Facial Recognition and Modelling on Adience Gender

Metric: Accuracy (5-fold) (higher is better)

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#	Model↕	Accuracy (5-fold)▼	Extra Data	Paper	Date↕	Code
1	MiVOLO-V2	97.39	Yes	Beyond Specialization: Assessing the Capabilitie...	2024-03-04	Code
2	ViT-hSeq	96.56	No	A Hybrid Transformer-Sequencer approach for Age ...	2024-03-19	-
3	MiVOLO-D1	96.51	Yes	MiVOLO: Multi-input Transformer for Age and Gend...	2023-07-10	Code
4	RetinaFace + ArcFace + MLP + Skip connections	90.66	Yes	Generalizing MLPs With Dropouts, Batch Normaliza...	2021-08-18	Code
5	CPG (single crop, pytorch)	89.66	Yes	Compacting, Picking and Growing for Unforgetting...	2019-10-15	Code
6	PAENet (single crop, tensorflow)	89.08	Yes	-	-	Code
7	Levi_Hassner CNN ( over-sample, caffe)	86.8	No	-	-	Code
8	Levi_Hassner CNN (single crop, caffe)	85.9	No	-	-	Code
9	LMTCNN-2-1 (single crop, tensorflow)	85.16	No	Joint Estimation of Age and Gender from Unconstr...	2018-06-06	Code
10	Levi_Hassner CNN (single crop, tensorflow)	82.52	No	-	-	Code

#1MiVOLO-V2SOTA
97.39
Accuracy (5-fold)· Extra Data· 2024-03-04
Beyond Specialization: Assessing the Capabilities of MLLMs in Age and Gender Estimation Code
#2ViT-hSeq
96.56
Accuracy (5-fold)· 2024-03-19
A Hybrid Transformer-Sequencer approach for Age and Gender classification from in-wild facial images
#3MiVOLO-D1SOTA
96.51
Accuracy (5-fold)· Extra Data· 2023-07-10
MiVOLO: Multi-input Transformer for Age and Gender Estimation Code
#4RetinaFace + ArcFace + MLP + Skip connectionsSOTA
90.66
Accuracy (5-fold)· Extra Data· 2021-08-18
Generalizing MLPs With Dropouts, Batch Normalization, and Skip Connections Code
#5CPG (single crop, pytorch)SOTA
89.66
Accuracy (5-fold)· Extra Data· 2019-10-15
Compacting, Picking and Growing for Unforgetting Continual Learning Code
#6PAENet (single crop, tensorflow)
89.08
Accuracy (5-fold)· Extra Data
No paperCode
#7Levi_Hassner CNN ( over-sample, caffe)
86.8
Accuracy (5-fold)
No paperCode
#8Levi_Hassner CNN (single crop, caffe)
85.9
Accuracy (5-fold)
No paperCode
#9LMTCNN-2-1 (single crop, tensorflow)SOTA
85.16
Accuracy (5-fold)· 2018-06-06
Joint Estimation of Age and Gender from Unconstrained Face Images using Lightweight Multi-task CNN for Mobile Applications Code
#10Levi_Hassner CNN (single crop, tensorflow)
82.52
Accuracy (5-fold)
No paperCode