# Facial Expression Recognition on FER Private 2013 (test) Source: [Facial Expression Recognition on FER Private 2013 (test)]() Collection index: [llms.txt]() Data updated: 2026-02-26T05:31:58.046Z Evaluation of Facial Expression Recognition performance on the test split of the FER Private 2013 dataset, typically 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 | Facial Expression Recognition | | Dataset (including any stated split) | FER Private 2013 (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 | | --- | --- | --- | --- | | OCFER-Net | 73.475 | Not recorded | 6937ad2b6cfd488761a4e9e6 | | VGG-VD-16 | 72.89 | Not recorded | 68fa62d41e209131ce9fb6df | | HDC†† | 72.72 | Not recorded | 68fa62d41e209131ce9fb6df | | WuJie1010 | 72.388 | Not recorded | 6937ad2b6cfd488761a4e9e6 | | VGG-M | 72.08 | Not recorded | 68fa62d41e209131ce9fb6df | | AlexNet | 71.44 | Not recorded | 68fa62d41e209131ce9fb6df | | HDC\* | 70.58 | Not recorded | 68fa62d41e209131ce9fb6df | | VGG-VD-16 | 70.38 | Not recorded | 68fa62d41e209131ce9fb6df | | Resnet-50 | 70.33 | Not recorded | 68fa62d41e209131ce9fb6df | | Resnet-50 | 69.02 | Not recorded | 68fa62d41e209131ce9fb6df | | VGG-M | 67.57 | Not recorded | 68fa62d41e209131ce9fb6df | | AlexNet | 63.28 | Not recorded | 68fa62d41e209131ce9fb6df | ### OCFER-Net Accuracy: 73.475. Result ID: 6998825c5698665ec4e39844. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Backbone":"ResNet-18"}. This record does not assert independent reproduction. ### VGG-VD-16 Accuracy: 72.89. Result ID: 698be297ecace47ef55991e8. [Reporting paper]() [Method origin paper]() [Implementation]() Recorded evaluation configuration: {"Pretraining":"VGGFaces"}. This record does not assert independent reproduction. ### HDC†† Accuracy: 72.72. Result ID: 698be297ecace47ef55991ea. [Reporting paper]() Recorded evaluation configuration: {"architecture\_type":"ensemble"}. This record does not assert independent reproduction. ### WuJie1010 Accuracy: 72.388. Result ID: 6998825c5698665ec4e39843. [Reporting paper]() Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction. ### VGG-M Accuracy: 72.08. Result ID: 698be297ecace47ef55991e6. [Reporting paper]() [Method origin paper]() [Implementation]() Recorded evaluation configuration: {"Pretraining":"VGGFaces"}. This record does not assert independent reproduction. ### AlexNet Accuracy: 71.44. Result ID: 698be297ecace47ef55991e5. [Reporting paper]() [Method origin paper]() [Implementation]() Recorded evaluation configuration: {"Pretraining":"VGGFaces"}. This record does not assert independent reproduction. ### HDC\* Accuracy: 70.58. Result ID: 698be297ecace47ef55991e9. [Reporting paper]() Recorded evaluation configuration: {"architecture\_type":"best single CNN"}. This record does not assert independent reproduction. ### VGG-VD-16 Accuracy: 70.38. Result ID: 698be297ecace47ef55991e4. [Reporting paper]() [Method origin paper]() [Implementation]() Recorded evaluation configuration: {"Pretraining":"ImageNet"}. This record does not assert independent reproduction. ### Resnet-50 Accuracy: 70.33. Result ID: 698be297ecace47ef55991e7. [Reporting paper]() [Method origin paper]() [Implementation]() Recorded evaluation configuration: {"Pretraining":"VGGFaces"}. This record does not assert independent reproduction. ### Resnet-50 Accuracy: 69.02. Result ID: 698be297ecace47ef55991e3. [Reporting paper]() [Method origin paper]() [Implementation]() Recorded evaluation configuration: {"Pretraining":"ImageNet"}. This record does not assert independent reproduction. ### VGG-M Accuracy: 67.57. Result ID: 698be297ecace47ef55991e2. [Reporting paper]() [Method origin paper]() [Implementation]() Recorded evaluation configuration: {"Pretraining":"ImageNet"}. This record does not assert independent reproduction. ### AlexNet Accuracy: 63.28. Result ID: 698be297ecace47ef55991e1. [Reporting paper]() [Method origin paper]() [Implementation]() Recorded evaluation configuration: {"Pretraining":"ImageNet"}. This record does not assert independent reproduction. Page 1 of 1. This is an index page, not the full collection.