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This is the offical implementation for the paper titled "TextFusion: Unveiling the Power of Textual Semantics for Controllable Image Fusion".

active 2024-01-082026-01-04 (UTC)

Complete coverage26,469 / 26,469 hourly files (100%) · 2 absent upstream2023-08-152026-08-21 (UTC)
Events
114
Pushes
47
Pull requests
0
Issues
15
Stars
36
Forks
1

Activity over time

Daily event counts in the loaded window

Line chart, 728 days from 2024-01-08 to 2026-01-04. Pushes: 47 total, peak 20 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 15 total, peak 2 in a day. Comments: 13 total, peak 2 in a day. Stars: 36 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
AWCXV604708
Britajin5001
nanakoMI3002
songwenhao1232001
Nine52541001
mm1112221000
xiaocheng12131000
Liulong-Aliang1000
yujiasunwp1000

Recent activity

Latest issues, pull requests and releases

  • Issue#7xiaocheng12132025-08-27 10:53
    training problem
  • Issue comment#6Britajin2025-04-16 05:55
    coarse to fine association代码
  • Issue#6Britajin2025-04-16 05:54
    coarse to fine association代码
  • Issue#6Britajin2025-04-16 05:54
    coarse to fine association代码
  • Issue#6Britajin2025-03-31 03:12
    coarse to fine association代码
  • Issue comment#6AWCXV2025-03-28 06:15
    coarse to fine association代码
  • Issue#6Britajin2025-03-27 11:41
    coarse to fine association代码
  • Issue comment#4AWCXV2025-01-04 01:50
    textual attention assessment
  • Issue#4AWCXV2025-01-04 01:50
    textual attention assessment
  • Issue comment#5AWCXV2025-01-04 01:49
    metric
  • Issue#5AWCXV2025-01-04 01:49
    metric
  • Issue comment#5nanakoMI2025-01-03 08:20
    metric
  • Issue comment#5AWCXV2024-12-25 02:41
    metric
  • Issue comment#5nanakoMI2024-12-11 01:29
    metric
  • Issue#5nanakoMI2024-12-11 01:28
    metric
  • Issue comment#4AWCXV2024-09-29 15:57
    textual attention assessment
  • Issue#4mm1112222024-09-29 13:39
    textual attention assessment
  • Issue#3AWCXV2024-06-30 18:13
    LLVIP测试集目标检测Label
  • Issue comment#3songwenhao1232024-06-30 00:38
    LLVIP测试集目标检测Label
  • Issue comment#3AWCXV2024-06-29 13:40
    LLVIP测试集目标检测Label
  • Issue#3songwenhao1232024-06-29 07:33
    LLVIP测试集目标检测Label
  • Issue#2AWCXV2024-05-26 12:37
    关于Train Set [Images&Text]:
  • Issue comment#2AWCXV2024-05-26 10:39
    关于Train Set [Images&Text]:
  • Issue#2yujiasunwp2024-05-25 04:18
    关于Train Set [Images&Text]:
  • Issue#1AWCXV2024-03-15 09:32
    How to train the model?

Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 36 stars here means stars gained during the window, not the repo's star count.