Yingjun Zhang — accepted AI-conference papers

2026

TLMA: Mitigating the Impact of Weakly Labeled Information for Video Anomaly Detection

Rong Xu, Runqi Wang, Yingjun Zhang, Tao Tao, Xiaomeng Li, Liping Jing

CVPR 2026

Weakly Supervised Video Anomaly Detection (WSVAD) aims to localize abnormal segments using only video-level labels during training.Although the paradigm significantly reduces annotation costs, the coarse-grained labels fail to precisely describe the full videos, resulting in the introduction of subs

Cited by 0 Source ↗Scholar ↗

2024

MapCVV: On-Cloud Map Construction Using Crowdsourcing Visual Vectorized Elements Towards Autonomous Driving

Pengxin Chen, Xiaoqi Jiang, Yingjun Zhang, Jiahao Tan, Rong Jiang

RA-L 2024

Maps are indispensable foundation for autonomous driving to provide prior knowledge of road structures. Constructing maps in a crowdsourcing manner has been a research hotspot in order to achieve lower map production cost and higher update frequency. Existing pipelines of crowdsourcing mapping const

Cited by 7 Source ↗Scholar ↗