Related work

The foundational work on continual learning, 1980 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

6 papers of 8,653Sort Recent · Most cited
  1. 2026
    Adaptive Continual Learning for Online Visual Object Tracking via Dynamic Grassmannian Appearance ModelingJinglin Zhou, Tianyang Xu, Xuefeng Zhu … Josef KittlerIEEE TCSVT · Jiangnan University · University of Surrey
  2. 2025
    Serial Over Parallel: Learning Continual Unification for Multi-Modal Visual Object Tracking and BenchmarkingZhangyong Tang, Tianyang Xu, Xuefeng Zhu … Josef KittlerACM International Conference on Multimedia · Jiangnan University · Nanjing University of Science and Technology · +1
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  3. 2022
    Doodle It Yourself: Class Incremental Learning by Drawing a Few SketchesAyan Kumar Bhunia, Viswanatha Reddy Gajjala, Subhadeep Koley … Yi-Zhe SongCVPR · University of Surrey · IFlyTek (China)
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  4. 2021
    Continual Learning Using Bayesian Neural NetworksHonglin Li, Payam Barnaghi, Shirin Enshaeifar, Frieder GanzTNNLS · University of Surrey · UK Dementia Research Institute · +1
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  5. 2020
    Incremental Few-Shot Object DetectionJuan-Manuel Pérez-Rúa, Xiatian Zhu, Timothy M. Hospedales, Tao XiangCVPR · Samsung (United Kingdom) · University of Edinburgh · +1
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  6. 2016
    One-Class to Multi-Class Model Update Using the Class-Incremental Optimum-Path Forest ClassifierMateus Riva, Moacir Antonelli Ponti, de Campos TeofiloFrontiers · Universidade de São Paulo · University of Surrey
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. By default it shows the papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or written by someone who has published there, or cited a few hundred times. The rest are one click away under “All papers”. 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.