Channel
@SHARE3DCAM_Russia
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
78subscribers
+3 since we began measuring on 31 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1003786318791 |
|---|---|
| Type | Channel |
| Username | @SHARE3DCAM_Russia |
| Created | 12 June 2026 — measured — dated from the channel’s first post |
| First recorded | 31 August 2026 |
| Last confirmed live | 12 October 2026 |
| Measurements held | 4 |
| Confirmed unchanged | 2 times, most recently 12 October 2026 |
| On Telegram | t.me/SHARE3DCAM_Russia |
Technology — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 2 October 2026 and assigned it the closest of 31 fixed categories, at 96% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 2 Oct 2026, 06:38 | 78 | +2 |
| 9 Sept 2026, 23:38 | 76 | +1 |
| 31 Aug 2026, 04:15 | 75 | no change |
| 31 Aug 2026, 04:00 | 75 | first reading |
11 posts held, back to 12 June 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 page of Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 11 posts for this entry, the most recent from 9 July 2026. An engagement rate over an empty window would be a number about nothing.
Measured directly from 5 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.
13 reactions across 5 posts, in 3 distinct kinds. The most used accounts for 53.8% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 🔥 | 7 | 53.8% | |
| ❤ | 3 | 23.1% | |
| 👍 | 3 | 23.1% |
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 5 of the 11 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 13 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 11 most recent posts we hold, published 12 June 2026 to 9 July 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
Где можно применять SHARE SLAM В этом видео мы показываем практические сценарии использования портативных 3D-лазерных сканеров SHARE SLAM — от строительных объектов и AEC-задач до пространственной документации, тоннелей и измерения объёмов складских запасов. С помощью мобильного SLAM LiDAR-сканирования реальные условия на объекте можно быстро преобразовать в облако точек, которое затем используется для: • визуализ…
🔥2
SHARE3DCAM Россия pinned «Мы открыли официальное сообщество SHARE3DCAM в России! 👋 Теперь вы можете задать вопросы по SHARE SLAM S20 и S100, программному обеспечению, облакам точек, 3DGS, CAD/BIM-процессам и тестированию оборудования. В сообществе можно: • получить техническую поддержку;…»
Мы открыли официальное сообщество SHARE3DCAM в России! 👋 Теперь вы можете задать вопросы по SHARE SLAM S20 и S100, программному обеспечению, облакам точек, 3DGS, CAD/BIM-процессам и тестированию оборудования. В сообществе можно: • получить техническую поддержку; • обсудить обработку данных и рабочие процессы; • поделиться своим проектом или результатами сканирования; • узнать больше о продуктах SHARE и возможностях…
❤3🔥2
Posted without readable text
Коммерческие пространства быстро меняются, а ручные обмеры не всегда позволяют зафиксировать все важные детали.😢😢 С SHARE SLAM S20 объект коммерческого fit-out был отсканирован примерно за 6 минут. Затем данные были обработаны в виде облака точек для проверки фактических условий и подготовки CAD-чертежей. Один скан — меньше недостающих данных, меньше повторных выездов и более уверенная подготовка проекта.😄😄 #SHARE…
От облака точек — к редактируемой BIM-модели. ⚡️ Лазерное сканирование — это не только быстрый способ зафиксировать пространство, но и основа для дальнейшей работы в BIM.☺️☺️ В этом ролике показан рабочий процесс на основе данных, собранных сканером SHARE: • быстрое сканирование помещения; • получение облака точек; • распознавание пространства с помощью плагина; • создание отчёта о плоскостности на основе облака то…
👍3
Сканирование крупного коммерческого комплекса — всего за считанные минуты. ❤️❤️ SHARE S20 позволяет работать в простом формате Walk-and-Scan: быстро, удобно и эффективно. От просмотра облака точек в реальном времени до реконструкции в масштабе 1:1 и экспорта 3DGS — единый рабочий процесс превращает архитектурные пространства в ценные цифровые материалы. #SHARE3DCAM #SHARES20 #3DScanning #RealityCapture #PointCloud…
Новая версия ПО SHARE уже доступна! 🚀 В обновлении появилась поддержка 3DGS — 3D Gaussian Splatting. Эта функция доступна бесплатно. С помощью 3DGS можно создавать более реалистичные 3D-модели с высокой визуальной детализацией и удобным просмотром сцены. Посмотрите качество 3DGS-модели в этом примере 👇 Как вам результат? #SHARE3DCAM #3DGS #SLAM #LiDAR #3DMapping #PointCloud #BIM
🔥2
Привет, Россия! Мы здесь 🇷🇺 SHARE3DCAM открывает официальный канал для российского рынка.❤️❤️ Здесь мы будем делиться новостями о SHARE S20/S100, примерами облаков точек, демонстрациями, новыми функциями и практическими кейсами применения SLAM/LiDAR в геодезии, BIM, строительстве и промышленности.😁😁 Добро пожаловать! Следите за обновлениями — впереди будет много полезного.😎😎
🔥1
Channel photo updated
Channel created
Showing the 11 most recent of 11 posts we hold for @SHARE3DCAM_Russia. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Named by 1 registered channel — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.
Named by
Channels on the register whose posts name this channel's handle.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 2 October 2026 — this entry's latest reading, not the date you are reading this.
“SHARE3DCAM Россия” (@SHARE3DCAM_Russia), 78 subscribers as measured 2 October 2026. Telegram Register, tgregister.com/channel/SHARE3DCAM_Russia.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.