervised-knowledge-distillation-for","title":"Self-supervised Knowledge Distillation for Few-shot Learning","date":"2020-06-17","rows_on_this_dataset":2,"code_links":2,"syntology":null},{"paper":"/paper/task-augmentation-by-rotating-for-meta","title":"Task Augmentation by Rotating for Meta-Learning","date":"2020-02-08","rows_on_this_dataset":4,"code_links":1,"syntology":null},{"paper":"/paper/fast-and-generalized-adaptation-for-few-shot","title":"Generalized Adaptation for Few-Shot Learning","date":"2019-11-25","rows_on_this_dataset":2,"code_links":0,"syntology":null},{"paper":"/paper/meta-learning-with-differentiable-convex","title":"Meta-Learning with Differentiable Convex Optimization","date":"2019-04-07","rows_on_this_dataset":2,"code_links":7,"syntology":null},{"paper":"/paper/meta-transfer-learning-for-few-shot-learning","title":"Meta-Transfer Learning for Few-Shot Learning","date":"2018-12-06","rows_on_this_dataset":3,"code_links":2,"syntology":null},{"paper":"/paper/tadam-task-dependent-adaptive-metric-for","title":"TADAM: Task dependent adaptive metric for improved few-shot learning","date":"2018-05-23","rows_on_this_dataset":2,"code_links":3,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":9,"samples_ran":0,"samples_unverified":9,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":6,"samples_harvested":34,"samples_ran":8,"samples_unverified":26,"pointer_only_for_licence":3,"papers_with_no_sample_that_ran":2,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}