Journal of Computer Applications ›› 2023, Vol. 43 ›› Issue (5): 1578-1583.DOI: 10.11772/j.issn.1001-9081.2022040606
Special Issue: 多媒体计算与计算机仿真
• Multimedia computing and computer simulation • Previous Articles Next Articles
Jianhui HE, Chunlong HU(), Xin SHU
Received:
2022-04-29
Revised:
2022-07-06
Accepted:
2022-07-07
Online:
2023-05-08
Published:
2023-05-10
Contact:
Chunlong HU
About author:
HE Jianhui, born in 1998, M. S. candidate. His research interests include computer vision, age estimation.Supported by:
通讯作者:
胡春龙
作者简介:
何建辉(1998—),男,湖南永州人,硕士研究生,主要研究方向:计算机视觉、年龄估计基金资助:
CLC Number:
Jianhui HE, Chunlong HU, Xin SHU. Multi-task age estimation method based on multi-peak label distribution learning[J]. Journal of Computer Applications, 2023, 43(5): 1578-1583.
何建辉, 胡春龙, 束鑫. 基于多峰标签分布学习的多任务年龄估计方法[J]. 《计算机应用》唯一官方网站, 2023, 43(5): 1578-1583.
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URL: https://www.joca.cn/EN/10.11772/j.issn.1001-9081.2022040606
阶段 | 层 | 卷积核 | 输出尺寸 | 参数量 |
---|---|---|---|---|
一 | Image | — | 112×112×3 | — |
Conv1 | 3×3 | 110×110×32 | 960 | |
AvgP | 2×2 | 55×55×32 | — | |
Conv2 | 3×3 | 53×53×32 | 9 312 | |
Conv3 | 3×3 | 51×51×32 | 9 312 | |
AvgP | 2×2 | 25×25×32 | — | |
二 | Conv4 | 3×3 | 23×23×64 | 18 624 |
Conv5 | 3×3 | 21×21×64 | 37 056 | |
AvgP | 2×2 | 10×10×64 | — | |
三 | Conv6 | 3×3 | 8×8×64 | 37 056 |
Conv7 | 3×3 | 6×6×64 | 37 056 | |
总计 | — | — | — | 149 376 |
Tab. 1 Lightweight feature extraction network structure
阶段 | 层 | 卷积核 | 输出尺寸 | 参数量 |
---|---|---|---|---|
一 | Image | — | 112×112×3 | — |
Conv1 | 3×3 | 110×110×32 | 960 | |
AvgP | 2×2 | 55×55×32 | — | |
Conv2 | 3×3 | 53×53×32 | 9 312 | |
Conv3 | 3×3 | 51×51×32 | 9 312 | |
AvgP | 2×2 | 25×25×32 | — | |
二 | Conv4 | 3×3 | 23×23×64 | 18 624 |
Conv5 | 3×3 | 21×21×64 | 37 056 | |
AvgP | 2×2 | 10×10×64 | — | |
三 | Conv6 | 3×3 | 8×8×64 | 37 056 |
Conv7 | 3×3 | 6×6×64 | 37 056 | |
总计 | — | — | — | 149 376 |
类型 | 方法 | 预训练集 | 参数量/103 | MAE |
---|---|---|---|---|
重量级 | DEX[ | ImageNet | 138 000 | 3.25 |
DEX[ | IMDB-WIKI | 138 000 | 2.68 | |
Posterior[ | — | 138 000 | 2.52 | |
MV[ | IMDB-WIKI | 138 000 | 2.16 | |
DLDL[ | IMDB-WIKI | 138 000 | 2.42 | |
RankingCNN[ | Audience | 500 000 | 2.96 | |
BridgeNet[ | IMDB-WIKI | 138 000 | 2.38 | |
DORFs[ | ImageNet | 138 000 | 2.19 | |
轻量级 | CEN[ | IMDB-WIKI | 11 200 | 1.91 |
LRN[ | IMDB-WIKI | 2 800 | 1.90 | |
ORCNN[ | IMDB-WIKI | 479.7 | 3.27 | |
C3AE[ | IMDB-WIKI | 39.7 | 2.75 | |
SSR-Net[ | IMDB-WIKI | 40.9 | 3.16 | |
DenseNet[ | IMDB-WIKI | 242 | 5.05 | |
MobileNet[ | IMDB-WIKI | 226.3 | 6.50 | |
MPDNet | — | 175 | 2.67 |
Tab. 2 Comparison of experimental results on MORPH Ⅱ dataset
类型 | 方法 | 预训练集 | 参数量/103 | MAE |
---|---|---|---|---|
重量级 | DEX[ | ImageNet | 138 000 | 3.25 |
DEX[ | IMDB-WIKI | 138 000 | 2.68 | |
Posterior[ | — | 138 000 | 2.52 | |
MV[ | IMDB-WIKI | 138 000 | 2.16 | |
DLDL[ | IMDB-WIKI | 138 000 | 2.42 | |
RankingCNN[ | Audience | 500 000 | 2.96 | |
BridgeNet[ | IMDB-WIKI | 138 000 | 2.38 | |
DORFs[ | ImageNet | 138 000 | 2.19 | |
轻量级 | CEN[ | IMDB-WIKI | 11 200 | 1.91 |
LRN[ | IMDB-WIKI | 2 800 | 1.90 | |
ORCNN[ | IMDB-WIKI | 479.7 | 3.27 | |
C3AE[ | IMDB-WIKI | 39.7 | 2.75 | |
SSR-Net[ | IMDB-WIKI | 40.9 | 3.16 | |
DenseNet[ | IMDB-WIKI | 242 | 5.05 | |
MobileNet[ | IMDB-WIKI | 226.3 | 6.50 | |
MPDNet | — | 175 | 2.67 |
方法 | 参数λ | MAE |
---|---|---|
回归 | 0 | 2.83 |
MPD | 1 | 2.78 |
5 | 2.75 | |
10 | 2.70 | |
15 | 2.69 | |
17 | 2.70 | |
18 | 2.67 | |
20 | 2.71 | |
高斯分布 | — | 2.78 |
Tab. 3 Ablation experimental results of parameter λ
方法 | 参数λ | MAE |
---|---|---|
回归 | 0 | 2.83 |
MPD | 1 | 2.78 |
5 | 2.75 | |
10 | 2.70 | |
15 | 2.69 | |
17 | 2.70 | |
18 | 2.67 | |
20 | 2.71 | |
高斯分布 | — | 2.78 |
类型 | 方法 | 预训练集 | CS(3)/% | CS(5)/% |
---|---|---|---|---|
重量级 | Posterior[ | IMDB-WIKI | 62.1 | 80.4 |
Posterior[ | MS-Celeb | 64.2 | 82.2 | |
轻量级 | CEN[ | IMDB-WIKI | 63.7 | 82.9 |
LRN[ | IMDB-WIKI | 64.4 | 82.9 | |
SSR-Net[ | IMDB-WIKI | 54.9 | 74.1 | |
DenseNet[ | IMDB-WIKI | 51.7 | 69.4 | |
MobileNet[ | IMDB-WIKI | 44.0 | 60.6 | |
MPDNet | IMDB-WIKI | 61.1 | 81.2 |
Tab. 4 Comparison of experimental results on MegaAge-Asian dataset
类型 | 方法 | 预训练集 | CS(3)/% | CS(5)/% |
---|---|---|---|---|
重量级 | Posterior[ | IMDB-WIKI | 62.1 | 80.4 |
Posterior[ | MS-Celeb | 64.2 | 82.2 | |
轻量级 | CEN[ | IMDB-WIKI | 63.7 | 82.9 |
LRN[ | IMDB-WIKI | 64.4 | 82.9 | |
SSR-Net[ | IMDB-WIKI | 54.9 | 74.1 | |
DenseNet[ | IMDB-WIKI | 51.7 | 69.4 | |
MobileNet[ | IMDB-WIKI | 44.0 | 60.6 | |
MPDNet | IMDB-WIKI | 61.1 | 81.2 |
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