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Artists favorite Rendering solution is constantly evolving 📈 ! As we continue to build one of the best rendering solutions available on the market, our developers have been working on some exciting new features that we've just released: - Playback feature: Artists can now preview their frame sequences in...

10,404 просмотров • 2 лет назад •via X (Twitter)

Комментарии: 14

Фото профиля Yoriichi Tsugikuni
Yoriichi Tsugikuni2 лет назад

I said it before & i’ll say it again. $OCTA will takeover the entire rendering sector.

Фото профиля mikro
mikro2 лет назад

$OCTA going mainstream 📈

Фото профиля Ferry Tayle 🐙
Ferry Tayle 🐙2 лет назад

$octa is the king of #depin 🔥💪🏻

Фото профиля Julio Benavides
Julio Benavides2 лет назад

Who make this red cute robot xd

Фото профиля OctaSpace
OctaSpace2 лет назад

Who indeed 😉

Фото профиля KryptoHase 🇺🇸🇩🇪
KryptoHase 🇺🇸🇩🇪2 лет назад

sky's the limit, and $OCTA is aiming for the stars! 🌌💎

Фото профиля Kakashi - τ -
Kakashi - τ -2 лет назад

$OCTA 💙

Фото профиля Dat Ho
Dat Ho2 лет назад

If you haven’t checked $OCTA out yet, now is the time 🕰️

Фото профиля 🛰️ CryptoGemGR 🛰️🌍 7Sins Island 🌍
🛰️ CryptoGemGR 🛰️🌍 7Sins Island 🌍2 лет назад

Yes it is. Deserves another x10 $octa

Фото профиля Reza.aghaamohamadi
Reza.aghaamohamadi2 лет назад

$octa 💎

Фото профиля Nisre
Nisre2 лет назад

Octa💯

Фото профиля Raptor_19
Raptor_192 лет назад

$OCTA 👊🏼

Фото профиля Clarois | Motion Designer
Clarois | Motion Designer2 лет назад

Still use it 🔥

Фото профиля H_Que
H_Que2 лет назад

Love $OCTA project ❤️❤️🫰

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VideoRF: Rendering Dynamic Radiance Fields as 2D Feature Video Streams paper page: Neural Radiance Fields (NeRFs) excel in photorealistically rendering static scenes. However, rendering dynamic, long-duration radiance fields on ubiquitous devices remains challenging, due to data storage and computational constraints. In this paper, we introduce VideoRF, the first approach to enable real-time streaming and rendering of dynamic radiance fields on mobile platforms. At the core is a serialized 2D feature image stream representing the 4D radiance field all in one. We introduce a tailored training scheme directly applied to this 2D domain to impose the temporal and spatial redundancy of the feature image stream. By leveraging the redundancy, we show that the feature image stream can be efficiently compressed by 2D video codecs, which allows us to exploit video hardware accelerators to achieve real-time decoding. On the other hand, based on the feature image stream, we propose a novel rendering pipeline for VideoRF, which has specialized space mappings to query radiance properties efficiently. Paired with a deferred shading model, VideoRF has the capability of real-time rendering on mobile devices thanks to its efficiency. We have developed a real-time interactive player that enables online streaming and rendering of dynamic scenes, offering a seamless and immersive free-viewpoint experience across a range of devices, from desktops to mobile phones.

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38,686 просмотров • 2 лет назад