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TonyLianLong/UnsupervisedSelectiveLabeling

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[ECCV 2022] Official Implementation for Unsupervised Selective Labeling for More Effective Semi-Supervised Learning

active 2023-10-272025-09-28 (UTC)

Partial coverage19,132 / 24,635 hourly files (78%) · 2 absent upstream · 5,500 failed, retryable2023-10-212026-08-12 (UTC)— sampled evenly across the window, so rankings and trends hold; absolute counts scale up.
Events
20
Pushes
0
Pull requests
0
Issues
5
Stars
13
Forks
1

Activity over time

Daily event counts in the loaded window

Line chart, 703 days from 2023-10-27 to 2025-09-28. Pushes: 0 total, peak 0 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 5 total, peak 1 in a day. Comments: 1 total, peak 1 in a day. Stars: 13 total, peak 1 in a day.

  • Pushes
  • Pull requests
  • Issues
  • Comments
  • Stars

Stars, PRs, issues and forks are under-captured in the later part of this window. GH Archive progressively stopped capturing non-push events during 2026 — −95% or worse by the end of the window. Every series here except Pushes fades for that reason, so a decline above reflects the archive, not this repository. Pushes stay reliable throughout, so read them, and the contributor counts derived from them, as the real signal. Data health has the measurements.

Top contributors

Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity

ContributorContributionsPushesPRsComments
TonyLianLong2001
5p61000
Tristan-Liu-131000
panxingyu6661000
lsyqlelel1000

Recent activity

Latest issues, pull requests and releases

  • Issue#105p62024-10-27 08:36
    Dependencies Version
  • Issue#9panxingyu6662024-03-27 07:31
    Can this method be applied to your own dataset?
  • Issue#7Tristan-Liu-132024-01-30 07:46
    Coreset baseline
  • Issue comment#6TonyLianLong2023-12-12 19:42
    Bug for Evaluate USL-T on CIFAR-10 on SimCLR-CLD
  • Issue#6TonyLianLong2023-12-12 19:42
    Bug for Evaluate USL-T on CIFAR-10 on SimCLR-CLD
  • Issue#5lsyqlelel2023-10-27 09:26
    Can this method be modified for semantic segmentation?

Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 13 stars here means stars gained during the window, not the repo's star count.