| Understanding anomaly detection with deep invertible networks through hierarchies of distributions and features R Schirrmeister, Y Zhou, T Ball, D Zhang Advances in Neural Information Processing Systems 33, 21038-21049, 2020 | 85 | 2020 |
| Hypergraph Transformer for Skeleton-based Action Recognition Y Zhou, ZQ Cheng, C Li, Y Geng, X Xie, M Keuper arXiv preprint arXiv:2211.09590, 2022 | 31 | 2022 |
| Language Supervised Training for Skeleton-based Action Recognition W Xiang, C Li, Y Zhou, B Wang, L Zhang arXiv preprint arXiv:2208.05318, 2022 | 21 | 2022 |
| Generative Action Description Prompts for Skeleton-based Action Recognition W Xiang, C Li, Y Zhou, B Wang, L Zhang Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 10 | 2023 |
| Overcoming Topology Agnosticism: Enhancing Skeleton-Based Action Recognition through Redefined Skeletal Topology Awareness Y Zhou, ZQ Cheng, JY He, B Luo, Y Geng, X Xie arXiv preprint arXiv:2305.11468, 2023 | 7 | 2023 |
| Sp-vit: Learning 2d spatial priors for vision transformers Y Zhou, W Xiang, C Li, B Wang, X Wei, L Zhang, M Keuper, X Hua 33rd British Machine Vision Conference. BMVA Press, 2022., 2022 | 6 | 2022 |
| Device and method for anomaly detection D Zhang, RT Schirrmeister, Y Zhou US Patent App. 17/181,473, 2021 | | 2021 |
| Understanding Anomaly Detection with Deep Invertible Networks through Hierarchies of Distributions and Features R Tibor Schirrmeister, Y Zhou, T Ball, D Zhang arXiv e-prints, arXiv: 2006.10848, 2020 | | 2020 |
| Generative Action Description Prompts for Skeleton-based Action Recognition-Supplementary Material W Xiang, C Li, Y Zhou, B Wang, L Zhang | | |
| Supplementary Material Understanding Anomaly Detection with Deep Invertible Networks through Hierarchies of Distributions and Features RT Schirrmeister, Y Zhou, T Ball, D Zhang | | |
Robin Tibor SchirrmeisterPhD Candidate, Neuromedical AI Lab and Machine Learning Lab, University Freiburguniklinik-freiburg.de의 이메일 확인됨
