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Finally got #gaussiansplatting working! I’m really impressed by how well it captured the fine details of the sneaker fabric and shoelaces, as well as the text. This was generated from 75 DSLR photos I shot on a 24mm lens, took about 30 minutes to process on an RTX 3090,...

183,486 次观看 • 2 年前 •via X (Twitter)

10 条评论

Matt Wolfe 的头像
Matt Wolfe2 年前

This looks amazing! Was the setup pretty complex? Were you able to follow the instructions from Github and get it working or did you run into complications? This looks so much better than the NeRFs I’ve been doing.

CoffeeVectors 的头像
CoffeeVectors2 年前

Thanks so much Matt! And I definitely kept running into different problems setting up the pipeline. The big thing to get this working was this video tutorial I found. Let me know if you still run into issues and I’ll try to help!

Oskar Stålberg 的头像
Oskar Stålberg2 年前

Cool! How big is a file like this on disk?

CoffeeVectors 的头像
CoffeeVectors2 年前

75 DSLR photos - 1.62 GB Camera Position Files from COLAB - 1.57 GB Trained Gaussian Splatter Model - 339 MB

illumixis 的头像
illumixis2 年前

Mouth. Watering.

CoffeeVectors 的头像
CoffeeVectors2 年前

Thank you! I was pretty surprised by the quality! I’ve been trying it on some other stuff and getting mixed results so trying to understand how to optimize things. Have you played around with the tech yet?

Javi Bravo | VFX 的头像
Javi Bravo | VFX2 年前

Can it be exported to an obj?

CoffeeVectors 的头像
CoffeeVectors2 年前

It’s pretty new so there aren’t many tools out other than the viewer. I’m hoping we start seeing more stuff soon!

MattVidPro AI 的头像
MattVidPro AI2 年前

How do the reflections work on the non fabric parts of the shoe?? That is amazing! Would kill to see this tech implemented into a game

CoffeeVectors 的头像
CoffeeVectors2 年前

This video might help explain how this all works:

相关视频

🔴 Finally! NVIDIA has finally made the code for Neuralangelo public! It has the ability to transform any video into a highly detailed 3D environment, and it's a technology related to but DIFFERENT from NeRF. 💡 Here's how it works: It takes a 2D video as input, showing an object, monument, building, landscape, etc., from various perspectives and analyzes details such as depth, size, and the shapes of objects. From this, the AI sketches an initial 3D model, similar to how an artist molds a figure. This representation is then refined to highlight more details, just as an artist would make the final touches when sculpting. The result is a 3D environment/model, perfect for use in any environment. Imagine the applications it will have for video games, cinema, virtual environments, VR, and more! 📽️🎮 💡 More details: A year ago, an article was presented on a groundbreaking technique called NVIDIA's Instant NeRF. This technique turns images into stunning 3D scenes in a short time, ideal for creating realistic models for video games and other applications. Although Instant NeRF had a lot of potential, the generated models were not perfect and often lacked detailed structures, appearing somewhat cartoonish. A year on, NVIDIA releases a new technique based on Instant NeRF, named Neuralangelo. This enhances the fidelity of surface structures. While NeRF reconstructs real objects in virtual environments from images or videos, Instant NeRF speeds up this process, and Neuralangelo further improves the quality, making the generated objects appear even more realistic when examined up close. Neuralangelo improves Instant NeRF's approach in two key ways related to the hash grid encoding technique: 1⃣ Numerical gradients have been used to compute higher-order derivatives as a smoothing operation. This optimizes the "hash grid" encoding using numerical rather than analytical gradients, providing a smoother input to the network that produces the 3D model. 2⃣ A "coarse-to-fine" optimization has been implemented in the hash grids to control different levels of detail. That is, they first focus on a smoothed version of the scene, and then refine it with more detailed updates. Well, as Arthur C. Clarke said, "Any sufficiently advanced technology is indistinguishable from magic."

Javi Lopez ⛩️

689,169 次观看 • 2 年前

It’s hard to believe that 3 years ago, none of this was possible. Now, it’s pretty much going to change everything. Last month, Fish Audio reached out to me to try their voice AI software. They just launched their new S1 model today, and I was curious about the state of AI and voice (and everything else), so I gave it a spin. I liked it enough that when I was asked about a partnership, I said yes. I’m free to talk about what I like and don’t like about the software, and I’m going to share with you a few voices I cloned as well as some of the workflow. It was much easier than I thought. To give you an example, here is a private (research only) voice I cloned as a test. I grabbed a clip of Rutger Hauer’s famous speech from Blade Runner and uploaded it to the voice cloner on the Fish Audio Website as a private voice (no one else can use it, as it is for research only). I didn’t think it would work. The audio sample is very short. But Fish Audio was able to clone the voice extremely well and very fast. I didn’t have to upload any more than that to produce these results. I used Grok to write the new dialog, and I added the rain and background effects and the result is pretty impressive. It only took just a few minutes once I had the audio uploaded for everything from cloning to generating multiple takes. I’ll give some tips and pointers on how to get the best results at the conclusion of this thread and show you some surprising things it can do. (con’t) #Promotion

Grummz

69,859 次观看 • 1 年前