Yaoyao Liu

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Yaoyao Liu

 https://orcid.org/0000-0002-5316-3028
  • 10 Conference contribution
  • 6 Article
  • 2 Conference article
  • 1 Paper
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  • 2024

    iNeMo: Incremental Neural Mesh Models for Robust Class-Incremental Learning

    Fischer, T., Liu, Y., Jesslen, A., Ahmed, N., Kaushik, P., Wang, A., Yuille, A. L., Kortylewski, A. & Ilg, E., 2024, Computer Vision – ECCV 2024 - 18th European Conference, Proceedings. Leonardis, A., Ricci, E., Roth, S., Russakovsky, O., Sattler, T. & Varol, G. (eds.). Springer, p. 357-374 18 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 15135 LNCS).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Wakening Past Concepts without Past Data: Class-Incremental Learning from Online Placebos

    Liu, Y., Li, Y., Schiele, B. & Sun, Q., Jan 3 2024, Proceedings - 2024 IEEE Winter Conference on Applications of Computer Vision, WACV 2024. Institute of Electrical and Electronics Engineers Inc., p. 2215-2224 10 p. (Proceedings - 2024 IEEE Winter Conference on Applications of Computer Vision, WACV 2024).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

    Open Access
  • 2023

    Class-Incremental Exemplar Compression for Class-Incremental Learning

    Luo, Z., Liu, Y., Schiele, B. & Sun, Q., 2023, Proceedings - 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2023. IEEE Computer Society, p. 11371-11380 10 p. (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition; vol. 2023-June).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

    Open Access

  • Continual Detection Transformer for Incremental Object Detection

    Liu, Y., Schiele, B., Vedaldi, A. & Rupprecht, C., 2023, Proceedings - 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2023. IEEE Computer Society, p. 23799-23808 10 p. (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition; vol. 2023-June).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

    Open Access

  • Continual Learning for Abdominal Multi-organ and Tumor Segmentation

    Zhang, Y., Li, X., Chen, H., Yuille, A. L., Liu, Y. & Zhou, Z., 2023, Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 - 26th International Conference, Proceedings. Greenspan, H., Madabhushi, A., Mousavi, P., Salcudean, S., Duncan, J., Syeda-Mahmood, T. & Taylor, R. (eds.). Springer, p. 35-45 11 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 14221 LNCS).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Online Hyperparameter Optimization for Class-Incremental Learning

    Liu, Y., Li, Y., Schiele, B. & Sun, Q., Jun 27 2023, AAAI-23 Technical Tracks 7. Williams, B., Chen, Y. & Neville, J. (eds.). American Association for Artificial Intelligence (AAAI) Press, p. 8906-8913 8 p. (Proceedings of the 37th AAAI Conference on Artificial Intelligence, AAAI 2023; vol. 37).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • 2021

    Adaptive Aggregation Networks for Class-Incremental Learning

    Liu, Y., Schiele, B. & Sun, Q., 2021, Proceedings - 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2021. IEEE Computer Society, p. 2544-2553 10 p. (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

    Open Access

  • RMM: Reinforced Memory Management for Class-Incremental Learning

    Liu, Y., Schiele, B. & Sun, Q., 2021, Advances in Neural Information Processing Systems 34 - 35th Conference on Neural Information Processing Systems, NeurIPS 2021. Ranzato, M., Beygelzimer, A., Dauphin, Y., Liang, P. S. & Wortman Vaughan, J. (eds.). Neural information processing systems foundation, p. 3478-3490 13 p. (Advances in Neural Information Processing Systems; vol. 5).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • 2020

    An Ensemble of Epoch-Wise Empirical Bayes for Few-Shot Learning

    Liu, Y., Schiele, B. & Sun, Q., 2020, Computer Vision – ECCV 2020 - 16th European Conference, Proceedings. Vedaldi, A., Bischof, H., Brox, T. & Frahm, J.-M. (eds.). Springer, p. 404-421 18 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12361 LNCS).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

    Open Access
  • 2019

    Meta-transfer learning for few-shot learning

    Sun, Q., Liu, Y., Chua, T. S. & Schiele, B., Jun 2019, Proceedings - 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2019. IEEE Computer Society, p. 403-412 10 p. 8954051. (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition; vol. 2019-June).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

    Open Access