Browse State-of-the-Art › Online unsupervised domain adaptation
Online unsupervised domain adaptation
3 papers with code · 0 benchmarks · 0 datasets archive 2025-07-28
Benchmarks archive 2025-07-28
No benchmark for this task in the archive.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
No dataset record in the archive lists this task.
Subtasks archive 2025-07-28
No subtask under this task in the archive's task tree.
Parent tasks archive 2025-07-28
Most implemented papers archive 2025-07-28
3 shown of 3 papers with code (8 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.
-
20 Jul 2022 2 repositories listedOur experiments show the effectiveness of our segmentation approach on thousands of real-world point clouds.
-
23 Feb 2024 1 repository listedOur framework is based on the extraction of a support set composed of source images that maximizes the similarity with the target data.
-
4 Oct 2021 1 repository listedWe consider the problem of online unsupervised cross-domain adaptation, where two independent but related data streams with different feature spaces -- a fully labeled source stream and an unlabeled target stream -- are…
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections