1 code implementation • 4 Dec 2023 • Chen Zhang, Guorong Li, Yuankai Qi, Hanhua Ye, Laiyun Qing, Ming-Hsuan Yang, Qingming Huang
To address these limitations, we propose a Dynamic Erasing Network (DE-Net) for weakly supervised video anomaly detection, which learns multi-scale temporal features.
no code implementations • CVPR 2023 • Chen Zhang, Guorong Li, Yuankai Qi, Shuhui Wang, Laiyun Qing, Qingming Huang, Ming-Hsuan Yang
Weakly supervised video anomaly detection aims to identify abnormal events in videos using only video-level labels.
1 code implementation • 26 Jul 2022 • Weidong Chen, Dexiang Hong, Yuankai Qi, Zhenjun Han, Shuhui Wang, Laiyun Qing, Qingming Huang, Guorong Li
To address this problem, we propose a multi-attention network which consists of dual-path dual-attention module and a query-based cross-modal Transformer module.
Ranked #5 on Referring Expression Segmentation on A2D Sentences
no code implementations • ICCV 2015 • Zhen Xu, Laiyun Qing, Jun Miao
Finally, the missing observation of an activity is predicted as the activity candidates provided by the auto-completion model.
no code implementations • 27 Sep 2015 • Wentao Zhu, Jun Miao, Laiyun Qing, Xilin Chen
Compared to traditional deep learning methods, the implemented feature learning method has much less parameters and is validated in several typical experiments, such as digit recognition on MNIST and MNIST variations, object recognition on Caltech 101 dataset and face verification on LFW dataset.
1 code implementation • 25 Jan 2015 • Wentao Zhu, Jun Miao, Laiyun Qing
Extreme learning machine (ELM) is an extremely fast learning method and has a powerful performance for pattern recognition tasks proven by enormous researches and engineers.