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Testing a method to blend objects into the terrain surface. This allows the terrain virtual texture and height to be sampled at pixels' world position and blended in to the object's texture. The terrain normal is computed from the height and also blended with the object normal.

14,923 次观看 • 2 年前 •via X (Twitter)

7 条评论

solitary 的头像
solitary2 年前

This an engine feature!?

János Turánszki 的头像
János Turánszki2 年前

Not yet but it will be, the implementation has still some things that I don't like.

SÄME 的头像
SÄME2 年前

How expensive it is at the runtime?

János Turánszki 的头像
János Turánszki2 年前

It's not very cheap, for every pixel, I look up terrain chunk, sample it's heightmap, compute terrain uv, normal and blending, then sample all terrain surface virtual textures on top of the object's base material.

gamedev_chris 的头像
gamedev_chris2 年前

nice! what about multiplayer support, do you have it in the engine?

János Turánszki 的头像
János Turánszki2 年前

Thanks but there is not multiplayer support.

kekitopu 🔞 的头像
kekitopu 🔞1 年前

🤯

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Blended-NeRF: Zero-Shot Object Generation and Blending in Existing Neural Radiance Fields paper page: Editing a local region or a specific object in a 3D scene represented by a NeRF is challenging, mainly due to the implicit nature of the scene representation. Consistently blending a new realistic object into the scene adds an additional level of difficulty. We present Blended-NeRF, a robust and flexible framework for editing a specific region of interest in an existing NeRF scene, based on text prompts or image patches, along with a 3D ROI box. Our method leverages a pretrained language-image model to steer the synthesis towards a user-provided text prompt or image patch, along with a 3D MLP model initialized on an existing NeRF scene to generate the object and blend it into a specified region in the original scene. We allow local editing by localizing a 3D ROI box in the input scene, and seamlessly blend the content synthesized inside the ROI with the existing scene using a novel volumetric blending technique. To obtain natural looking and view-consistent results, we leverage existing and new geometric priors and 3D augmentations for improving the visual fidelity of the final result. We test our framework both qualitatively and quantitatively on a variety of real 3D scenes and text prompts, demonstrating realistic multi-view consistent results with much flexibility and diversity compared to the baselines. Finally, we show the applicability of our framework for several 3D editing applications, including adding new objects to a scene, removing/replacing/altering existing objects, and texture conversion.

AK

62,768 次观看 • 2 年前