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Ever wished you could have sprites that could move like 3D models, without actually needing to be boring old 3D models? Then look no further! #screenshotsaturday

43,926 Aufrufe • vor 1 Jahr •via X (Twitter)

10 Kommentare

Profilbild von D.O.R.F. Real-Time Strategic Conflict
D.O.R.F. Real-Time Strategic Conflictvor 1 Jahr

Watch on Youtube:

Profilbild von kingbdogz
kingbdogzvor 1 Jahr

This looks incredible. Love to see improvement on old rendering techniques.

Profilbild von Punished Norm
Punished Normvor 1 Jahr

Beautiful stuff as always, but I'll be very honest: those black triangles at the top are kind of annoying. I get that there's a rendering distance limit, but still, it's a little irritating. I'm still excited for this game, though. Keep it up!

Profilbild von D.O.R.F. Real-Time Strategic Conflict
D.O.R.F. Real-Time Strategic Conflictvor 1 Jahr

That’s actually an ancient bug we’ve been trying to figure out for a while. It’s still unclear what is causing it

Profilbild von Uncle Sponge
Uncle Spongevor 1 Jahr

This looks sick. I love the HUD. Graphic system is similar to brigador. Do you have a target release date?

Profilbild von Sid
Sidvor 1 Jahr

Sprite Sheet? Like an image with all the different views?

Profilbild von D.O.R.F. Real-Time Strategic Conflict
D.O.R.F. Real-Time Strategic Conflictvor 1 Jahr

The sprite sheet is just an image that has all the different sprite frames of every different view rendered onto it, with metadata to tell the game where every frame is located

Profilbild von Jussi Kemppainen | Drivers of the Apocalypse
Jussi Kemppainen | Drivers of the Apocalypsevor 1 Jahr

Perfection 👌

Profilbild von Kay🔮🧙‍♂️
Kay🔮🧙‍♂️vor 1 Jahr

Been saying forever RTS should go back to this style of rendering; it lets low end computers (such as ones with integrated gpus) play without pathfinding calculation being heavily impacted.

Profilbild von Noble Six
Noble Sixvor 1 Jahr

Aircraft handling looks amazing!!

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3D-LLM: Injecting the 3D World into Large Language Models paper page: Large language models (LLMs) and Vision-Language Models (VLMs) have been proven to excel at multiple tasks, such as commonsense reasoning. Powerful as these models can be, they are not grounded in the 3D physical world, which involves richer concepts such as spatial relationships, affordances, physics, layout, and so on. In this work, we propose to inject the 3D world into large language models and introduce a whole new family of 3D-LLMs. Specifically, 3D-LLMs can take 3D point clouds and their features as input and perform a diverse set of 3D-related tasks, including captioning, dense captioning, 3D question answering, task decomposition, 3D grounding, 3D-assisted dialog, navigation, and so on. Using three types of prompting mechanisms that we design, we are able to collect over 300k 3D-language data covering these tasks. To efficiently train 3D-LLMs, we first utilize a 3D feature extractor that obtains 3D features from rendered multi- view images. Then, we use 2D VLMs as our backbones to train our 3D-LLMs. By introducing a 3D localization mechanism, 3D-LLMs can better capture 3D spatial information. Experiments on ScanQA show that our model outperforms state-of-the-art baselines by a large margin (e.g., the BLEU-1 score surpasses state-of-the-art score by 9%). Furthermore, experiments on our held-in datasets for 3D captioning, task composition, and 3D-assisted dialogue show that our model outperforms 2D VLMs. Qualitative examples also show that our model could perform more tasks beyond the scope of existing LLMs and VLMs.

AK

249,572 Aufrufe • vor 2 Jahren