HyperAI초신경

Age And Gender Classification On Adience Age

평가 지표

Accuracy (5-fold)

평가 결과

이 벤치마크에서 각 모델의 성능 결과

		Paper Title
ViT-hSeq	84.91	A Hybrid Transformer-Sequencer approach for Age and Gender classification from in-wild facial images
MiVOLO-V2	69.43	Beyond Specialization: Assessing the Capabilities of MLLMs in Age and Gender Estimation
MiVOLO-D1	68.69	MiVOLO: Multi-input Transformer for Age and Gender Estimation
AL-ResNets-34 + IMDB-WIKI	67.47	Fine-Grained Age Estimation in the wild with Attention LSTM Networks
R-SAAFc2 +IMDB-WIKI	67.3	ConvNets with Smooth Adaptive Activation Functions for Regression
RoR-34 + IMDB-WIKI	66.74	Age Group and Gender Estimation in the Wild with Deep RoR Architecture
MWR	62.6	Moving Window Regression: A Novel Approach to Ordinal Regression
UNIORD-ResNet-101 (single crop, pytorch)	61	Deep Ordinal Regression using Optimal Transport Loss and Unimodal Output Probabilities
RetinaFace + ArcFace + MLP + IC + Skip connections	60.86	Generalizing MLPs With Dropouts, Batch Normalization, and Skip Connections
CPG (single crop, pytorch)	57.66	Compacting, Picking and Growing for Unforgetting Continual Learning
PAENet (single crop, tensorflow)	57.3	Increasingly Packing Multiple Facial-Informatics Modules in A Unified Deep-Learning Model via Lifelong Learning
MegaAge	56.01	Quantifying Facial Age by Posterior of Age Comparisons
Levi_Hassner CNN (over-sample, caffe)	50.7	Age and Gender Classification using Convolutional Neural Networks
Levi_Hassner CNN (single crop, caffe)	49.5	Age and Gender Classification using Convolutional Neural Networks
LMTCNN-2-1 (single crop, tensorflow)	44.26	Joint Estimation of Age and Gender from Unconstrained Face Images using Lightweight Multi-task CNN for Mobile Applications
Levi_Hassner CNN (single crop, tensorflow)	44.14	Age and Gender Classification using Convolutional Neural Networks

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