Related work

The foundational work on continual learning, 1959 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

11 papers of 11,817Sort Recent · Most cited
  1. 2025
    Invariant prompting with classifier rectification for continual learningChu-Ping Lo, H. Zhang, Andy J. MaImage and Vision Computing
  2. 2025
    Memory augmented using diffusion model for class-incremental learningQuentin Jodelet, Xin Liu, Yin Jun Phua, Tsuyoshi MurataImage and Vision Computing
  3. 2025
    Exemplar-free class incremental action recognition based on self-supervised learningChun-Yu Hou, Yong-Hong Hou, Jin-Yi Jiang, Günel AbdullayevaImage and Vision Computing
  4. 2024
    Background debiased class incremental learning for video action recognitionL. Nguyen, Jin-Woo Choi, L. Dang, Hyeonjoon MoonImage and Vision Computing
  5. 2024
    Few-shot class incremental learning via prompt transfer and knowledge distillationFeidu Akmel, Fanman Meng, Mingyu Liu … Elias LemuyeImage and Vision Computing
  6. 2024
  7. 2021
    Generative feature-driven image replay for continual learningKevin Thandiackal, Tiziano Portenier, Andrea Giovannini … Orçun GökselImage and Vision Computing · ETH Zurich · IBM Research - Zurich · +1
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  8. 2023
    RECALL+: Adversarial Web-based Replay for Continual Learning in Semantic SegmentationChang Liu, Giulia Rizzoli, Francesco Barbato … P. ZanuttighImage and Vision Computing
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  9. 2021
    Incremental human action recognition with dual memoryMatheus Gutoski, André Eugênio Lazzaretti, Heitor Silvério LopesImage and Vision Computing · Universidade Tecnológica Federal do Paraná
  10. 2021
    Task-based parameter isolation for foreground segmentation without catastrophic forgetting using multi-scale region and edges fusion networkIslam Osman, Agwad ElTantawy, Mohamed ShehataImage and Vision Computing · University of British Columbia · University of British Columbia, Okanagan Campus · +1
  11. 2020
    Cuepervision: self-supervised learning for continuous domain adaptation without catastrophic forgettingMark Schutera, Frank M. Hafner, Jochen Abhau … Markus ReischlImage and Vision Computing · Karlsruhe Institute of Technology · ZF Friedrichshafen (Germany)
About this index

We keep this list because we read the field and wanted one place to see it. It covers work on continual learning itself, in the core areas of machine learning, and leaves out papers that apply it inside another field, such as medical imaging or fault diagnosis. It is seeded from the community lists kept by ContinualAI and by Xialei Liu, then filled out from OpenAlex, and every week a script looks for new papers on OpenAlex and arXiv. A model reads each candidate and decides whether it belongs; a person reviews the additions before they go live. Authors and affiliations come from OpenAlex, so a recent preprint can lack its institutions for a week or two.

Missing something, or filed under the wrong venue? Write to hello@unify.ai with the arXiv id or DOI.