Why THIS is the Future of Imagery (and Nobody Knows it Yet)

The video explores the revolutionary impact of neural radiance fields (NeRF) on the future of imagery and filmmaking. The host demonstrates how NeRF technology can quickly and easily create photorealistic 3D renders from a series of 2D images, overcoming the limitations of traditional photo scanning. The video showcases various applications of NeRF, such as background replacement, creating portals to other worlds, and even simulating complex camera moves post-capture. The host also discusses the potential for NeRF to facilitate a VFX revolution, as evidenced by the interest from renowned VFX artist Paul Franklin. The summary highlights the current capabilities and future possibilities of NeRF, emphasizing its potential to transform visual storytelling and filmmaking.

Takeaways

• 🌟 Neural Radiance Fields (NRFs) are a groundbreaking technology that could revolutionize filmmaking by enabling the creation of photorealistic imagery with minimal effort.
• 🚀 Traditional CGI requires significant time and resources, but NRFs allow for quick and easy rendering of complex scenes, even those with challenging elements like reflections and transparency.
• 🎥 The creator has a background in experimenting with new technologies to produce short films, utilizing tools like deep fakes, virtual production, and 3D scanning.
• 📸 Photo scanning is a powerful tool for creating 3D models from photos, but it has limitations, especially with reflective and transparent objects that cannot be accurately scanned.
• 🤔 NRFs solve the problem of imperfect photo scanning by using neural rendering to understand how light interacts with objects, allowing for realistic reflections and transparency.
• 🏆 Paul Franklin, an Oscar-winning VFX artist, sees a potential VFX revolution with NRFs, indicating a significant shift in the industry's approach to visual effects.
• 🌄 Photorealism in CGI is achieved through accurate reflections, which NRFs can replicate naturally by learning the color of every point in 3D space based on the viewer's perspective.
• 🎬 NRFs can be used for various applications like background replacement, creating portals to other worlds, and even scaling scenes to make objects or people appear larger or smaller.
• 📱 With advancements like Luma AI, creating NRFs has become as easy as using a phone app, significantly reducing the technical barriers to entry for filmmakers and creators.
• 🌆 NRFs are particularly effective in replicating the lighting conditions of the original scene, providing a unique flavor of photorealism that is tailored to the capturing camera.
• 🔍 While NRFs offer a new level of photorealism, they are not without limitations, such as the inability to extract reflective geometry without losing the reflective properties.

Q & A

What is the technology that the video discusses as the future of imagery?

The video discusses 'Neural Radiance Fields' (NeRF) as the future of imagery, which is a new technology that can create photorealistic images and videos with less time and effort compared to traditional CGI methods.

How does NeRF technology differ from traditional photo scanning?

NeRF technology differs from traditional photo scanning by not just creating a 3D model but also capturing the lighting, reflections, and transparency in a way that photo scanning cannot. It uses neural rendering to learn the color of every point in 3D space based on the viewing position, resulting in more realistic and photorealistic images.

What is the significance of reflections in achieving photorealism in CGI?

Reflections are significant in achieving photorealism because they play a crucial role in convincing our brains that the rendered objects are real. Every object reflects light from every other object in a scene, and accurately simulating these reflections can make a rendered image appear incredibly realistic.

How did the video's creator process the photos into a neural Radiance Field?

The creator used Luma AI, which simplifies the process to the point of using a phone app. They took a bunch of different photos, uploaded them to Luma AI's server, and after a few minutes, received a NeRF.

What are some potential applications of NeRF technology in filmmaking?

Potential applications of NeRF technology in filmmaking include background replacement, creating portals to other worlds, scaling objects or scenes to make characters appear larger or smaller, and post-production adjustments such as changing camera angles or adding effects after the footage has been captured.

How does the quality of the camera used to capture the original footage affect the final NeRF scan?

The quality of the camera used to capture the original footage significantly affects the final NeRF scan. Factors such as compression, dynamic range, and the quality of the lens can impact the finished scan, resulting in a more cinematic look for higher-quality cameras and a cheaper webcam look for lower-quality cameras.

What is the main advantage of using NeRF technology over traditional photogrammetry?

The main advantage of using NeRF technology over traditional photogrammetry is the ability to capture and render reflections, transparency, and lighting conditions in a more realistic and photorealistic manner. NeRF technology also allows for more flexibility in post-production, as the neural rendering can be adjusted and manipulated after the scan is taken.

How does the video demonstrate the potential of NeRF technology for creating complex and dynamic shots?

The video demonstrates the potential of NeRF technology by showing how it can be used to create complex and dynamic shots, such as a 'King Kong' effect where the subject appears巨大的 (huge), and an 'Inception' shot where the environment appears to fold over. These effects would be difficult and time-consuming with traditional methods but are achievable with much less effort using NeRF.

What is the current limitation of extracting geometry from a NeRF scan?

Extracting geometry from a NeRF scan is possible, but it results in the loss of the reflective properties of the scan. The reflectiveness gets baked down into a single diffuse texture, which means it does not change as you view it from different angles, losing the dynamic reflections that are a key feature of NeRF technology.

How does the video's creator suggest pushing the boundaries of NeRF technology?

The video's creator suggests pushing the boundaries of NeRF technology by experimenting with different applications, such as creating collision geometry for simulations, applying motion blur and depth of field effects, and exploring partnerships with software like Blender and Polycam to integrate NeRF technology into existing workflows.

What is the ultimate goal of the video's creator regarding NeRF technology?

The ultimate goal of the video's creator is to inspire others to explore and push the limits of NeRF technology. They believe that with further development, it will be impossible to distinguish between a NeRF and actual video, and they encourage artists and filmmakers to embrace this technology to create more realistic and innovative visual content.

Outlines

00:00

🎬 Introduction to Neural Radiance Fields (NRF) in Filmmaking

The video begins by expressing gratitude to 'bones and all' for sponsoring the video. The creator discusses the limitations of traditional CGI and introduces Neural Radiance Fields (NRF), a new technology that promises to revolutionize filmmaking. The speaker shares their experience with various technologies like deep fakes, virtual production, and 3D scanning, highlighting the challenges of photo scanning, especially with reflective or transparent objects. The video then demonstrates the process of creating a NRF from a set of photos, emphasizing the technology's ability to handle reflections and transparency, which are difficult for traditional photo scanning.

05:02

🌟 Sponsorship and NRF Technology's Capabilities

The video features a sponsored segment for the movie 'bones and all,' which is described as a unique blend of love story and horror thriller. The film is praised for its performances, cinematography, and direction. After the sponsorship message, the video returns to the topic of NRF technology, showcasing how easy it has become to create NRFs with the help of Luma AI. The creator discusses the potential applications of NRF, such as background replacement and creating portals to other worlds, and demonstrates these techniques with examples.

10:03

📸 Experimenting with NRF for Various Visual Effects

The video continues to explore the use of NRF technology for creating various visual effects. The creator discusses the importance of matching lighting conditions when capturing both the plate and the NRF to achieve a consistent look. They also experiment with different camera types, noting the impact on the final scan's quality. The video showcases the potential for complex camera movements and the possibility of extracting geometry from NRFs, although this comes with the loss of reflective properties. The creator expresses excitement about the future possibilities of NRF technology and its potential to change the way films are made.

15:05

🔍 The Future of NRF and Encouraging Exploration

The final paragraph focuses on the potential and future of NRF technology. The creator encourages artists to explore and push the boundaries of this new tech. They mention the use of Luma and NVIDIA's instant NRF, as well as the recent partnership between Polycam and NRF Studio, indicating a growing ecosystem of tools for artists. The video concludes with a call to action for viewers to look into NRF technology and consider its implications for the future of filmmaking.

Keywords

💡Neural Radiance Fields (NeRF)

Neural Radiance Fields, or NeRF, is a cutting-edge technology that uses machine learning to generate highly realistic 3D images from a collection of 2D photos. It's a method that captures the way light interacts within a scene, allowing for the creation of photorealistic renderings with reflections and shadows that change dynamically as the viewpoint changes. In the video, NeRF is used to create a photorealistic render of a scene in mere minutes, which would typically require significant effort and time using traditional CGI methods.

💡Photogrammetry

Photogrammetry is a technique that involves taking multiple photographs of an object or scene from different angles and using software to create a 3D model from these images. It's a common method in 3D scanning and is mentioned in the video as a shortcut for rendering 3D scenes. However, photogrammetry has limitations, such as difficulty in accurately capturing reflective or transparent objects, which is where NeRF technology offers an advantage.

💡Deep Fakes

Deep fakes refer to synthetic media in which a person's likeness is replaced with another's using artificial intelligence. While the video doesn't go into detail about deep fakes, it mentions them as one of the many new technologies the speaker has experimented with to create short films. Deep fakes are part of a broader conversation about the capabilities of AI in manipulating visual content.

💡3D Scanning

3D scanning is the process of analyzing a real-world object or environment to collect data on its shape and possibly its appearance (such as color). The data is then used to construct a digital 3D model. In the video, 3D scanning is highlighted as a favorite tool of the speaker for creating short films, and it's used to demonstrate the limitations of traditional scanning when compared to the capabilities of NeRF.

💡Photorealism

Photorealism is the quality of an image or a rendering that is so lifelike and accurate in its representation that it resembles a photograph. The pursuit of photorealism is a significant theme in the video, as the speaker discusses how NeRF technology can achieve this level of detail with reflections and transparency that are difficult to replicate using traditional rendering methods.

💡NVIDIA Instant NeRF

NVIDIA Instant NeRF is a program developed by NVIDIA that allows for the creation of Neural Radiance Fields from a set of photographs. It's mentioned in the video as the starting point of the speaker's journey with NeRF technology. The program was initially complex to use, requiring coding and command terminal operations, but has since become more accessible.

💡Luma AI

Luma AI is a service mentioned in the video that simplifies the process of creating Neural Radiance Fields. Users can upload a series of photos to Luma AI's server, and after a short processing time, receive a NeRF. This service is highlighted as a significant advancement in making NeRF technology more accessible and easier to use for creators.

💡Camera Animation

Camera animation refers to the process of moving a virtual camera within a 3D environment to create dynamic and engaging shots. In the context of the video, the speaker discusses the ability to import custom camera animation into the NeRF technology, which opens up possibilities for creating more complex and cinematic shots using the generated 3D scenes.

💡Background Replacement

Background replacement is a technique used in video production where the background of a subject is removed and replaced with a different image or video. The video discusses using NeRF technology for background replacement, particularly in the context of green screen shots, to create more realistic and dynamic scenes.

💡Portals

In the video, the concept of 'portals' is explored as a creative application of NeRF technology. The speaker imagines turning a door into a portal to another world by using NeRF to manipulate the 3D scene after the fact. This showcases the potential for NeRF to create fantastical and immersive environments that were not possible with traditional photogrammetry.

💡Inception Shot

The 'Inception Shot' refers to a famous scene from the movie 'Inception' where the city of Paris appears to fold over onto itself. The video suggests using NeRF technology to create a similar effect, which would be much less labor-intensive than traditional methods. This demonstrates the potential of NeRF for creating complex and visually stunning effects with relative ease.

Highlights

A new technology called Neural Radiance Fields (Nerf) is set to revolutionize filmmaking with its ability to create photorealistic images quickly and with minimal effort.

Nerf technology allows for the creation of 3D models with accurate reflections and transparency from a set of photos in mere minutes.

Photo scanning has been a shortcut for 3D scene rendering, but Nerf technology takes it a step further by automatically handling lighting and material reflections.

Objects with complex reflections, such as a chrome ball, which are impossible to scan with traditional methods, can be captured using Nerf technology.

Nerf relies on neural rendering, similar to deep fakes, to learn the color of every point in 3D space based on the viewer's perspective.

The technology can replicate reality in a way that looks like video, offering a new level of photorealism in CGI.

Nerf technology can be used for simple tasks like background replacement in green screen scenarios.

The technology enables the creation of portals and other complex visual effects with ease.

Nerf scans work exceptionally well in low-light conditions where photo scanning typically fails.

Reflections and subtle lighting changes in Nerf scans contribute to the photorealistic quality of the images.

Nerf technology can scale scenes up or down, opening up possibilities for creative shots and perspectives.

The lighting conditions in which the Nerf scan is captured can influence the final photorealistic outcome.

Nerf scans from different cameras, like a RED camera versus a webcam, can result in varying levels of photorealism and aesthetic quality.

The neural render provided by Nerfs is more valuable than the extracted geometry, as it retains the reflective properties of the scan.

Nerf technology can be used to create collision geometry for simulations, combining the benefits of photogrammetry with neural rendering.

The potential of Nerf technology is in its ability to be treated like video footage, offering a new approach to filmmaking and visual effects.

Despite current limitations, the potential of Nerf technology is vast, and it is expected to become increasingly indistinguishable from actual video in the future.

The technology is still in its early stages, but with advancements, it could significantly change the way visual effects and filmmaking are approached.