Telegram RegisterThe public register of Telegram

Channel

Cinema 4D Fresh

@C4D_Tutorials

On this record: Growth · Engagement · What this channel posts · Reactions · Stars · Posts · Citations · Cite this entry

959subscribers

+0 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of Under 1,000.

Register entry

Telegram ID-1002058286922
TypeChannel
Username@C4D_Tutorials
DescriptionСвежие, новые и классные, старые уроки, а также сцены, материалы, скрипты и плагины для Cinema 4D со всего интернета. New, fresh and good, old Cinema 4D tutorials, scenes, materials, scripts, plugins from all over the Internet.
CreatedBetween 1 November 2023 and 31 May 2024— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live13 August 2026
Measurements held2
On Telegramt.me/C4D_Tutorials

Growth

9596 Aug 2026, 03:53 — 959 subscribers6 Aug 2026, 13:38 — 959 subscribers6 Aug 2026, 03:536 Aug 2026, 13:38
2 measurements taken within a single day. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 958–960 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
6 Aug 2026, 13:38959no change
6 Aug 2026, 03:53959first reading

Engagement

20 posts held, back to 26 July 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 pageof Telegram’s post history, 20 posts per page.

ERR · 30 days
22.8%
avg views ÷ 959 subscribers
Avg views / post
218
20 posts measured
Reaction rate
1.22%
reactions ÷ views · ER floor
Posts in window
20
of 20 held

ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.

ER is defined industry-wide as (forwards + reactions + comments) ÷ views— note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate. It is computed over the 16 of 20 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 6 August 2026
Posts held20 (26 July 20266 August 2026)
Views total4,366
Reactions total44
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken6 Aug 2026, 13:38 UTC

Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.

Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.

Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.

What this channel posts

Photos
110
Videos
173
Links
2,520

Lifetime counters from Telegram’s own channel header, read 6 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.

Reaction mix

44 reactions across 16 posts, in 5 distinct kinds. The most used accounts for 34.1% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
👍1534.1%
🔥1431.8%
1022.7%
🤝49.09%
👌12.27%

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 16 of the 20 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 44reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 20 most recent posts we hold, published 26 July 2026 to 6 August 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.

Telegram Stars

Stars received
1
across the posts below
Posts paid on
1
of 20 we hold a reading for · 5%
Most on one post
1
single highest reading

A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @C4D_Tutorials. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.

Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.

This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.

Counted over the 20 most recent posts we hold for this entry, published 26 July 2026 to 6 August 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.

Recent posts

5 Aug 2026, 11:22 UTC175 views1 reactions1 Starread 6 August 2026

Создаём реалистичную анимацию океана в Cinema 4D 2026 с помощью бесплатного плагина HOT4D 2026. Настраиваем деформатор, изучаем влияние параметра Choppiness на форму и выразительность волн, а также используем Vertex Map для создания эффекта морской пены. Осваиваем продвинутые техники: настраиваем Xpresso для процедурного управления движением объектов и применяем тег Constraint, чтобы лодка или камера естественно след

👌1

5 Aug 2026, 01:44 UTC172 views2 reactionsread 6 August 2026

Детальное видео от профессионального фотографа том, как выставлять выразительный свет в продуктовой съемке стекла и жидкости. Учимся управлять светом и физикой отражений, используя диффузные экраны для получения мягких градиентов, скрытые отражатели для придания напитку внутреннего свечения и флаги для контроля паразитного света. Пошагово собираем световую схему, анализируя роль каждого элемента — от контурного освещ

🔥2

5 Aug 2026, 01:44 UTC175 views2 reactionsread 6 August 2026

Разбираемся, как выстраивать продуктовый свет, на примере реальной съемки товаров для красоты. Пошагово собираем сложную световую схему для косметических продуктов, используя импульсные источники света и узконаправленные насадки для точной проработки отдельных деталей. Работаем с тезерингом, оценивая результат на мониторе в реальном времени, и точно настраиваем мощность каждого источника без использования флешметра.

🔥2

5 Aug 2026, 01:44 UTC186 viewsread 6 August 2026

Несколько дней назад наткнулся на просторах Ютюба на видео Карла Тейлора про освещение в продуктовой фотографии. Сначала думал, что в основном будут технические аспекты и совсем немного художественных. Оказалось с точностью наоборот. Карл рассказывает как выстроить наиболее выразительный свет, чего нужно избегать и как вообще выстроить работу. В целом смотреть интересно и невероятно познавательно. Всем любителям прод

4 Aug 2026, 16:51 UTC153 views12 reactionsread 6 August 2026
Forwarded from @adrogan_artPhoto

Мне всегда не хватало на камере Redshift одной простой вещи: вкладки типа Project, чтобы можно было выключить видимость объектов для конкретной камеры. Через тейки делать не хотелось. Всегда удивлялся, почему такой функции нет. Взял и сделал. Скачать RS_CamExclude Накидываете тег на камеру и добавляете в него объекты. Я изобрёл велосипед или норм?

👍5🤝4🔥3

3 Aug 2026, 10:36 UTC222 views1 reactionsread 6 August 2026

Разбираем основные инструменты освещения в Octane Render и учимся добиваться физически корректных результатов. Детально изучаем работу источника Area Light, выясняем, как его размер влияет на мягкость теней, и разбираемся с параметром Surface Brightness, отвечающим за интенсивность свечения. Также рассматриваем специализированные типы света: Target Light для удобного слежения за объектом, IES Light для имитации реаль

👍1

3 Aug 2026, 10:31 UTC217 views1 reactionsread 6 August 2026

Вместе с Мишей Бычковым детально разбираем рекламный ролик Google, выполненный в стиле минимализма. Пошагово воссоздаём ключевые сцены, уделяя особое внимание настройке физической динамики, работе с клонерами и процедурному моделированию объектов. Разбираемся, как добиться эстетики «мягкого» освещения, правильно настроить материалы и управлять движением элементов с помощью полей и эффекторов. #Stream #Google #BreakD

1

3 Aug 2026, 10:16 UTC212 views3 reactionsread 6 August 2026

Подробно разбираем ноду UV Context в Redshift, которая значительно упрощает процесс наложения текстур и создания сложных материалов. Изучаем, как с его помощью можно избежать эффекта тайлинга благодаря гексагональной раскладке и гибко управлять проекциями без изменения тегов самого объекта. В качестве практического примера используем фигурки, созданные с помощью ИИ-сервиса Tripo 3D, и добавляем на них царапины, грязь

2🔥1

3 Aug 2026, 10:11 UTC218 viewsread 6 August 2026

Создаём процедурную конвейерную ленту в Cinema 4D, используя возможности модуля MoGraph. Распределяем объекты вдоль замкнутого сплайна с помощью клонера и добиваемся плавного движения, активируя функцию Smooth Rotation. Используем Target Effector в режиме Next Node, чтобы каждый сегмент ленты ориентировался на следующий за ним элемент. #Conveyor #MoGraph #TargetEffector #NextNode #MaxonTeam #Noseman #Jul26 https://w

30 Jul 2026, 01:44 UTC230 views1 reactionsread 6 August 2026

Урок про создание реалистичного рендера баскетбольного мяча. Основной акцент ставится на глубокую проработку текстур и материалов. Николай Хан рассказывает про использование искусственного интеллекта для генерации UV-разверток и масок. Это позволяет быстро интегрировать сложные паттерны Louis Vuitton и логотипы NBA на бесплатную базовую модель. Урок охватывает технические аспекты настройки нодовой системы, включая р

👍1

30 Jul 2026, 01:44 UTC243 viewsread 6 August 2026

Урок про реорганизацию интерфейса настроек Octane Render 2026. Вместо привычных четырех вкладок теперь представлено пять. Обновление направлено на упорядочивание параметров, разделение глобальные установки плагина и специфические настройки сцены для более интуитивной навигации. Ключевые изменения коснулись выделения инструментов постобработки и управления цветом, а также появления более удобного процентного управлени

Showing the 12 most recent of 20 posts we hold for @C4D_Tutorials. 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.

Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.

Citation-graph rank

Citation-graph rank — 269,009 of 1,176,251entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.

Forward network

Republished by

Channels on the register that have forwarded this channel's posts into their own feed.

Republishes

Channels on the register whose posts this channel has forwarded.

Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.

Mentions

Names

Channels on the register whose handles appear in this channel's posts.

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.

Cite this entry

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 6 August 2026 — this entry's latest reading, not the date you are reading this.

“Cinema 4D Fresh” (@C4D_Tutorials), 959 subscribers as measured 6 August 2026. Telegram Register, tgregister.com/channel/C4D_Tutorials.

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.