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Unofficial implementation of "(ICCV'23) Learning to Upsample by Learning to Sample"

active 2024-02-132026-04-04 (UTC)

Partial coverage17,214 / 22,005 hourly files (78%) · 2 absent upstream · 4,791 failed, retryable2024-02-072026-08-12 (UTC)— sampled evenly across the window, so rankings and trends hold; absolute counts scale up.
Events
118
Pushes
5
Pull requests
0
Issues
13
Stars
82
Forks
4

Activity over time

Daily event counts in the loaded window

Line chart, 782 days from 2024-02-13 to 2026-04-04. Pushes: 5 total, peak 4 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 13 total, peak 5 in a day. Comments: 14 total, peak 3 in a day. Stars: 82 total, peak 2 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
poppuppy19507
honghess3001
AliasChenYi3002
Prown6662000
Zhangyucong02102002
swjtunb1001
2001luo1000
kk25651001

Recent activity

Latest issues, pull requests and releases

  • Issue comment#22poppuppy2025-08-21 14:04
    fix a bug
  • Issue#11poppuppy2025-03-12 04:17
    Is there a version for 3D images?
  • Issue#14poppuppy2025-03-12 04:17
    Change feature dim
  • Issue comment#19kk25652025-03-12 02:30
    The results of each run are inconsistent
  • Issue comment#19swjtunb2025-03-09 02:52
    The results of each run are inconsistent
  • Issue comment#17poppuppy2024-11-08 02:14
    Why do I replace the deconvolution of the decoder with Dysample(lp) during training? The GPU memory overhead is even greater,From the original 17GB to 22GB
  • Issue#15Prown6662024-11-08 02:11
    Can feature scale upsampling be singular before and after, such as x1=(1, 64, 80, 45) x2=(1, 64, 40, 23)
  • Issue comment#15poppuppy2024-11-03 08:55
    Can feature scale upsampling be singular before and after, such as x1=(1, 64, 80, 45) x2=(1, 64, 40, 23)
  • Issue#162001luo2024-10-29 02:11
    提问
  • Issue#15Prown6662024-10-20 07:46
    Can feature scale upsampling be singular before and after, such as x1=(1, 64, 80, 45) x2=(1, 64, 40, 23)
  • Issue comment#14poppuppy2024-09-04 02:12
    Change feature dim
  • Issue comment#13poppuppy2024-08-19 05:17
    Can this method be included when converting the model to ONNX format and running it on OpenCV?
  • Issue#10poppuppy2024-06-29 14:26
    The model structure is inconsistent with the code description
  • Issue#8poppuppy2024-06-29 14:25
    Hi, I am getting the following error after I introduced DySample to the network and would like to hear from you.
  • Issue#7poppuppy2024-06-29 14:25
    dysample channel
  • Issue#6poppuppy2024-06-29 14:25
    pl和lp
  • Issue#5poppuppy2024-06-29 14:25
    onnx export
  • Issue comment#10poppuppy2024-06-21 11:27
    The model structure is inconsistent with the code description
  • Issue comment#10AliasChenYi2024-06-21 06:02
    The model structure is inconsistent with the code description
  • Issue comment#10AliasChenYi2024-06-21 06:00
    The model structure is inconsistent with the code description
  • Issue#10AliasChenYi2024-06-21 06:00
    The model structure is inconsistent with the code description
  • Issue#9honghess2024-04-22 02:00
    (pl+8)速度确实比双线性插值快
  • Issue comment#9honghess2024-04-21 09:51
    (pl+8)速度确实比双线性插值快,但是对精度的损害太高了,所需显存和3d性能也有少量和大量的增幅
  • Issue#9honghess2024-04-21 09:26
    (pl+8)速度确实比双线性插值快,但是对精度的损害太高了,所需显存和3d性能也有少量和大量的增幅
  • Issue comment#8poppuppy2024-04-03 06:49
    Hi, I am getting the following error after I introduced DySample to the network and would like to hear from you.

Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 82 stars here means stars gained during the window, not the repo's star count.