研究图像分辨率对人脸年龄估计的影响，发现224x224是最佳尺寸。
Impact of Image Resolution on Age Estimation with DeepFace and InsightFace
- 在7种分辨率下测试1000张图像，评估准确率变化
- 224x224时误差最小，DeepFace MAE为10.83年，InsightFace为7.46年
- 过低或过高分辨率都会降低精度，InsightFace更快
自动年龄估计广泛应用于年龄验证，但输入图像分辨率差异较大。本研究评估了图像分辨率对DeepFace和InsightFace年龄估计准确率的影响。从IMDB-Clean数据集选取1000张图像，在七种分辨率下处理，共生成7000个测试样本。采用平均绝对误差（MAE）、标准差（SD）和中位绝对误差（MedAE）进行评估。结果表明，输入图像分辨率对两种框架的年龄估计准确率均有显著且一致的影响。两者在224x224像素时表现最优，分别达到MAE 10.83年（DeepFace）和7.46年（InsightFace）。低分辨率下MAE显著上升，极高分辨率也导致准确率下降。在整个分辨率范围内，InsightFace始终比DeepFace更快速。
原文摘要 · Abstract (English)
Automatic age estimation is widely used for age verification, where input images often vary considerably in resolution. This study evaluates the effect of image resolution on age estimation accuracy using DeepFace and InsightFace. A total of 1000 images from the IMDB-Clean dataset were processed in seven resolutions, resulting in 7000 test samples. Performance was evaluated using Mean Absolute Error (MAE), Standard Deviation (SD), and Median Absolute Error (MedAE). Based on this study, we conclude that input image resolution has a clear and consistent impact on the accuracy of age estimation in both DeepFace and InsightFace. Both frameworks achieve optimal performance at 224x224 pixels, with an MAE of 10.83 years (DeepFace) and 7.46 years (InsightFace). At low resolutions, MAE increases substantially, while very high resolutions also degrade accuracy. InsightFace is consistently faster than DeepFace across all resolutions.
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