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Dev Diary: Advanced Rendering and Realistic Game Environments #ABI utilizes a comprehensive physically-based rendering framework, enhanced by advanced camera technologies such as automatic exposure and local exposure, to provide optimal lighting and visual comfort. It also features real-time global illumination, volumetric clouds, and dynamic weather, creating a realistic and...

44,175 次观看 • 2 年前 •via X (Twitter)

10 条评论

Guille Igenes 的头像
Guille Igenes2 年前

What about lowering hardware requirements? Please

actualTurtle 的头像
actualTurtle2 年前

Very nice but too bad the game is going to be Pay2Win

Lifeless 的头像
Lifeless2 年前

But yet its pitch black when looking into windows from outside

Super vegeta 的头像
Super vegeta2 年前

bro when can i be able to play with my NVIDIA GeForce GTX 1660 Ti

Martin Ho 的头像
Martin Ho2 年前

Unlock for RTX 3050 laptop pls 🫠

DANTE 的头像
DANTE2 年前

That's good but plz remove hardware restriction 🙂

kanpai 的头像
kanpai2 年前

@ArenaBreakoutPC Holy shit blue Memphis!!!! No way!!! I better tune in!!!

Pque 的头像
Pque2 年前

guess thats why my framerate is so unstable :DD

Yilmaz Ibrahim Basha 的头像
Yilmaz Ibrahim Basha2 年前

Magnificent! But at some places it’s too dark to see

nunya biz 的头像
nunya biz2 年前

Please let RTX 3050 laptop owners enjoy this as well. # Lower dem requirements lol.

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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.

AK

38,686 次观看 • 2 年前