# Image Classification on ImageNet Transfer Learning Suite Many-Shot (test) Source: [Image Classification on ImageNet Transfer Learning Suite Many-Shot (test)]() Collection index: [llms.txt]() Data updated: 2026-02-26T05:34:06.213Z Evaluation of Image Classification performance using a transfer learning setup, measuring accuracy across multiple downstream datasets/subsets (e.g., Aircraft, Caltech, Cars, CIFAR-10, VOC) and reporting the average performance. 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 | Image Classification | | Dataset (including any stated split) | ImageNet Transfer Learning Suite Many-Shot (test) | | Metric | Accuracy (Aircraft) | | Unit | PERCENT | | Direction | Higher is better | | Results loaded | 6 of 6 | | 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 (Aircraft)](): Higher is better; unit: PERCENT. - [Accuracy (Caltech)](): Higher is better; unit: PERCENT. - [Accuracy (Cars)](): Higher is better; unit: PERCENT. - [Accuracy (CIFAR-10)](): Higher is better; unit: PERCENT. - [Accuracy (CIFAR-100)](): Higher is better; unit: PERCENT. - [Accuracy (DTD)](): Higher is better; unit: PERCENT. - [Accuracy (Flowers)](): Higher is better; unit: PERCENT. - [Accuracy (Food)](): Higher is better; unit: PERCENT. - [Accuracy (Pets)](): Higher is better; unit: PERCENT. - [Accuracy (SUN)](): Higher is better; unit: PERCENT. - [Accuracy (VOC)](): Higher is better; unit: PERCENT. - [Average Accuracy](): Higher is better; unit: PERCENT. ## Recorded results | Method | Accuracy (Aircraft) | Result date | Report paper | | --- | --- | --- | --- | | IP-IRM | 43.12 | Not recorded | 68fa6b2c1e209131cea2c8e9 | | MoCo-v2 | 41.28 | Not recorded | 68fa6b2c1e209131cea2c8e9 | | PIRL | 37.08 | Not recorded | 68fa6b2c1e209131cea2c8e9 | | InsDis | 36.87 | Not recorded | 68fa6b2c1e209131cea2c8e9 | | MoCo-v1 | 35.55 | Not recorded | 68fa6b2c1e209131cea2c8e9 | | PCL | 21.61 | Not recorded | 68fa6b2c1e209131cea2c8e9 | ### IP-IRM Accuracy (Aircraft): 43.12. Result ID: 698e6777ffc3901de09d4daf. [Reporting paper]() [Method origin paper]() [Implementation]() Recorded evaluation configuration: {"Regime":"Many-Shot"}. This record does not assert independent reproduction. ### MoCo-v2 Accuracy (Aircraft): 41.28. Result ID: 698e6777ffc3901de09d4dae. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Regime":"Many-Shot"}. This record does not assert independent reproduction. ### PIRL Accuracy (Aircraft): 37.08. Result ID: 698e6777ffc3901de09d4dac. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Regime":"Many-Shot"}. This record does not assert independent reproduction. ### InsDis Accuracy (Aircraft): 36.87. Result ID: 698e6777ffc3901de09d4daa. [Reporting paper]() [Method origin paper]() [Implementation]() Recorded evaluation configuration: {"Regime":"Many-Shot"}. This record does not assert independent reproduction. ### MoCo-v1 Accuracy (Aircraft): 35.55. Result ID: 698e6777ffc3901de09d4dad. [Reporting paper]() [Method origin paper]() [Implementation]() Recorded evaluation configuration: {"Regime":"Many-Shot"}. This record does not assert independent reproduction. ### PCL Accuracy (Aircraft): 21.61. Result ID: 698e6777ffc3901de09d4dab. [Reporting paper]() [Method origin paper]() [Implementation]() Recorded evaluation configuration: {"Regime":"Many-Shot"}. This record does not assert independent reproduction. Page 1 of 1. This is an index page, not the full collection.