Large-Scale Logo Detection

doi:10.1109/TPAMI.2025.3630505

CSpace

	Large-Scale Logo Detection
	Hou, Sujuan 1,2; Li, Jiacheng 1; Min, Weiqing 3; Zhan, Jianxin 1; Zhang, Mengmeng 2; Li, Peng 1; Jiang, Shuqiang 3
	2026-03-01
发表期刊	IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
ISSN	0162-8828
卷号	48 期号:3 页码:2919-2935
摘要	Logo detection is crucial for trademark compliance and media monitoring, enabling companies to monitor online trademark usage and evaluate brand visibility on social media and advertisements. The use of large datasets significantly improves accuracy and generalization, emphasizing the need for high-quality datasets to optimize performance and enhance reasoning abilities in visual detection models. This drove us to create Logo4500, an unparalleled dataset featuring 4,500 logo categories and over 293,000 meticulously labeled images. To ensure the dataset's quality, we meticulously designed the construction and annotation process, with detailed information provided in our paper. Compared to existing logo datasets, Logo4500 offers greater diversity and class imbalance, making it more reflective of real-world distribution. Leveraging this high-quality dataset, we introduce a benchmark called Frequency-Aware Learnable Dual Reweighting Network (FALDR-Net), which enhances the representation of ambiguous features and addresses class imbalance for large-scale logo detection. We conducted extensive experiments, evaluating various recent methods on this new dataset and several existing publicly available logo datasets, demonstrating its effectiveness. Additionally, we verified Logo4500's generalization ability in several tasks. We anticipate that Logo4500 and the benchmark will inspire further exploration in the logo-related research community, facilitating the advancement of visual foundation models.
关键词	Benchmark testing Training Visualization Annotations Deep learning Videos Transformers Monitoring Feature extraction Detectors Logo detection large-scale dataset deep learning
DOI	10.1109/TPAMI.2025.3630505
收录类别	SCI
语种	英语
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号	WOS:001680997300040
出版者	IEEE COMPUTER SOC
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/42794
专题	中国科学院计算技术研究所
通讯作者	Hou, Sujuan; Min, Weiqing; Zhang, Mengmeng
作者单位	1.Shandong Normal Univ, Sch Informat Sci & Engn, Jinan 250358, Peoples R China 2.Beijing Union Univ, Beijing 100101, Peoples R China 3.Chinese Acad Sci, Key Lab Intelligent Informat Proc, Inst Comp Technol, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Hou, Sujuan,Li, Jiacheng,Min, Weiqing,et al. Large-Scale Logo Detection[J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,2026,48(3):2919-2935.
APA	Hou, Sujuan.,Li, Jiacheng.,Min, Weiqing.,Zhan, Jianxin.,Zhang, Mengmeng.,...&Jiang, Shuqiang.(2026).Large-Scale Logo Detection.IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,48(3),2919-2935.
MLA	Hou, Sujuan,et al."Large-Scale Logo Detection".IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 48.3(2026):2919-2935.