newslounge.co · Jan 05, 2024

Good Morning. 

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on Today’s menu:

• Is Nerf The End of Photogrammetry

• Gaussian Splatting

• Why “Realistic Vision” is My Favorite AI Model?

• AnimateDiff v3: scary good

-Ardy

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HEADLINE

Is Nerf The End of Photogrammetry

💡Here's why I think NeRF is game-changing, industry-altering, and most of all—super exciting.

What is Nerf Technology?
Nerf stands for Neural Radiance Fields. It's a new tech in the 3D world that's making waves for its ability to create stunning 3D models. It uses machine learning to transform images and videos into highly detailed 3D representations.

How is Nerf Different from Traditional Photogrammetry?
Photogrammetry has been the standard for turning photos into 3D models. It's useful but can be slow and sometimes produces less-than-perfect results. Nerf, on the other hand, is faster and more accurate. It can work with fewer images and even handle dynamic, moving objects, which traditional photogrammetry struggles with.

Key Features of Nerf:

• Efficiency and Speed: Nerf processes data quicker than traditional methods.

• Handling Dynamic Objects: Unlike photogrammetry, Nerf can work with videos, allowing it to capture moving objects.

• Radiance Field: This is a core part of Nerf. It guesses how unseen parts of an object might look, allowing for renders from any angle.

• Quality of Renders: Nerf is known for capturing intricate details and can even handle reflective surfaces and lighting changes.

While Nerf is promising, it's not without its challenges. It needs a lot of high-quality data for training and Sometimes, lighting and shadow effects can be inconsistent.

Gaussian Splatting vs Nerf Technology

• Nerf uses neural networks to create a Radiance Field from images, guessing unseen parts of an object. Gaussian Splatting, however, uses a Point Cloud and transforms each point into a Gaussian, optimized to match the original photos.

• Gaussian Splatting is generally faster and more efficient in training, making it suitable for quick 3D scene generation.

▶This video by Wren Weichman over at Corridor Digital demonstrates the level of excitement that this new technology warrants.

▶This video demonstrates the power of 3D Gaussian Splatting.

Conclusion:
Both 3D Gaussian Splatting and Nerf are innovative technologies in the field of 3D modeling and virtual production. Gaussian Splatting stands out for its speed and detail in creating 3D scenes, especially useful in real-time applications. Nerf, with its neural network-based approach, offers versatility in creating detailed 3D models from limited data. Each has its unique strengths, making them valuable tools in different aspects of 3D creation and visualization.

-AA

🚨KIRI Engine introduced 3D Gaussian Splatting in their 3D scanning app in November. Now, it's even better because you can create a 3D model from a photo and edit it directly on your smartphone.

CASE STUDY

Why “Realistic Vision” is My Favorite AI Model?

The Realistic Vision model is highly regarded for its ability to create images that are not only visually stunning but also remarkably lifelike, making it a valuable tool for generating realistic and professional-quality digital imagery.

This model excels in several key areas:

• Professional Photographic Quality: The images generated have a professional photo feel, characterized by realistic posing and lighting, as well as expressive models.

• Realism in Scenes and Details: It can create very realistic-looking scenes, including detailed foliage, backgrounds, and tattoos. The materials, like fabric textures and skin tones, are rendered with high fidelity.

• Photorealistic Composition: The compositions created by the model are aesthetically pleasing and realistic, often featuring dramatic backdrops and natural lighting effects.

🙋‍♂️It's not just limited to portraits or human subjects; the model can also create realistic landscapes, animals, and even fantasy elements.

👩‍💻you can find all of them on HuggingFace.

-AA

SNIPPETS

🥽Liminal Space secures $2.5M funding to offer VR-like immersion without the need for headsets.

💲Industry has said Britain could lose out to other countries, particularly in animation and special effects.

🚨The GPT store will be here next week. Users will now be able to distribute and monetize GPTs.

👩‍💻CES 2024: How to watch as Nvidia, Samsung and more reveal hardware, AI updates.

🎬Record Once: Create video tutorials in minutes with an AI that edits and fixes mistakes.

AROUND THE WORLD OF AI

AnimateDiff v3: scary good

I recently explored AnimateDiff v3, the latest update to the AnimateDiff software, which revolutionizes the way we animate images. This new version introduces some cool features that set it apart from its predecessors and other similar software in the market.

A standout feature of AnimateDiff v3 is its ability to utilize multiple scribbles for guiding animations.

Now, you can draw multiple lines or shapes on an image, and AnimateDiff v3 ingeniously uses these as a basis to craft animations. Imagine sketching a circle on a person's face in a photo; the software can animate the head moving within that circle, adding a dynamic layer to your images.

Moreover, AnimateDiff v3 breaks new ground with its extended animation length. While the previous version was capped at 16 frames, AnimateDiff v3 leaps forward, allowing animations up to 64 frames. This expansion means more room for creativity, enabling more complex and nuanced animations.

📌In the realm of similar software, AnimateDiff v3 stands out. While Stable Video Diffusion offers comparable features, its commercial use is restricted by licensing limitations. Another competitor, Comfy, though similar, falls short in terms of user-friendliness.

-AA

This AI-powered animation with a fun storyline has been created using Stable Diffusion and After Effects .

A bag of money has been stolen - will the police catch the suspect? . 👀👮💼

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