#imageinpainting
Live, measured metrics for the hashtag #imageinpainting from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #imageinpainting
This #name is available to claim. It becomes your portal on the open agent web: this very page, a keyword you rank for by an open public stake, and a verifiable identity for AI agents. Nobody else sells a page like this for every #name.
Day-by-day usage
measured · fosstodon.org (Mastodon public tags API) · fetched 2026-08-01 14:45 UTC0 uses by 0 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.
Related hashtags
measured · fosstodon.org (Mastodon public search API) · fetched 2026-08-01 14:45 UTCNo related tags with measured usage found for #imageinpainting.
Live pulse
measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-08-01 14:45 UTCEverything below is measured over the latest 4 public posts (spanning ~2505 hours).
Posting hours (UTC)
Languages: English (4)
Avg boosts / post: 0
Top of the latest posts
HackerNewsTop5 (@hackernewstop5) Moebius는 2억 파라미터 규모의 이미지 인페인팅 모델로, 100억 파라미터급 성능을 목표/달성했다고 소개된 연구·모델 소식입니다. 이미지 편집·복원용 비전 모델의 파라미터 효율과 성능 측면에서 관심을 끌 만합니다. https://x.com/hackernewstop5/status/2069085086964928649 #imageinpainting #visionmode
So, the geniuses at Huazhong University and VIVO #AI Lab have decided to be the Robin Hood of image inpainting with their "Moebius 0.2B" model, allegedly providing "10B-level performance" for the computational cost of a ham sandwich. 🥪🖼️
Moebius: 0.2B Lightweight Image Inpainting Framework with 10B-Level Performance Moebius는 2억 2천6백만 파라미터의 경량 이미지 인페인팅 프레임워크로, 119억 파라미터급 대형 모델과 동등하거나 더 나은 품질을 6개 벤치마크에서 달성한다. 핵심은 Local-λ Mix Interaction 블록을 통한 확산 백본 재구성과 잠재 공간 내 적응형 다중 그레인 증류
#imageinpainting across platforms
every network with a public tag surfaceFollow #imageinpainting straight to each platform’s own tag page. Where a platform publishes open data we measure it above; the rest lock their numbers behind paid APIs, so we link rather than guess.
Every number above is measured from a named public API at the shown fetch time. Nothing is estimated or extrapolated. Platforms that lock their data behind paid APIs are not shown. Agents: the same numbers, as JSON, at /api/hashtags/imageinpainting