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Source code for "Online Unsupervised Domain Adaptation for Semantic Segmentation in Ever-Changing Conditions", ECCV 2022. This is the code has been implemented to perform training and evaluation of UDA approaches in continuous scenarios. The library has been implemented in PyTorch 1.7.1. Some newer versions should work as well.

active 2023-09-122024-09-28 (UTC)

Complete coverage26,550 / 26,550 hourly files (100%) · 2 absent upstream2023-08-152026-08-25 (UTC)
Events
15
Pushes
1
Pull requests
0
Issues
5
Stars
6
Forks
0

Activity over time

Daily event counts in the loaded window

Line chart, 383 days from 2023-09-12 to 2024-09-28. Pushes: 1 total, peak 1 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 5 total, peak 2 in a day. Comments: 2 total, peak 2 in a day. Stars: 6 total, peak 2 in a day.

  • Pushes
  • Pull requests
  • Issues
  • Comments
  • Stars

Top contributors

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

ContributorContributionsPushesPRsComments
theo20215101
Sumanth1810993001

Recent activity

Latest issues, pull requests and releases

  • Issue#3theo20212024-06-11 17:54
    Question about Equ. (2)
  • Issue#5theo20212024-06-11 17:52
    How to get pretrained source model for DeepLabV3 plus along with first 10 epochs prototype?
  • Issue#4theo20212024-01-04 11:55
    Cannot reproduce the results of Table 1(a) for OnDA-Hybrid Switch for 200mm rain condition
  • Issue comment#4Sumanth1810992024-01-04 11:51
    Cannot reproduce the results of Table 1(a) for OnDA-Hybrid Switch for 200mm rain condition
  • Issue comment#4theo20212024-01-04 11:07
    Cannot reproduce the results of Table 1(a) for OnDA-Hybrid Switch for 200mm rain condition
  • Issue#5Sumanth1810992024-01-04 10:25
    How to get pretrained source model for DeepLabV3 plus along with first 10 epochs prototype?
  • Issue#4Sumanth1810992023-12-28 09:48
    Cannot reproduce the results of Table 1(a) for OnDA-Hybrid Switch for 200mm rain condition

Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 6 stars here means stars gained during the window, not the repo's star count.