Why THIS is the Future of Imagery (and Nobody Knows it Yet)
TLDRThe video explores the revolutionary potential of Neural Radiance Fields (NeRF) in transforming the future of imagery and filmmaking. The host, having experimented with various technologies like deep fakes and 3D scanning, introduces NeRF as a game-changer that can render photorealistic 3D models from a series of photos in mere minutes. The video demonstrates the technology's ability to handle complex reflections and transparencies, which are challenging for traditional photo scanning. It also highlights the ease of use with new apps like Luma AI, which simplifies the process to a few minutes. The host showcases various creative applications, such as background replacement, creating portals, and scaling objects within the scene. The video concludes with the potential of NeRF to revolutionize visual effects, with endorsements from industry experts like Paul Franklin, an Oscar-winning VFX artist. The host encourages artists to embrace and push the boundaries of this technology.
Takeaways
- 🎬 The video discusses the potential of a new technology called Neural Radiance Fields (NRF) to revolutionize filmmaking with its ability to quickly and easily create photorealistic 3D renderings.
- 🚀 NRF technology can produce high-quality renders in minutes, which traditionally would require a significant amount of time and effort using CGI methods.
- 🤖 The creator mentions using various technologies like deep fakes, virtual production, and 3D scanning in his work, highlighting the ongoing evolution of tech in the film industry.
- 📸 Photo scanning, while useful, has limitations, particularly with reflective or transparent objects, which NRF technology aims to overcome.
- 🌟 Photorealism in CGI is achieved through accurate reflections, and NRF leverages neural rendering to capture how light interacts with objects, thus creating more convincing imagery.
- 📹 NRF technology can be used for various applications like background replacement, creating portals to other worlds, and generating complex camera movements.
- 🎥 The video features a sponsored segment for the movie 'Bones and All', indicating the integration of commercial interests with content creation.
- 🌆 NRF works exceptionally well in different lighting conditions, including nighttime scenes, where traditional photo scanning falls short.
- 📱 The process of creating a NRF has been simplified to be as easy as using a phone app, thanks to advancements by companies like Luma AI.
- 🔍 The quality of the original scan, including the camera used, significantly impacts the final NRF, with higher quality cameras producing more cinematic results.
- 🔧 Despite current limitations, such as the inability to extract reflective geometry without losing details, the potential for growth and development in NRF technology is immense.
- ⏳ The creator expresses optimism about the future of NRF, envisioning a time when the distinction between NRF and actual video will be indistinguishable.
Q & A
What is the main topic of the video?
-The main topic of the video is the introduction and potential impact of a new technology called Neural Radiance Fields (NRFs) on the future of imagery and filmmaking.
What does the acronym 'Nerf' stand for in the context of the video?
-In the context of the video, 'Nerf' stands for Neural Radiance Fields, which is a technology that enables the creation of highly realistic 3D renderings from a set of 2D images.
How does the video describe the process of creating a Neural Radiance Field?
-The video describes the process as taking a set of photos, processing them into a neural Radiance Field using software like Luma AI or Nvidia's Instant NeRF, and then receiving a highly realistic 3D rendering that can be manipulated and viewed from different angles.
What are some of the limitations of photo scanning mentioned in the video?
-The limitations of photo scanning mentioned in the video include the inability to accurately scan objects with many reflections or transparent materials, as well as the need for additional effort to set up lighting and correct materials for rendering 3D scenes.
How does the video suggest using Neural Radiance Fields for filmmaking?
-The video suggests using Neural Radiance Fields for tasks such as background replacement, creating portals to other worlds, and post-production adjustments like scaling scenes to make objects appear larger or smaller, all with a high degree of photorealism.
What is the significance of reflections in achieving photorealism, as discussed in the video?
-Reflections are significant in achieving photorealism because they play a crucial role in convincing our brains that the imagery is real. Every object reflecting light from every other object in a scene contributes to the overall realism of the image.
How does the video compare photo scanning with Neural Radiance Fields?
-The video compares photo scanning with Neural Radiance Fields by demonstrating that while photo scanning can produce 3D models quickly, it still requires significant effort for lighting and material adjustments. In contrast, Neural Radiance Fields can capture reflections and transparency more accurately, with less post-processing needed.
What is the role of lighting in the quality of a Neural Radiance Field?
-Lighting plays a critical role in the quality of a Neural Radiance Field. Capturing both the plate and the NeRF under the same lighting conditions and with the same camera can help ensure that the final rendering matches the original scene in terms of lighting and mood.
How does the video demonstrate the potential of Neural Radiance Fields for post-production?
-The video demonstrates the potential of Neural Radiance Fields for post-production by showing how the technology can be used to easily replace backgrounds, create complex visual effects like portals, and manipulate scenes to achieve cinematic shots that would be difficult or time-consuming with traditional methods.
What is the relationship between the quality of the camera used and the resulting Neural Radiance Field?
-The quality of the camera used has a direct impact on the resulting Neural Radiance Field. High-quality cameras with better dynamic range and lens quality will produce more cinematic and higher-resolution NeRFs, while lower-quality cameras like webcams may result in a cheaper, less refined look.
What are some of the future possibilities for Neural Radiance Fields that the video alludes to?
-The video alludes to future possibilities for Neural Radiance Fields such as improved rendering quality to the point where it's indistinguishable from real video, the ability to apply post-effects like motion blur and depth of field, and the potential for using NeRFs as collision geometry for simulations.
Outlines
🎬 Introduction to Neural Radiance Fields in Filmmaking
The video begins with an introduction to the concept of Neural Radiance Fields (NRF), a new technology that promises to revolutionize filmmaking by enabling the creation of photorealistic CGI in a fraction of the time and effort traditionally required. The speaker discusses their background in experimenting with new technologies to create short films and highlights their experience with photo scanning, a technique that has been a shortcut in the rendering process but still requires significant effort to set up lighting and materials. The limitations of photo scanning, particularly with reflective and transparent objects, are also discussed, setting the stage for the introduction of NRF.
🚀 NRF Technology and Its Impact on Visual Effects
The speaker dives into the potential of NRF technology, explaining how it captures the subtleties of light reflections and transparency, which are crucial for photorealism. They demonstrate the process of creating a NRF from a set of photos, highlighting the initial results and the improvements made possible by the technology. The video also features a response from Paul Franklin, a renowned visual effects artist, who sees a VFX revolution on the horizon. The discussion then explores the principles of photorealism, emphasizing the importance of reflections in creating realistic images and how NRF technology leverages neural rendering to achieve this effect.
🎥 Practical Applications of NRF in Film and Video Production
The video showcases practical applications of NRF technology in film and video production. It discusses the ease of use with new tools like Luma AI, which simplifies the process to the point of using a phone app. The speaker demonstrates how NRF can be used for background replacement, creating portals to other worlds, and other visual effects that were previously complex to achieve. They also touch on the ability to import custom camera animations and the potential for using NRF in night scenes, where traditional photo scanning falls short. The limitations of extracting geometry from a NRF without the reflective properties are also mentioned.
🌟 The Future of NRF and Its Creative Potential
The final paragraph outlines the future potential of NRF technology and encourages artists to explore and push the boundaries of this new tech. The speaker shares their experiments with camera movements, including a complex 'Inception' style shot, and discusses the current limitations and the potential for future improvements. They also mention the importance of capturing both the plate and the NRF under the same lighting conditions for the best results. The video concludes by highlighting the excitement around NRF and the opportunities it presents for creators, suggesting a future where the line between NRF and actual video footage becomes indistinguishable.
Mindmap
Keywords
💡Neural Radiance Fields (Nerf)
💡Photogrammetry
💡Photorealism
💡3D Scanning
💡Deep Fakes
💡Virtual Production
💡Reflections
💡Transparency
💡Luma AI
💡Background Replacement
💡Inception Shot
Highlights
A new technology called Neural Radiance Fields (Nerf) is set to revolutionize filmmaking by creating photorealistic CGI in minutes.
Nerf technology allows for quick, easy, and cost-effective replication of reality, similar to video footage.
Photo scanning has been a shortcut for rendering 3D scenes, but Nerf addresses the limitations of photo scanning, especially with reflective and transparent objects.
Nerf uses neural rendering to learn the color of every point in 3D space based on the viewer's perspective, resulting in highly realistic reflections.
The potential of Nerf technology was recognized by Paul Franklin, a two-time Oscar winner for best visual effects.
Nerf technology can be used for simple tasks like background replacement in green screen scenarios.
Creating portals to other worlds is one of the creative applications of Nerf technology, allowing for unique and immersive experiences.
Nerf technology can handle complex camera movements and can be used to create cinematic shots with ease.
Nerf scans can be combined with camera animation to create dynamic and realistic scenes.
The reflective properties captured by Nerf technology are what sell the realism of the imagery, as they mimic how light works in the real world.
Nerf technology can scale scenes up or down, opening up possibilities for creating giant or miniature worlds.
The lighting conditions in which Nerf scans are captured can affect the final photorealistic outcome, emphasizing the importance of matching lighting between the scan and the plate.
Nerf scans from different cameras, such as a RED camera versus a webcam, can result in different visual qualities, reflecting the cinematic or cheap look based on the source.
Extracting geometry from a Nerf scan is possible but loses the reflective properties, as they are baked down into a single diffuse texture.
Nerf technology is most powerful when used like video footage rather than as a source for textures and models.
The potential applications of Nerf technology are vast, including complex effects like the folding city scene from the movie Inception.
Nerf technology is in its early stages, with tools currently being rudimentary, but the potential for growth and development is immense.
The future of Nerf technology is promising, with advancements likely making it indistinguishable from actual video in terms of realism.