164 citations · 502 across the 24 of their papers we have counts for
38 papers
Patch-wise Auto-Encoder for Visual Anomaly Detection
Yajie Cui, Zhaoxiang Liu, Shiguo Lian
Anomaly detection without priors of the anomalies is challenging. In the field of unsupervised anomaly detection, traditional auto-encoder (AE) tends to fail based on the assumptio…
Semi-supervised Object Detection: A Survey on Recent Research and Progress
Yanyang Wang, Zhaoxiang Liu, Shiguo Lian
In recent years, deep learning technology has been maturely applied in the field of object detection, and most algorithms tend to be supervised learning. However, a large amount of…
Application-Driven AI Paradigm for Person Counting in Various Scenarios
Minjie Hua, Yibing Nan, Shiguo Lian
Person counting is considered as a fundamental task in video surveillance. However, the scenario diversity in practical applications makes it difficult to exploit a single person c…
Data-Centric AI Paradigm Based on Application-Driven Fine-Grained Dataset Design
Huan Hu, Yajie Cui, Zhaoxiang Liu +1
Deep learning has a wide range of applications in industrial scenario, but reducing false alarm (FA) remains a major difficulty. Optimizing network architecture or network paramete…
Application-Driven AI Paradigm for Hand-Held Action Detection
Kohou Wang, Zhaoxiang Liu, Shiguo Lian
In practical applications especially with safety requirement, some hand-held actions need to be monitored closely, including smoking cigarettes, dialing, eating, etc. Taking smokin…
Application-Driven AI Paradigm for Human Action Recognition
Zezhou Chen, Yajie Cui, Kaikai Zhao +2
Human action recognition in computer vision has been widely studied in recent years. However, most algorithms consider only certain action specially with even high computational co…