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Age And Gender Classification On Adience Age

Metrics

Accuracy (5-fold)

Results

Performance results of various models on this benchmark

Paper Title
ViT-hSeq84.91A Hybrid Transformer-Sequencer approach for Age and Gender classification from in-wild facial images
MiVOLO-V269.43Beyond Specialization: Assessing the Capabilities of MLLMs in Age and Gender Estimation
MiVOLO-D168.69MiVOLO: Multi-input Transformer for Age and Gender Estimation
AL-ResNets-34 + IMDB-WIKI67.47Fine-Grained Age Estimation in the wild with Attention LSTM Networks
R-SAAFc2 +IMDB-WIKI67.3ConvNets with Smooth Adaptive Activation Functions for Regression
RoR-34 + IMDB-WIKI66.74Age Group and Gender Estimation in the Wild with Deep RoR Architecture
MWR62.6Moving Window Regression: A Novel Approach to Ordinal Regression
UNIORD-ResNet-101 (single crop, pytorch)61Deep Ordinal Regression using Optimal Transport Loss and Unimodal Output Probabilities
RetinaFace + ArcFace + MLP + IC + Skip connections60.86Generalizing MLPs With Dropouts, Batch Normalization, and Skip Connections
CPG (single crop, pytorch)57.66Compacting, Picking and Growing for Unforgetting Continual Learning
PAENet (single crop, tensorflow)57.3Increasingly Packing Multiple Facial-Informatics Modules in A Unified Deep-Learning Model via Lifelong Learning
MegaAge56.01Quantifying Facial Age by Posterior of Age Comparisons
Levi_Hassner CNN (over-sample, caffe)50.7Age and Gender Classification using Convolutional Neural Networks
Levi_Hassner CNN (single crop, caffe)49.5Age and Gender Classification using Convolutional Neural Networks
LMTCNN-2-1 (single crop, tensorflow)44.26Joint Estimation of Age and Gender from Unconstrained Face Images using Lightweight Multi-task CNN for Mobile Applications
Levi_Hassner CNN (single crop, tensorflow)44.14Age and Gender Classification using Convolutional Neural Networks
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