Meta's AI Text-to-3D Generators - The Ultimate Tool For Creators ! - video Dailymotion

High tech & Ai world

Ever wondered how AI can revolutionize your 3D design process? In this video we dive into Meta's latest breakthrough :

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00:00As you go into VR and you have an avatar version of the AI and you can talk to them there,

00:07that's going to be really compelling. It's at a minimum creating much better NPCs and experiences

00:14when there isn't another actual person who you want to play a game with. You can just have

00:18AIs that are much more realistic and kind of compelling to interact with.

00:23Meta has launched a new text-to-3D generator AI that will transform your workflow.

00:28This revolutionary tool lets you create 3D models from simple text descriptions

00:33in a fraction of the time. Imagine crafting intricate characters, designing stunning

00:39environments, or generating unique props, all with just a few words. Meta's text-to-3D is

00:46your ultimate companion. Let's delve into its full capabilities. Meta's AI text-to-3D generator.

00:54Meta is known for its constant evolution in the realm of artificial intelligence,

00:59particularly with its content tagging system that adapts to new types of content and trends.

01:05Beyond these day-to-day applications, Meta's research wing is delving into more groundbreaking

01:10areas of AI technology. One of their most innovative developments is an AI tool called

01:15Meta 3D Gen. Meta 3D Gen represents a big leap forward in the field of generative AI.

01:22This tool is designed to generate 3D assets from text descriptions with a high degree of accuracy,

01:28as shown by the images on Meta handle on thread. The ability to create 3D models based solely on

01:34textual input is a game changer, especially for industries that rely heavily on digital

01:40content creation, such as gaming, virtual reality, and film. Meta claims that 3D Gen

01:46can produce outputs at speeds three to sixty times faster than professional artists. This

01:52remarkable efficiency does not come at the expense of quality. On the contrary, 3D Gen generates

01:58assets with high-resolution textures and material maps that are superior in quality compared to

02:04previous state-of-the-art solutions. This performance boost is achieved at three to ten

02:09times the speed of earlier methods, highlighting the system's huge advancements in both speed and

02:14quality. One of the standout features of Meta 3D Gen is its support for physically-based rendering.

02:21This is essential for creating 3D objects that look realistic under various lighting conditions,

02:26as depicted in the example here. This technology simulates the physical properties of materials,

02:32allowing the 3D assets generated by Meta 3D Gen to react to light in a way that mimics real-world

02:38materials. This means that objects created using this tool can appear hyper-realistic, enhancing

02:44the visual experience in any application where they are used. Moreover, Meta 3D Gen is not just

02:50about creating new 3D assets from scratch. It is also highly versatile in its ability to re-texture

02:56existing models. Whether the original model was generated by AI or created by an artist, Meta 3D

03:03Gen can apply new textures based on fresh text prompt. This feature allows for a high degree of

03:08customization and flexibility, enabling users to alter the appearance of 3D models to fit different

03:15themes or requirements without having to rebuild them from the ground up. How it works. Meta's 3D

03:21Gen uses a two-stage method that leverages the strengths of two foundational generative models,

03:27Asset Gen and Texture Gen, to create high-quality 3D models for immersive content.

03:32This approach involves a division of labor between the two models, where each focuses

03:37on different aspects of the 3D creation process, allowing for enhanced control and refinement,

03:44much like the way text-to-image generators function. The first stage in this process is

03:48handled by Meta's Asset Gen. Asset Gen is responsible for generating the 3D geometry

03:54of the object. When provided with a prompt, Asset Gen rapidly constructs the basic shape

04:00and structure of the object in three dimensions. This initial stage takes only about 30 seconds,

04:06during which the model also applies basic textures and physically-based rendering to the 3D object.

04:13Once the basic 3D geometry is created by Asset Gen, the process moves to the second stage,

04:19where Texture Gen takes over. Texture Gen's role is to refine and enhance the textures

04:24applied to the 3D object, ensuring high resolution and detailed surface properties.

04:30This optimization process happens swiftly, within the next 20 seconds. Texture Gen meticulously

04:37works on the textures, improving their quality and making them more realistic and detailed.

04:42This stage is crucial because it significantly enhances the visual fidelity of the 3D model,

04:48making it suitable for immersive content where high-quality visuals are essential.

04:53The separation of tasks between Asset Gen and Texture Gen allows for greater control over the

04:583D modeling process. Users can focus on refining specific aspects of the model independently,

05:05similar to how text-to-image generators allow for iterative refinement of generated images.

05:10Additionally, users can provide further textual inputs to retexture previously created 3D shapes.

05:17This feature is particularly useful for those who need to modify the appearance of an object

05:21without starting from scratch. For instance, if a user is satisfied with the shape of a 3D model,

05:27but wants to change its texture to fit a different context or aesthetic, they can simply input new

05:32textual instructions, and Texture Gen will apply the new texture accordingly. This flexibility

05:38significantly enhances the usability and adaptability of the 3D Gen system. You can

05:43easily make those adjustments without having to redo the entire model from scratch.

05:483D Gen Generation Process

05:51Meta 3D Gen generation process involves several sophisticated steps to achieve

05:57photorealistic quality, leveraging advanced techniques in computer graphics and machine

06:02learning. The first step in Meta 3D Gen's process is generating multiple views of the object. These

06:09views are not just simple 2D images, but are enhanced with detailed information about the

06:14object's appearance. Specifically, the views include factored shaded appearance in albedo.

06:20The shaded appearance refers to how the object looks under different lighting conditions,

06:25while albedo represents the inherent color of the object, independent of lighting and shadows. By

06:31capturing this information, Meta 3D Gen can accurately represent the object's visual properties

06:37from different angles. Next, the system reconstructs key physical attributes of the

06:42object, including its colors, metallicity, and roughness in a 3D space. These attributes are

06:49crucial for creating realistic models because they affect how the object interacts with light.

06:55For instance, metallicity determines how metallic or non-metallic the surface appears,

07:00influencing reflections and highlights. Roughness affects the surface texture,

07:06dictating how light scatters when it hits the object. To achieve this reconstruction,

07:11Meta 3D Gen uses a neural network trained via a method called deferred shading loss.

07:17Deferred shading is a technique in computer graphics where the rendering of light and

07:22shadow is postponed until after the initial geometry and texture information has been

07:27processed. By applying a deferred shading loss, the network learns to accurately recreate the

07:32object's appearance in 3D by comparing its predictions to the target appearance under

07:37various lighting conditions. This approach ensures that the reconstructed model maintains

07:42high fidelity to the original object. A critical output of this reconstruction process is the sine

07:48distance function. A sine distance function provides a mathematical representation of the

07:53object's surface by indicating the distance of any point in space to the closest point on the

07:58object's surface. From this function, a 3D mesh can be extracted. The mesh represents the object's

08:05geometry as a network of vertices, edges, and faces, forming a detailed structure that can be

08:12rendered in 3D space. After the mesh is created, a final texture refinement step is performed in

08:18the UV space. UV space refers to a 2D representation of the 3D surface used for texture mapping.

08:25This process involves unwrapping the 3D model onto a 2D plane where textures can be applied

08:30more efficiently. The texture refinement step significantly enhances the sharpness and detail

08:36of the model by fine-tuning the textures mapped onto the 3D surface. This step ensures that even

08:42the smallest details are accurately represented, resulting in a highly realistic and visually

08:48appealing final model. Potential application. The implications of this technology are vast.

08:55For instance, in the gaming industry, developers can use Meta 3D Gen to quickly generate a wide

09:01variety of assets, reducing the time and cost associated with manual 3D modeling.

09:07Similarly, in virtual reality, where the creation of immersive environments is key,

09:12this tool can expedite the process of populating these virtual spaces with detailed and realistic

09:18objects. In film and animation, artists can leverage Meta 3D Gen to produce detailed props

09:24and environments more efficiently, allowing them to focus more on creative storytelling.

09:29Additionally, the ability to generate and retexture 3D models based on text descriptions

09:35makes this tool accessible to users who may not have extensive experience in 3D modeling. By

09:41lowering the barrier to entry, Meta 3D Gen democratizes the creation of high-quality 3D

09:47content, enabling more people to participate in the production of digital assets. Beyond its immediate

09:52applications, Meta 3D Gen also opens up new possibilities for future innovations. As AI

09:59continues to improve, it could potentially generate even more complex and detailed models,

10:05further pushing the boundaries of what is possible in digital content creation.

10:10Moreover, the integration of this technology with other AI-driven tools and platforms could lead to

10:15even more sophisticated and automated workflows, transforming the way industries approach 3D

10:21modeling and rendering. The Future of 3D Generator

10:26One of the big issues in 3D generation is creating models that look convincing

10:30in both virtual reality and real-world applications. This difficulty arises because

10:36VR environments are particularly unforgiving when it comes to artificial detailing. In VR,

10:42users can view objects up close and from multiple angles, making any imperfections

10:47or lack of detail immediately noticeable. To create a believable experience, it is crucial

10:52to have as much detail as possible in the actual geometry of the models, rather than relying solely

10:58on textures. Currently, many AI models that generate 3D content tend to produce low-resolution

11:04geometry and rely heavily on textures to approximate details. This approach can work

11:10for certain applications where the models are not examined too closely. However, in VR, this method

11:16falls short because textures alone cannot provide the depth and realism needed when users can

11:22scrutinize every aspect of the environment. Metacompany, known for its advancements in AI

11:27and large language models like the recent Lama3, is addressing this challenge with its tool Meta3DGen.

11:34Meta3DGen aims to create more sophisticated 3D models that can meet the high standards required

11:40for VR and real-world applications. One of the main obstacles in this field is the limited

11:46availability of high-quality 3D datasets for training AI models. Unlike images and videos,

11:52which are abundant and easily accessible, 3D data is much scarcer and more complex to work with.

11:59Despite these challenges, the examples provided by Meta3DGen are remarkably promising. The tool

12:05leverages Meta's expertise in AI to push the boundaries of what is possible in 3D generation.

12:11By focusing on enhancing the actual geometry of the models, Meta3DGen can produce more detailed

12:18and realistic outputs. Meta is setting a new standard for 3D generation in both VR and real-world

12:25applications. The advancements made by Meta in the 3D generation space have broader implications

12:31for the industry. As tools like Meta3DGen become more sophisticated, they will enable creators and

12:38developers to produce higher-quality content, more immersive VR experiences, and more realistic 3D

12:45models in various applications, from gaming and entertainment to design and architecture.

12:51If you have made it this far, let us know what you think in the comment section below.

12:55For more interesting topics, make sure you watch the recommended video that you see on the screen

12:59right now. Thanks for watching.

Meta's AI Text-to-3D Generators - The Ultimate Tool For Creators !

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