1 code implementation • 16 Apr 2024 • Jiangning Zhang, Chengjie Wang, Xiangtai Li, Guanzhong Tian, Zhucun Xue, Yong liu, Guansong Pang, DaCheng Tao
Moreover, current metrics such as AU-ROC have nearly reached saturation on simple datasets, which prevents a comprehensive evaluation of different methods.
1 code implementation • 9 Apr 2024 • Haoyang He, Yuhu Bai, Jiangning Zhang, Qingdong He, Hongxu Chen, Zhenye Gan, Chengjie Wang, Xiangtai Li, Guanzhong Tian, Lei Xie
Recent advancements in anomaly detection have seen the efficacy of CNN- and transformer-based approaches.
no code implementations • 7 Mar 2024 • Yuhu Bai, Jiangning Zhang, Yuhang Dong, Guanzhong Tian, Liang Liu, Yunkang Cao, Yabiao Wang, Chengjie Wang
We consider anomaly detection as a discriminative classification problem, wherefore the dual-path feature discrimination module is employed to detect and locate the image-level and feature-level anomalies in the feature space.
no code implementations • 1 Nov 2023 • Xuhai Chen, Jiangning Zhang, Guanzhong Tian, Haoyang He, Wuhao Zhang, Yabiao Wang, Chengjie Wang, Yong liu
This paper considers zero-shot Anomaly Detection (AD), performing AD without reference images of the test objects.
no code implementations • 2 Jul 2023 • Jun Chen, Shipeng Bai, Tianxin Huang, Mengmeng Wang, Guanzhong Tian, Yong liu
In this paper, we propose a data-free mixed-precision compensation (DF-MPC) method to recover the performance of an ultra-low precision quantized model without any data and fine-tuning process.
1 code implementation • 8 Jun 2023 • Juntao Jiang, Xiyu Chen, Guanzhong Tian, Yong liu
Deep neural networks have been widely used in medical image analysis and medical image segmentation is one of the most important tasks.
1 code implementation • CVPR 2023 • Liang Liu, Boshen Zhang, Jiangning Zhang, Wuhao Zhang, Zhenye Gan, Guanzhong Tian, Wenbing Zhu, Yabiao Wang, Chengjie Wang
Despite the remarkable progress made by modern detection models, this challenge is particularly evident in the semi-supervised case.
no code implementations • 27 May 2019 • Guanzhong Tian, Yi Yuan, Yong liu
We propose an end to end deep learning approach for generating real-time facial animation from just audio.