Knowledge Commons of Institute of Automation,CAS
Cascaded Split-and-Aggregate Learning with Feature Recombination for Pedestrian Attribute Recognition | |
Yang, Yang1,2; Tan, Zichang4,5![]() ![]() ![]() ![]() | |
发表期刊 | INTERNATIONAL JOURNAL OF COMPUTER VISION
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ISSN | 0920-5691 |
2021-07-18 | |
页码 | 14 |
摘要 | Multi-label pedestrian attribute recognition in surveillance is inherently a challenging task due to poor imaging quality, large pose variations, and so on. In this paper, we improve its performance from the following two aspects: (1) We propose a cascaded Split-and-Aggregate Learning (SAL) to capture both the individuality and commonality for all attributes, with one at the feature map level and the other at the feature vector level. For the former, we split the features of each attribute by using a designed attribute-specific attention module (ASAM). For the later, the split features for each attribute are learned by using constrained losses. In both modules, the split features are aggregated by using several convolutional or fully connected layers. (2) We propose a Feature Recombination (FR) that conducts a random shuffle based on the split features over a batch of samples to synthesize more training samples, which spans the potential samples' variability. To the end, we formulate a unified framework, named CAScaded Split-and-Aggregate Learning with Feature Recombination (CAS-SAL-FR), to learn the above modules jointly and concurrently. Experiments on five popular benchmarks, including RAP, PA-100K, PETA, Market-1501 and Duke attribute datasets, show the proposed CAS-SAL-FR achieves new state-of-the-art performance. |
关键词 | Pedestrian attribute recognition Attention Split-and-aggregate learning Feature recombination |
DOI | 10.1007/s11263-021-01499-z |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Key Research and Development Program[2020YFC2003901] ; Chinese National Natural Science Foundation[61806203] ; Chinese National Natural Science Foundation[61961160704] ; Chinese National Natural Science Foundation[61876179] ; External cooperation key project of Chinese Academy Sciences[173211KYSB20200002] ; Key Project of the General Logistics Department[AWS17J001] ; Science and Technology Development Fund of Macau[0010/2019/AFJ] ; Science and Technology Development Fund of Macau[0025/2019/AKP] ; Science and Technology Development Fund of Macau[0019/2018/ASC] ; Spanish project (MINECO/FEDER, UE)[TIN2016-74946-P] ; CERCA Programme/Generalitat de Catalunya ; Academy of Finland[336033] ; Academy of Finland[315896] ; Business Finland[884/31/2018] ; EU[101016775] |
项目资助者 | National Key Research and Development Program ; Chinese National Natural Science Foundation ; External cooperation key project of Chinese Academy Sciences ; Key Project of the General Logistics Department ; Science and Technology Development Fund of Macau ; Spanish project (MINECO/FEDER, UE) ; CERCA Programme/Generalitat de Catalunya ; Academy of Finland ; Business Finland ; EU |
WOS研究方向 | Computer Science |
WOS类目 | Computer Science, Artificial Intelligence |
WOS记录号 | WOS:000674202900001 |
出版者 | SPRINGER |
是否为代表性论文 | 否 |
七大方向——子方向分类 | 图像视频处理与分析 |
国重实验室规划方向分类 | 人工智能基础前沿理论 |
是否有论文关联数据集需要存交 | 否 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/45512 |
专题 | 多模态人工智能系统全国重点实验室_生物识别与安全技术 |
通讯作者 | Wan, Jun |
作者单位 | 1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Ctr Biometr & Secur Res, Beijing, Peoples R China 2.Univ Chinese Acad Sci UCAS, Sch Artificial Intelligence, Beijing, Peoples R China 3.Chinese Acad Sci, Hong Kong Inst Sci & Innovat, Ctr Artificial Intelligence & Robot, Hong Kong, Peoples R China 4.Baidu Res, Inst Deep Learning, Beijing, Peoples R China 5.Natl Engn Lab Deep Learning Technol & Applicat, Beijing, Peoples R China 6.Aalto Univ, Dept Comp Sci, Espoo, Finland 7.Edge Hill Univ, Dept Comp Sci, Ormskirk, England |
第一作者单位 | 模式识别国家重点实验室 |
通讯作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Yang, Yang,Tan, Zichang,Tiwari, Prayag,et al. Cascaded Split-and-Aggregate Learning with Feature Recombination for Pedestrian Attribute Recognition[J]. INTERNATIONAL JOURNAL OF COMPUTER VISION,2021:14. |
APA | Yang, Yang.,Tan, Zichang.,Tiwari, Prayag.,Pandey, Hari Mohan.,Wan, Jun.,...&Li, Stan Z..(2021).Cascaded Split-and-Aggregate Learning with Feature Recombination for Pedestrian Attribute Recognition.INTERNATIONAL JOURNAL OF COMPUTER VISION,14. |
MLA | Yang, Yang,et al."Cascaded Split-and-Aggregate Learning with Feature Recombination for Pedestrian Attribute Recognition".INTERNATIONAL JOURNAL OF COMPUTER VISION (2021):14. |
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