Gaussian Splatting – A$AP Rocky "Helicopter" music video

21 days ago (radiancefields.com)

https://www.youtube.com/watch?v=g1-46Nu3HxQ

Hi,

I'm David Rhodes, Co-founder of CG Nomads, developer of GSOPs (Gaussian Splatting Operators) for SideFX Houdini. GSOPs was used in combination with OTOY OctaneRender to produce this music video.

If you're interested in the technology and its capabilities, learn more at https://www.cgnomads.com/ or AMA.

Try GSOPs yourself: https://github.com/cgnomads/GSOPs (example content included).

  • I’m fascinated by the aesthetic of this technique. I remember early versions that were completely glitched out and presented 3d clouds of noise and fragments to traverse through. I’m curious if you have any thoughts about creatively ‘abusing’ this tech? Perhaps misaligning things somehow or using some wrong inputs.

  • I remember splatting being introduced as a way to capture real life scenes, but one of the links you have provided in this discusson seems to have used a traditional polygon mesh scene as training input for the splat model. How common is this and why would one do it that way over e.g. vertex shader effects that give the mesh a splatty aesthetic?

    • Yes, it's quite trivial to convert traditional CG to Gaussian splats. We can render our scenes/objects just as we would capture physical spaces. The additional benefits of using synthetic data is 100% accurate camera poses (alignment) which means the structure from motion (SfM) step can be bypassed.

      It's also possible to splat from textured meshes directly, see: https://github.com/electronicarts/mesh2splat. This approach yields high quality, PBR compatible splats, but is not quite as efficient as a traditional training workflow. This approach will likely become mainstream in third party render engines, moving forward.

      Why do this? 1. Consistent, streamlined visuals across a massive ecosystem, including content creation tools, the web, and XR headsets. 2. High fidelity, compressed visuals. With SOGs compression, splats are going to become the dominant 3D representation on the web (see https://superspl.at). 3. E-commerce (product visualizations, tours, real-estate, etc.) 4. Virtual production (replace green screens with giant LED walls). 5. View-dependent effects without (traditional) shaders or lighting

      It's not just about the aesthetic, it's also about interoperability, ease of use, and the entire ecosystem.

  • From the article:

    >Evercoast deployed a 56 camera RGB-D array

    Do you know which depth cameras they used?

    • We (Evercoast) used 56 RealSense D455s. Our software can run with any camera input, from depth cameras to machine vision to cinema REDs. But for this, RealSense did the job. The higher end the camera, the more expensive and time consuming everything is. We have a cloud platform to scale rendering, but it’s still overall more costly (time and money) to use high res. We’ve worked hard to make even low res data look awesome. And if you look at the aesthetic of the video (90s MTV), we didn’t need 4K/6K/8K renders.

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    • Couldn’t you just use iphone pros for this? I developed an app specifically for photogrammetry capture using AR and the depth sensor as it seemed like a cheap alternative.

      EDIT: I realize a phone is not on the same level as a red camera, but i just saw iphones as a massively cheaper option to alternatives in the field i worked in.

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  • Hi David, have you looked into alternatives to 3DGS like https://meshsplatting.github.io/ that promise better results and faster training?

    • I have. Personally, I'm a big fan of hybrid representations like this. An underlying mesh helps with relighting, deformation, and effective editing operations (a mesh is a sparse node graph for an otherwise unstructured set of data).

      However, surface-based constraints can prevent thin surfaces (hair/fur) from reconstructing as well as vanilla 3DGS. It might also inhibit certain reflections and transparency from being reconstructed as accurately.

  • Random question, since I see your username is green.

    How did you find out this was posted here?

    Also, great work!

    • My friend and colleague shared a link with me. Pretty cool to see this trending here. I'm very passionate about Gaussian splatting and developing tools for creatives.

      And thank you!

  • I've been mesmerized by the visusals of Gaussian splatting for a while now, congratulations for your great work!

    Do you have some benchmarks about what is the geometric precision of these reproductions?

    • Thank you!

      Geometric analysis for Gaussian splatting is a bit like comparing apples and oranges. Gaussian splats are not really discrete geometry, and their power lies in overlapping semi-transparent blobs. In other words, their benefit is as a radiance field and not as a surface representation.

      However, assuming good camera alignment and real world scale enforced at the capture and alignment steps, the splats should match real world units quite closely (mm to cm accuracy). See: https://www.xgrids.com/intl?page=geomatics.

  • nice work.

    I can see that relighting is still a work in progress, as the virtual spot lights tends to look flat and fake. I understand that you are just making brighter splats that fall inside the spotlight cone and darker the ones behind lots of splats.

    Do you know if there are plans for gaussian splats to capture unlit albedo, roughness and metalness? So we can relight in a more realistic manner?

    Also, environment radiosity doesnt seem to translate to the splats, am I right?

    Thanks

    • Thank you!

      There are many ways to relight Gaussian splats. However, the highest quality results are currently coming from raytracing/path tracing render engines (such as Octane and VRay), with 2D diffusion models in second place. Relighting with GSOPs nodes does not yield as high quality, but can be baked into the model and exported elsewhere. This is the only approach that stores the relit information in the original splat scene.

      That said, you are correct that in order to relight more accurately, we need material properties encoded in the splats as well. I believe this will come sooner than later with inverse rendering and material decomposition, or technology like Beeble Switchlight (https://beeble.ai). This data can ultimately be predicted from multiple views and trained into the splats.

      "Also, environment radiosity doesnt seem to translate to the splats, am I right?"

      Splats do not have their own radiosity in that sense, but if you have a virtual environment, its radiosity can be translated to the splats.

    • Back in 2001 I was the math consultant for "A Beautiful Mind". One spends a lot of time waiting on a film set. Eventually one wonders why.

      The majority of wait time was the cinematographer lighting each scene. I imagined a workflow where secondary digital cameras captured 3D information, and all lighting took place in post production. Film productions hemorrhage money by the second; this would be a massive cost saving.

      I described this idea to a venture capitalist friend, who concluded one already needed to be a player to pull this off. I mentioned this to an acquaintance at Pixar (a logical player) and they went silent.

      Still, we don't shoot movies this way. Not there yet...

I want to shoutout Nial Ashley (aka Llainwire) for doing this in 2023 as a solo act and doing the visuals himself as well - https://www.youtube.com/watch?v=M1ZXg5wVoUU

A shame that kid was slept on. Allegedly (according to discord) he abandoned this because so many artists reached out to have him do this style of mv, instead of wanting to collaborate on music.

  • > so many artists reached out to have him do this style of mv, instead of wanting to collaborate on music

    Well yes, the visuals are awesome, while the music… isn’t.

    • I love HN because everyone is so different outside of the core purpose of the site. Sometimes people reference art, or a book or something, that I'd never would think to exist.

      Llainwire was my top artist listens throughout 2023, so it’s always funny to bump into reactions that feel totally different from my world/my peers.

  • This is sooo sick. I’m a total hip hop unc and haven’t caught up for a decade and a half now and I think the music is great as well. Pairs perfectly with the visuals. Hope this guy makes it, a creative one of one.

    His stuff is already on repeat. Thanks for the recc, love this site.

  • You're saying Nial used guassian splatting for his video? Or the style of camerawork, staging, and costuming is similar?

    Put another way, is this a scientific comparison or an artistic comparison?

    • It sounds like to me he [artist] was disappointed that more people were interested in his video editing than his musical efforts.

Never did I think I would ever see anything close to related to A$AP on HN. I love this place.

Super cool to read but can someone eli5 what Gaussian splatting is (and/or radiance fields?) specifically to how the article talks about it finally being "mature enough"? What's changed that this is now possible?

  • 1. Create a point cloud from a scene (either via lidar, or via photogrammetry from multiple images)

    2. Replace each point of the point cloud with a fuzzy ellipsoid, that has a bunch of parameters for its position + size + orientation + view-dependent color (via spherical harmonics up to some low order)

    3. If you render these ellipsoids using a differentiable renderer, then you can subtract the resulting image from the ground truth (i.e. your original photos), and calculate the partial derivatives of the error with respect to each of the millions of ellipsoid parameters that you fed into the renderer.

    4. Now you can run gradient descent using the differentiable renderer, which makes your fuzzy ellipsoids converge to something closely reproducing the ground truth images (from multiple angles).

    5. Since the ellipsoids started at the 3D point cloud's positions, the 3D structure of the scene will likely be preserved during gradient descent, thus the resulting scene will support novel camera angles with plausible-looking results.

  • Gaussian splatting is a way to record 3-dimensional video. You capture a scene from many angles simultaneously and then combine all of those into a single representation. Ideally, that representation is good enough that you can then, post-production, simulate camera angles you didn't originally record.

    For example, the camera orbits around the performers in this music video are difficult to imagine in real space. Even if you could pull it off using robotic motion control arms, it would require that the entire choreography is fixed in place before filming. This video clearly takes advantage of being able to direct whatever camera motion the artist wanted in the 3d virtual space of the final composed scene.

    To do this, the representation needs to estimate the radiance field, i.e. the amount and color of light visible at every point in your 3d volume, viewed from every angle. It's not possible to do this at high resolution by breaking that space up into voxels, those scale badly, O(n^3). You could attempt to guess at some mesh geometry and paint textures on to it compatible with the camera views, but that's difficult to automate.

    Gaussian splatting estimates these radiance fields by assuming that the radiance is build from millions of fuzzy, colored balls positioned, stretched, and rotated in space. These are the Gaussian splats.

    Once you have that representation, constructing a novel camera angle is as simple as positioning and angling your virtual camera and then recording the colors and positions of all the splats that are visible.

    It turns out that this approach is pretty amenable to techniques similar to modern deep learning. You basically train the positions/shapes/rotations of the splats via gradient descent. It's mostly been explored in research labs but lately production-oriented tools have been built for popular 3d motion graphics tools like Houdini, making it more available.

    • Thanks for the explanation! It makes a lot of sense that voxels would scale as badly as they do, especially if you want to increase resolution. Am I right in assuming that the reason this scales a lot better is because the Gaussian splats, once there's enough "resolution" of them, can provide the estimates for how light works reasonably well at most distances? What I'm getting at is, if I can see Gaussian splats vs voxels similarly to pixels vs vector graphics in images?

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    • Are meshes not used instead of gaussian splats only due to robustness reasons? I.e., if there were a piece of software that could reliably turn a colored point cloud into a textured mesh, would that be preferable?

      3 replies →

    • > Gaussian splatting is a way to record 3-dimensional video.

      I would say it's a 3D photo, not a 3D video. But there are already extensions to dynamic scenes with movement.

      2 replies →

  • It’s a point cloud where each point is a semitransparent blob that can have a view dependent color: color changes depending on direction you look at them. Allowing to capture reflections, iridescence…

    You generate the point clouds from multiple images of a scene or an object and some machine learning magic

  • For the ELI5, Gaussian splatting represents the scene as millions of tiny, blurry colored blobs in 3D space and renders by quickly "splatting" them onto the screen, making it much faster than computing an image by querying a neural net model like radiance fields.

    I'm not up on how things have changed recently

  • I found this VFX breakdown of the recent Superman movie to have a great explanation of what it is and what it makes possible: https://youtu.be/eyAVWH61R8E?t=232

    tl;dr eli5: Instead of capturing spots of color as they would appear to a camera, they capture spots of color and where they exist in the world. By combining multiple cameras doing this, you can make a 3D works from footage that you can then zoom a virtual camera round.

Hello! I’m Chris Rutledge, the post EP / cg supervisor at Grin Machine. Happy to answer any questions. Glad people are enjoying this video, was so fun to get to play with this technique and help break it into some mainstream production

  • Awesome work, incredibly well done! What was the process like for setting the direction on use of these techniques with Rakim? Were you basically just trusted to make something great or did they have a lot of opinions on the technicalities?

    • I didn’t interface much with Rocky outside of the shoot, our director Dan was talking to him regularly and he certainly had options and great ideas but mostly left it up to us. All of the creative came from Dan and bouncing ideas off us / trying things and seeing what was possible with this tech. By the end of the process it was awesome to get Dan also into blender helping set up camera moves himself, in addition to finessing the edit and animatic to help point us in the right direction.

Really amazing video. Unfortunately this article is like 60% over my head. Regardless, I actually love reading jargon-filled statements like this that are totally normal to the initiated but are completely inscrutable to outsiders.

    "That data was then brought into Houdini, where the post production team used CG Nomads GSOPs for manipulation and sequencing, and OTOY’s OctaneRender for final rendering. Thanks to this combination, the production team was also able to relight the splats."

  • Hi, I'm one of the creators of GSOPs for SideFX Houdini.

    The gist is that Gaussian splats can replicate reality quite effectively with many 3D ellipsoids (stored as a type of point cloud). Houdini is software that excels at manipulating vast numbers of points, and renderers (such as Octane) can now leverage this type of data to integrate with traditional computer graphics primitives, lights, and techniques.

    • Can you put "Gaussing splats" in some kind of real world metaphor so I can understand what it means? Either that or explain why "Gaussian" and why "splat".

      I am vaguely aware of stuff like Gaussian blur on Photoshop. But I never really knew what it does.

      9 replies →

  • My bad! I am the author. Gaussian splatting allows you to take a series of normal 2D images or a video and reconstruct very lifelike 3D from it. It’s a type of radiance field, like NeRFs or voxel based methods like Plenoxels!

> many viewers focused on the chaos, the motion, and the unmistakable early MTV energy of the piece

It certainly moves around a lot!

It certainly looks like the tech and art style here are indissociable. Not only the use of Gaussian Splats made such extreme camera movement possible, one can be argued that it made them necessary.

Pause the video and notice the blurriness and general lack of details. But the frantic motion doesn't let the viewer focus on this details, most of them hidden by a copious amount of motion blur anyways.

To me it is typical of demos, both as in the "demoscene" and "tech demo" sense, where the art style is driven by the technology, insisting on what it enables, while at the same time working around its shortcomings. I don't consider it a bad thing of course, it leads to a lot of creativity and interesting art styles.

  • Kinda, it all depends on platforms and eras. As a demoscener I see more of techdemo, indiedev and "game-mods" vibes in much of it (especially certain kinds of jankiness feel of visuals in some parts that demosceners doing more high end in general try to avoid but is more meme-worthy in game-mods/indiedev circles). Demos often aim for a bit more clean visuals (and palettes), blurriness is often tuned in another way.

    Sadly, much of the demoscene is in a bit of a navel-grazing retro computing phase, many active ones today are "returners" from the C64 and Amiga eras whilst PC sceners of the 90s either dropped off for money, games or kids.

    It's also the sheer work-effort, demoscene in the 90s and early 00s could focus on rendering while visual art pipelines didn't matter as much, as graphics cards got better it was obvious that the scene was falling behind the cutting edge games (both in asset due to workload and hacks required for graphics cards to render realistically).

    The introduction and early popularization of SDF rendering turned the scene a bit more relevant again, but it's also been masking a certain lack of good artists since programmers could create nice renderings without needing assets.

    However, to match something like this video in creativity would require a lot of asset workload (and non-trival rendering), and that combo is not really that common today sadly.

    Funnily enough, I was actually discussing just Gaussian Splatting as a solution for more "asset heavy" demos about a year ago with another scener friend, but sadly there's a tad of a stigma culturally as NN/"AI" methods has been fairly controversial within the scene, aside from programmers there are both visual and music artists, and among those camps it's not really a popular thing.

    It's still mostly a method though, and SDF rendering + GS could in the end be a saviour in disguise for the scene to go beyond just rendering and bring back a bit more story-telling to the scene.

    • > but sadly there's a tad of a stigma culturally as NN/"AI" methods has been fairly controversial within the scene

      The scene has always been a ridiculously conservative bunch. Back when 3dfx was new, using 3d acceleration was similarly controversial. The Pouet comments were scary similar to those today. All we need is a few demos that actually use these technologies with great results (instead of for laziness/slop), and the majority opinion will shift as it always has.

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To be honest it looks like it was rendered in an old version of Unreal Engine. That may be an intentional choice - I wonder how realistic guassian splatting can look? Can you redo lights, shadows, remove or move parts of the scene, while preserving the original fidelity and realism?

The way TV/movie production is going (record 100s of hours of footage from multiple angles and edit it all in post) I wonder if this is the end state. Gaussian splatting for the humans and green screens for the rest?

  • The aesthetic here is at least partially an intentional choice to lean into the artifacts produced by Gaussian splatting, particularly dynamic (4DGS) splatting. There is temporal inconsistency when capturing performances like this, which are exacerbated by relighting.

    That said, the technology is rapidly advancing and this type of volumetric capture is definitely sticking around.

    The quality can also be really good, especially for static environments: https://www.linkedin.com/posts/christoph-schindelar-79515351....

  • Knowing what I know about the artist in this video this was probably more about the novelty of the technology and the creative freedom it offers rather than it is budget.

  • For me it felt more like higher detail version of Teardown, the voxel-based 3d demolition game. Sure it's splats and not voxels, but the camera and the lighting give this strong voxel game vibe.

  • I wonder if you are thinking Source engine? I was getting serious skibidi toilet vibes during several parts of this video.

Tangential, but I've been exploring gaussian splatting as a photographic/artistic medium for a while, and love the expressionistic quality of the model output when deprived of data.

https://bayardrandel.com/gaussographs/

Be sure to watch the video itself* - it’s really a great piece of work. The energy is frenetic and it’s got this beautiful balance of surrealism from the effects and groundedness from the human performances.

* (Mute it if you don’t like the music, just like the rest of us will if you complain about the music)

  • Similarly, the music video for Taylor Swif[0] (another track by A$AP Rocky) is just as surrealistic and weird in the best way possible, but with an eastern european flavor of it (which is obviously intentional and makes sense, given the filming location and being very on-the-nose with the theme).

    0. https://youtu.be/5URefVYaJrA

    • I can see how this kind of videos can attract the tiktok addicts with less than 3 seconds of attention time.

      I wonder what will be the state of cinema/series/video clips in 30 years? Will singers/rappers give up sentences completely and just mention names of emojis? Will we have to use screens at 576hz to be able to watch acclerated videos without seeing a constant blur?

      I guess most kids from today would fall asleep before the end of the generic of Twin Peaks or the opening scene of Fargo.

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Too bad, but I managed to watch about 30 seconds of the video before getting motion sickness.

Seems like a really cool technology, though.

I wonder if anyone else got the same response, or it's just me.

The end result is really interesting. As others have pointed out, it looks sort of like it was rendered by an early 2000s game engine. There’s a cohesiveness to the art direction that you just can’t get from green screens and the like. In service of some of the worst music made by human brains, but still really cool tech.

Hello! I'm Ben Nunez, CEO at Evercoast. Our software was used to capture and reconstruct the 4D Gaussian splats in this A$AP Rocky video.

The music video is a mix of creative and technical genius from several different teams, and it's ultimately a byproduct of building tooling to capture reality once and reuse it downstream.

There’s a lot more to explore here. Once you have grounded 4D human motion and appearance tied to a stable world coordinate system, it becomes a missing primitive for things like world models, simulation, and embodied AI, where synthetic or purely parametric humans tend to break down.

It’s interesting to see Gaussian splatting show up in a mainstream music video this quickly. A year ago it was mostly a research demo, and now artists are using it as part of their visual toolkit. What I find most notable is how well splats handle chaotic motion like helicopter shots — it’s one of the few 3D reconstruction methods that doesn’t completely fall apart with fast movement. Feels like we’re going to see a lot more of this in creative work before it shows up in anything “serious”.

The texture of Gaussian Splatting always looks off to me. It looks like the entire scene has been textured or has a bad, uniform film grain filter to me. Everything looks a little off in an unpleasing way -- things that should be sharp are aren't, and things that should be blurry are not. It's uncanny valley and not in a good way. I don't get what all the rage is about it and it always looks like really poor B-roll to me.

Oh wow, somehow I was not aware of how capable this technology has become, looks like a major game changer, across many fields.

In the near term, it could be very useful for sports replays. The UFC has this thing where they stitch together sequences of images from cameras all around the ring, to capture a few seconds of '360 degree' video of important moments. It looks horrible, this would be a huge improvement.

A$AP Mob has some really great music videos. They're usually not the first to adopt a new technology, but they love to push the envelope and popularize fringe techniques.

The Yamborghini High music video from 2016 did some really cool stuff with datamoshing and hue shifting: https://www.youtube.com/watch?v=tt7gP_IW-1w

I can't really respect the artist though, after the assault on a random bystander in Stockholm in 2019 — for which he was convicted. He got off too easy.

I would have refused to work on this.

> Viewers assume the imagery is AI-generated.

Watching this Helicopter music video made me recall a scene in Money for Nothing by Dire Straits, which was famously the first music video to air on MTV Europe (when the MTV phenomenon launched the 80s). It used 3D animation for the human characters and was considered groundbreaking animation in that time. The irony is we knew it was computer generated but now human generated is indistinguishable from AI.

Where does this tech originate, creatively? I'm especially thinking about a 1990s or 2000s Rolling Stones pop video that seemed to 'mess with time' but (by and large) in 2d. Had a 'drunk' look to it.

How did Rhianna look him in the eyes and say "yes babe, good album, release it, this is what the people wanted after 7 years, it is pleasing to listen to and enjoyable"?

  • I prefer when artists make music they intrinsically want to make — not what others want them to make.

    • the real question is how much of the art is their own and how much is outside expectations and their reactions to it.

      And it's not always giving in to those voices, sometimes it's going in the opposite direction specifically to subvert those voices and expectations even if that ends up going against your initial instincts as an artist.

      With someone like A$AP Rocky, there is a lot of money on the line wrt the record execs but even small indie artists playing to only a hundred people a night have to contend with audience expectation and how that can exert an influence on their creativity.

  • It seems the numerous leaks and trials took their toll.

    I don’t disagree with you—I felt “Tailor Swif,” “DMB,” and “Both Eyes Closed” were all stronger than the tracks that made it onto this album.

    But sometimes you’ve gotta ship the project in the state it’s in and move on with your life.

    Maybe now he can move forward and start working on something new. And perhaps that project will be stronger.

  • Im sure it was more like, “hey babe, can I get a few millions to go in the studio and experiment/make some art?” And then she was like, “yeah go for it! Make some weird shit.”

    If I was in his position I’d probably be doing the same. Why bother with another top hit that pleases the masses.

They really said it’s capturing everything when A$AP Rocky’s Gaussian splatted mouth in that video be looking worse than AI generated video lol

Both of my worlds are colliding with this article. I love reading about how deeply technical products/artifacts get used in art.

Can somebody explain to me what was actually scanned? Only the actors doing movements like push ups, or whole scenes / rooms?

The splatting seems to be video only but I could be wrong.

It's only a matter of time until the #1 hit figures out how to make this work

This reminds me about how Soulja Boy just used a cracked copy of Fruity Loops and a cheap microphone and recorded all his songs that made him millions.[1] Edit: Ok this was a big team of VFX producers who did this. Still, prices are coming down dramatically in general, but yeah that idea is a bit of an underfit to this case.

[1] https://www.youtube.com/watch?v=f1rjhVe59ek

  • You might consider why this article which has nothing to do with AI as you know it (except for the machine learning aspects of Gaussian splatting), and was produced by a huge team of vfx professionals, has made you think about AI democratising culture (despite the fact that music videos and films have been cheap to make for decades). Don’t just look for opportunities to discuss your favourite talking points.

  • The whole rap/hip-hop scene got jump-started by 1977 NYC blackout electronics store lootings.

So sad that nobody thought it important to ELI5 whatever on earth "gaussian splatting" means, and how it's different than regular splatting (if there's such a thing), or regular video. To me the video looks like the figures have slightly rounder edges, that's all.

  • Say you have a photo, but you want to be able to explore it in 3d so you put it into fortnite but when you move you can't see behind objects because the photo never "saw" behind object.

    So you decide to take lots and lots of photos at every single angle possible, but you need a way to link these all together, so you decide that each Centrepoint of the image is a "gaussian". These splat everywhere.

    Now you have taken all of these photos and you can now explore the image in fortnite because you took thousands of images of every possible view!

    But what if you didn't want to just look at the frozen image in a landscape in fortnite, instead you wanted to use a man dancing in your new upcoming YouTube video called helicopter.

    If you isolate this person (let's say taking all these photos on a green screen) you now have a 3d like recording model, you can reshoot and "scene" on-top of something else (like a 3d diarama like in your video!)

In another setting, it looks like ass, but lo-fi, glitchy shit is perfectly compatible with hip-hop aesthetic. Good track though.

  • I think in 2026 it's hard to make a video look this "bad" without it being a clear aesthetic choice, so not sure you could find this video in another setting.

  • The technology is impressive, but the end result… Weapons-grade brainrot.

    I’m curious what other artists end up making with it.

    • I really disagree with the label brainrot. Brainrot is low-quality garbage with no artistic merit, and very little thought behind its creation, which does nothing but make you briefly pause while scrolling, before scrolling away with no lasting impression being done to your mind (besides increased boredom and inability to focus).

      This is clearly an artistic statement, whether you like the art or not. A ton of thought and time was put into it. And people will likely be thinking and discussing this video for some time to come.

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Hi all! If you watched the video and thought you'd love to make stuff like that, but then you looked at the cost of a volumetric capture and nope'ed out, we should talk!

I've been developing a solution to make the cost of 4D capture an order of magnitude cheaper by using a small number of off-the-shelf cameras. Here's the proof-of-concept demo using 4x GoPros: https://youtube.com/shorts/Y56l0FlLlAg (yes, lots of room to improve quality). You can also see the interactive version (with XR support) at https://gaussplay.lovable.app

"The team also used Blender heavily for layout and previs, converting splat sequences into lightweight proxy caches for scene planning."

so basically despite the higher resource requirements like 10TB of data for 30 minutes of footage, the compositing is so much faster and more flexible and those resources can be deleted or moved to long term storage in the cloud very quickly and the project can move on

fascinating

I wouldn't have normally read this and watched the video, but my Claude sessions were already executing a plan

the tl;dr is that all the actors were scanned in a 3D point cloud system and then "NeRF"'d which means to extrapolate any missing data about their transposed 3D model

this was then more easily placed into the video than trying to compose and place 2D actors layer by layer

  • Gaussian splatting is not NeRF (neural radiance field), but it is a type of radiance field, and supports novel view synthesis. The difference is in an explicit point cloud representation (Gaussian splatting), versus a process that needs to be inferred by a neural network.

  • > and then "NeRF"'d which means to extrapolate any missing data about their transposed 3D model

    Not sure if it's you or the original article but that's a slightly misleading summary of NeRFs.

It would be super cool if these articles or websites actually explained anywhere what volumetric capture and radiance fields actually are!

Maybe I'm getting old, but I can't watch for more than about 5 seconds without getting a headache.

> One recurring reaction to the video has been confusion. Viewers assume the imagery is AI-generated. According to Evercoast, that couldn’t be further from the truth. Every stunt, every swing, every fall was physically performed and captured in real space. What makes it feel synthetic is the freedom volumetric capture affords.

No, it’s simply the framerate.

Pretty sure most of this could be filmed with a camera drone and preprogrammed flight path...

Did the Gaussian splatting actually make it any cheaper? Especially considering that it needed 50+ fixed camera angles to splat properly, and extensive post-processing work both computationally and human labour, a camera drone just seems easier.

  • > Pretty sure most of this could be filmed with a camera drone and preprogrammed flight path

    This is a “Dropbox is just ftp and rsync” level comment. There’s a shot in there where Rocky is sitting on top of the spinning blades of a helicopter and the camera smoothly transitions from flying around the room to solidly rotating along with the blades, so it’s fixed relative to rocky. Not only would programming a camera drone to follow this path be extremely difficult (and wouldn’t look as good), but just setting up the stunt would be cost prohibitive.

    This is just one example of the hundreds you could come up with.

    • Drones and 2d compositing could do a lot. They would excel in some areas used in the video, require far more resources than this technique in others, and be completely infeasible on a few.

      They would look much better in a very "familiar" way. They would have much less of the glitch and dynamic aesthetic that makes this so novel.

  • A drone path would not allow for such seamless transitions, never mind the planning required to nail all that choreography, effects, etc.

    This approach is 100% flexible, and I'm sure at least part of the magic came from the process of play and experimentation in post.

  • If it was achievable, cheaper, and of equal quality then it would have been done that way. Surely it would’ve been done that way a long time ago too. Drone paths have been around a lot longer than this technology.

    There’s no proof of your claim and this video is proof of the opposite.

  • I think you’re missing the point

    Volumetric capture like this allows you to decide on the camera angles in post-production

  • It's fucking cool. That's why.

    This tech is moving along at breakneck pace and now we're all talking about it. A drone video wouldn't have done that.