Online Domain Adaptation

Description from the archive archive 2025-07-28.

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Most implemented papers archive 2025-07-28

5 shown of 5 papers with code (14 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• ATL: Autonomous Knowledge Transfer from Many Streaming Processes
  8 Oct 2019 2 repositories listed
  It automatically evolves its network structure from scratch with/without the presence of ground truth to overcome independent concept drifts in the source and target domain.
• To Adapt or Not to Adapt? Real-Time Adaptation for Semantic Segmentation
  27 Jul 2023 1 repository listed Syntology ran 5 of 5 samples · 0 unverified · 5 pointer-only (licence)
  The goal of Online Domain Adaptation for semantic segmentation is to handle unforeseeable domain changes that occur during deployment, like sudden weather events.
• Online Domain Adaptation for Semantic Segmentation in Ever-Changing Conditions
  21 Jul 2022 1 repository listed Syntology ran 16 of 21 samples · 5 unverified · 21 pointer-only (licence)
  Unsupervised Domain Adaptation (UDA) aims at reducing the domain gap between training and testing data and is, in most cases, carried out in offline manner.
• Automatic Online Multi-Source Domain Adaptation
  5 Sep 2021 1 repository listed
  Knowledge transfer across several streaming processes remain challenging problem not only because of different distributions of each stream but also because of rapidly changing and never-ending environments of data…
• Online Domain Adaptation for Occupancy Mapping
  1 Jul 2020 1 repository listed
  Further, with the use of high-fidelity driving simulators and real-world datasets, we demonstrate how parameters of 2D and 3D occupancy maps can be automatically adapted to accord with local spatial changes.

Syntology lines on 2 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.