Liu, Lingqiao

Memorizing Normality to Detect Anomaly: Memory-Augmented Deep Autoencoder for Unsupervised Anomaly Detection

Gong, D., Liu, L., Le, V., Saha, B., Mansour, M. R., Venkatesh, S., & Van Den Hengel, A. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV)

Anomaly Detection Techniques and ApplicationsAdversarial Robustness in Machine Learning

Cited by 1,930

In defense of soft-assignment coding

Liu, L., Wang, L., & Liu, X. (2011) · 2011 International Conference on Computer Vision

Advanced Image and Video Retrieval TechniquesImage Retrieval and Classification Techniques

Cited by 443

Self-supervised Learning of Adversarial Example: Towards Good Generalizations for Deepfake Detection

Chen, L., Zhang, Y., Song, Y., Liu, L., & Wang, J. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Digital Media Forensic DetectionGenerative Adversarial Networks and Image Synthesis

Cited by 307

METransformer: Radiology Report Generation by Transformer with Multiple Learnable Expert Tokens

Wang, Z., Liu, L., Wang, L., & Zhou, L. (2023) · 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Multimodal Machine Learning ApplicationsArtificial Intelligence in Healthcare and Education

Cited by 184

Multi-attention Network for One Shot Learning

Wang, P., Liu, L., Shen, C., Huang, Z., Van Den Hengel, A., & Shen, H. T. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 91