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

Corridor Crew
20 Nov 202216:49

TLDRThe video explores the revolutionary impact of Neural Radiance Fields (NeRFs) on the future of imagery and filmmaking. The host demonstrates how NeRFs, a new technology, can create photorealistic 3D models from a series of photos in mere minutes, which traditionally required significant effort and time. The video showcases the process of creating a NeRF from photos, the importance of reflections in achieving photorealism, and how NeRFs use neural rendering to capture the color of every point in 3D space from different viewing angles. The host also discusses the potential applications of NeRFs, such as background replacement, creating portals to other worlds, and post-production adjustments without needing to reshoot scenes. The video concludes with a vision of the technology's potential, suggesting that soon, it may be impossible to distinguish between a NeRF-rendered image and actual video footage.

Takeaways

  • 🎬 The video discusses the future of imagery with the advent of a new technology called Neural Radiance Fields (NRF), which is poised to revolutionize filmmaking.
  • 🚀 NRF allows for the creation of photorealistic images and videos with a fraction of the time and effort traditionally required for CGI rendering.
  • 📸 Photo scanning, while powerful, has limitations, especially with reflective and transparent objects, which NRF aims to overcome.
  • 🤔 The secret to photorealism in CGI is accurate reflections, and NRF technology leverages neural rendering to achieve this, making it appear as realistic as the original photos.
  • 🌟 NRF has the potential to change the way visual effects are created, as noted by Paul Franklin, a two-time Oscar winner for best visual effects.
  • 📱 Advances in technology have made NRF more accessible, with tools like Luma AI and Polycam allowing users to create NRFs using just a series of photos.
  • 🌃 NRF technology works exceptionally well in various lighting conditions, including challenging low-light scenarios where photo scanning often falls short.
  • 🔄 The ability to manipulate NRFs post-capture allows for creative applications such as background replacement, creating portals, and scaling objects within a scene.
  • 🎥 NRFs can be combined with camera animation to produce complex and dynamic shots that would be difficult or impossible to achieve with traditional photogrammetry.
  • 📹 The quality of the original capture, including the camera used, significantly impacts the final NRF, with higher quality cameras producing more cinematic results.
  • 🔍 While NRFs can be used to extract geometry, the reflective properties are lost in the process, emphasizing the importance of the neural render over the geometric model.

Q & A

  • What is the main technology discussed in the video?

    -The main technology discussed in the video is Neural Radiance Fields (NeRF), which is a new method for creating photorealistic 3D renderings from a set of 2D images.

  • How does NeRF technology differ from traditional photo scanning?

    -Unlike traditional photo scanning, which requires significant effort to set up lighting and materials, NeRF uses neural rendering to understand how light interacts with objects. It can handle complex reflections and transparencies, which are often difficult or impossible to capture with photo scanning.

  • What is the significance of reflections in achieving photorealism?

    -Reflections play a crucial role in achieving photorealism because they help convince our brains that the rendered image is real. Every object reflecting light from every other object contributes to the overall realism of a scene.

  • How does NeRF technology handle objects with complex reflections like a chrome ball?

    -NeRF technology can accurately represent the reflections on a chrome ball by using neural rendering to learn the color of every point in 3D space based on the viewer's perspective, resulting in realistic reflections without the need for additional CG lighting.

  • What is the potential impact of NeRF on the film and visual effects industry?

    -NeRF has the potential to revolutionize the film and visual effects industry by enabling the creation of highly realistic 3D scenes with significantly less time and effort compared to traditional CGI methods.

  • How does the video demonstrate the ease of use of NeRF technology?

    -The video demonstrates the ease of use of NeRF technology by showing how it can be processed from a set of photos into a NeRF using Luma AI, which simplifies the process to the point of using a phone app or a web service.

  • What are some creative applications of NeRF technology shown in the video?

    -The video shows creative applications of NeRF technology such as background replacement, creating portals to other worlds, and scaling objects or scenes to make someone appear larger or smaller.

  • How does capturing lighting conditions affect the final NeRF scan?

    -Capturing both the plate and the NeRF under the same lighting conditions and ideally with the same camera ensures that the final scan matches the original footage in terms of lighting, resulting in a more photorealistic outcome.

  • 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 reflectiveness, as all the details are baked down into a single diffuse texture, which does not change when viewed from different angles.

  • How does the video suggest the potential future of NeRF technology?

    -The video suggests that the future of NeRF technology could involve advanced features like motion blur and depth of field adjustments within the NeRF program, and that it will become increasingly difficult to distinguish between a NeRF and actual video.

  • What is the recommendation made by the video for those interested in NeRF technology?

    -The video recommends using Luma AI for those interested in NeRF technology, and also mentions that NVIDIA's instant NeRF and a partnership with Polycam offer additional options for working with NeRF technology.

Outlines

00:00

🎬 Introduction to Neural Radiance Fields (Nerf) in Filmmaking

The video begins with the sponsorship acknowledgment and introduces the concept of Neural Radiance Fields (Nerf), a new technology that promises to revolutionize filmmaking. The speaker discusses the limitations of traditional CGI and photo scanning, highlighting the challenges of achieving photorealism and the difficulties in scanning reflective or transparent objects. The speaker then demonstrates the process of creating a Nerf from a set of photos, noting the initial results' imperfections but also the potential for realistic reflections and transparency. The video also mentions the responses from visual effects professionals, indicating the technology's potential to change the VFX industry.

05:02

🎥 Nerf Technology and Its Applications in Video Production

The second paragraph delves into the practical applications of Nerf technology in video production. It discusses the ease of creating a Nerf using Luma AI and the ability to import custom camera animations. The speaker explores various uses of Nerfs, such as background replacement, creating portals to other worlds, and manipulating the scale of objects within a scene. The importance of reflections in achieving photorealism is emphasized, and the potential for using Nerfs in night scenes, where traditional photo scanning falls short, is highlighted. The limitations of extracting geometry from a Nerf without the reflective properties are also mentioned.

10:03

🌆 Outdoor Nerf Capture and the Impact of Camera Quality

In this section, the speaker attempts to capture a large building using Nerf technology with the aim of compositing a person into the scene. The importance of matching lighting conditions between the plate and the Nerf is stressed to achieve a cohesive look. An experiment comparing scans from a high-quality camera versus a webcam is conducted, demonstrating the impact of camera quality on the final Nerf. The speaker also discusses the potential of using complex camera movements and the limitations when extracting geometry from a Nerf. The potential for using Nerfs in simulations and the current limitations of the technology are also touched upon.

15:05

📽 Final Thoughts on the Potential of Nerf Technology

The final paragraph reflects on the potential and current state of Nerf technology. The speaker expresses optimism about the future of the technology and encourages artists to explore and push its boundaries. The video showcases a range of experimental shots to inspire viewers, emphasizing that while the technology is not yet production-ready, it offers a glimpse into the possibilities it holds. The speaker recommends resources for further exploration, such as Luma and Nvidia's instant Nerf, and highlights the importance of staying informed about the technology's development.

Mindmap

Keywords

💡Neural Radiance Fields (Nerf)

Neural Radiance Fields (Nerf) is a groundbreaking technology in computer graphics that allows for the creation of highly realistic 3D scenes from a collection of 2D images. It achieves this by using machine learning to infer how light interacts with the environment and objects within it. In the video, Nerf is used to quickly generate photorealistic renders that would traditionally require significant time and effort in CGI. The technology is showcased as a potential game-changer for filmmaking due to its ability to replicate reality in a way that looks like video.

💡Photogrammetry

Photogrammetry is a technique that uses photographs to create 3D models or to calculate the distance between objects. It's often used in film and video production to generate 3D models from real-world objects. In the context of the video, photogrammetry is compared to Nerf, highlighting the limitations such as the inability to perfectly capture reflections and transparent objects, which Nerf technology can handle more effectively.

💡Photorealism

Photorealism refers to the quality of an image or visual representation that closely resembles the complexity and detail of real-life imagery. It is a key goal for many in computer graphics and visual effects. The video emphasizes the importance of reflections in achieving photorealism, as they play a crucial role in convincing the viewer that what they are seeing is real. Nerf technology is highlighted as a means to achieve photorealism more easily and quickly.

💡Deep Fakes

Deep Fakes is a term used to describe the use of AI and machine learning to create convincing video or audio of people saying or doing things they never actually did. In the video, deep fakes are mentioned as one of the many technologies the creator has experimented with, and it is used as a comparison point to illustrate how Nerf technology uses similar neural rendering techniques to create realistic visuals.

💡3D Scanning

3D scanning is the process of analyzing a real-world object to collect data on its shape and possibly its appearance (color, texture, etc.). The data is then used to construct a 3D model of the object. In the video, 3D scanning is discussed as a tool that has been used in the past to create 3D models from photographs, but it is noted that it has limitations when it comes to capturing certain materials and reflections, which Nerf technology can better handle.

💡NVIDIA's Instant Nerf

NVIDIA's Instant Nerf is a program that utilizes Neural Radiance Fields to generate 3D representations from a set of photographs. It represents a significant advancement in making Nerf technology more accessible. In the video, the creator discusses their initial experience with the program, which required coding and command-line interface, but has since become more user-friendly with advancements like Luma AI.

💡Luma AI

Luma AI is a platform that simplifies the process of creating Neural Radiance Fields. It allows users to upload photographs and receive a Nerf in return, greatly reducing the technical barrier to entry. The video script mentions Luma AI as a tool that has made working with Nerfs as easy as using a phone app, highlighting its role in democratizing access to advanced visual effects technology.

💡Background Replacement

Background replacement is a technique used in video production where the background of a subject is removed or replaced with a different image or video. In the context of the video, the creator demonstrates how Nerf technology can be used to easily replace the background of a scene, even when the camera is moving, which is traditionally challenging with standard green screen techniques.

💡Portals

In the video, the concept of 'portals' refers to a creative application of Nerf technology where a door or other object in the scene is transformed into a gateway to another world or environment. This is achieved by using the 3D tracking data from the original scene and applying it to a Nerf, allowing for the creation of seemingly impossible visuals with relative ease.

💡Camera Animation

Camera animation refers to the movement and positioning of a camera within a scene, which can greatly affect the final appearance of the footage. The video discusses the ability to import custom camera animation into Nerf technology, opening up possibilities for more dynamic and complex visuals. This feature allows creators to match the camera movements from one scene to another, creating seamless transitions and composites.

💡Inception Shot

The 'Inception Shot' refers to a specific visual effect from the movie 'Inception,' where the city of Paris appears to fold over onto itself. In the video, the creator attempts to recreate a similar effect using Nerf technology, demonstrating the potential for complex and innovative visual storytelling. This experiment shows how Nerf can be used to achieve advanced visual effects with less effort than traditional methods.

Highlights

Neural Radiance Fields (Nerf) is a new technology that can create photorealistic 3D renderings in minutes.

Nerf technology has the potential to revolutionize filmmaking by simplifying and expediting the process of creating 3D scenes.

Photo scanning has traditionally been limited by the need for consistent lighting and material appearance.

Nerf addresses the limitations of photo scanning by handling complex reflections and transparent objects that are difficult to scan.

Nerf uses neural rendering to learn the color of every point in 3D space based on the viewer's perspective, achieving photorealism.

Visual effects artists are excited about the potential of Nerfs due to their ability to replicate reality with high accuracy.

Nerfs can be used for simple tasks like background replacement with ease, thanks to advancements in user-friendly applications.

The technology allows for creative applications such as creating portals to other worlds by applying camera moves to Radiance Fields.

Nerfs work exceptionally well at night, where traditional photo scanning falls short.

Reflections and lighting play a crucial role in convincing the viewer of the realism of a scene, which Nerfs handle effectively.

The quality of the camera used to capture the Nerf can influence the final scan's look, with higher quality cameras producing more cinematic results.

Nerfs can be manipulated post-capture, allowing for complex camera moves and effects that would be difficult to achieve in real filming.

Extracting geometry from a Nerf results in a loss of reflectiveness, as it converts the data into a single diffuse texture.

Nerfs are most powerful when used like video footage, rather than as a source for textures and models.

The technology is still in its early stages, with tools being basic and results sometimes imperfect, but the potential is vast.

Nerfs could potentially make it indistinguishable from actual video, representing a significant leap in visual effects capabilities.

Artists are encouraged to explore and push the boundaries of Nerf technology to unlock its full creative potential.

Luma AI and NVIDIA's instant Nerf are mentioned as tools that have made working with Nerfs more accessible and easier.

The future of Nerf technology is promising, with ongoing development and partnerships that will likely enhance its capabilities.