# 5-way 1-shot Image Classification on miniImageNet standard (test) Source: [5-way 1-shot Image Classification on miniImageNet standard (test)]() Collection index: [llms.txt]() Data updated: 2026-02-26T05:27:57.612Z Evaluation of 5-way, 1-shot few-shot classification performance on the test split of the standard miniImageNet dataset, measured by accuracy. A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. | Scope | Recorded value | | --- | --- | | Task | 5-way 1-shot Image Classification | | Dataset (including any stated split) | miniImageNet standard (test) | | Metric | Accuracy | | Unit | PERCENT | | Direction | Higher is better | | Results loaded | 12 of 12 | | Coverage | All results currently returned for this benchmark | Evaluation settings may differ between results. The original papers and recorded configurations are needed to establish comparability. A shared metric name alone does not establish an identical protocol. ## Metrics - [Accuracy](): Higher is better; unit: PERCENT. ## Recorded results | Method | Accuracy | Result date | Report paper | | --- | --- | --- | --- | | TrainProto-FSL | 58.92 | Not recorded | 68fa6a3d1e209131cea26ed1 | | CSSL-FSL\_Image168 | 54.17 | Not recorded | 68fa6a3d1e209131cea26ed1 | | ProtoNets | 47.01 | Not recorded | 68fa6a3d1e209131cea26ed1 | | MAML | 46.6 | Not recorded | 68fa6a3d1e209131cea26ed1 | | ULDA-MetaOptNet | 40.71 | Not recorded | 68fa6a3d1e209131cea26ed1 | | ULDA-ProtoNets | 40.63 | Not recorded | 68fa6a3d1e209131cea26ed1 | | UMTRA | 39.93 | Not recorded | 68fa6a3d1e209131cea26ed1 | | CACTUS-MAML | 39.9 | Not recorded | 68fa6a3d1e209131cea26ed1 | | CACTUS-ProtoNets | 39.18 | Not recorded | 68fa6a3d1e209131cea26ed1 | | AAL-ProtoNets | 37.67 | Not recorded | 68fa6a3d1e209131cea26ed1 | | AAL-MAML++ | 34.57 | Not recorded | 68fa6a3d1e209131cea26ed1 | | UFLST | 33.77 | Not recorded | 68fa6a3d1e209131cea26ed1 | ### TrainProto-FSL Accuracy: 58.92. Result ID: 698e2258ffc3901de09b10d3. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Supervision":"unsupervised"}. This record does not assert independent reproduction. ### CSSL-FSL\_Image168 Accuracy: 54.17. Result ID: 698e2258ffc3901de09b10d2. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Supervision":"unsupervised"}. This record does not assert independent reproduction. ### ProtoNets Accuracy: 47.01. Result ID: 698e2258ffc3901de09b10d5. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Supervision":"supervised"}. This record does not assert independent reproduction. ### MAML Accuracy: 46.6. Result ID: 698e2258ffc3901de09b10d4. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Supervision":"supervised"}. This record does not assert independent reproduction. ### ULDA-MetaOptNet Accuracy: 40.71. Result ID: 698e2258ffc3901de09b10d1. [Reporting paper]() [Method origin paper]() [Implementation]() Recorded evaluation configuration: {"Supervision":"unsupervised"}. This record does not assert independent reproduction. ### ULDA-ProtoNets Accuracy: 40.63. Result ID: 698e2258ffc3901de09b10d0. [Reporting paper]() [Method origin paper]() [Implementation]() Recorded evaluation configuration: {"Supervision":"unsupervised"}. This record does not assert independent reproduction. ### UMTRA Accuracy: 39.93. Result ID: 698e2258ffc3901de09b10cd. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Supervision":"unsupervised"}. This record does not assert independent reproduction. ### CACTUS-MAML Accuracy: 39.9. Result ID: 698e2258ffc3901de09b10ca. [Reporting paper]() [Method origin paper]() [Implementation]() Recorded evaluation configuration: {"Supervision":"unsupervised"}. This record does not assert independent reproduction. ### CACTUS-ProtoNets Accuracy: 39.18. Result ID: 698e2258ffc3901de09b10cb. [Reporting paper]() [Method origin paper]() [Implementation]() Recorded evaluation configuration: {"Supervision":"unsupervised"}. This record does not assert independent reproduction. ### AAL-ProtoNets Accuracy: 37.67. Result ID: 698e2258ffc3901de09b10ce. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Supervision":"unsupervised"}. This record does not assert independent reproduction. ### AAL-MAML++ Accuracy: 34.57. Result ID: 698e2258ffc3901de09b10cf. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Supervision":"unsupervised"}. This record does not assert independent reproduction. ### UFLST Accuracy: 33.77. Result ID: 698e2258ffc3901de09b10cc. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Supervision":"unsupervised"}. This record does not assert independent reproduction. Page 1 of 1. This is an index page, not the full collection.