Two decades after the release of *The Matrix*, a team has recreated its iconic bullet time effect using a fraction of the original resources. While the original sequence required 120 expensive film cameras, a multimillion-dollar budget, and nearly a year of post-production, the Corridor crew achieved a similar result with just ten phone cameras and a single 5090 workstation. The key to this modern recreation was the clever application of AI tools for video interpolation, inpainting, and 3D editing. This demonstrates how AI can dramatically reduce the technical and financial barriers for creating complex visual effects, making what was once a monumental cinematic feat far more accessible.
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It’s wild to think they matched that iconic effect with just ten phone cameras compared to the original 120 film rigs. As someone who dabbles in video editing, this makes me want to experiment with AI interpolation tools on some old action shots I have. Do you think this accessibility will lead to the effect becoming overused, or will it just empower more creators?
It’s truly wild how they condensed that 120-camera rig down to just ten phones, and your instinct to experiment with your own action shots is exactly the kind of creativity this empowers. While any tool can become overused, I believe this accessibility will primarily fuel innovation, letting creators focus on new storytelling rather than just replicating old effects. A great first step is to try a free AI interpolation tool like RIFE to add slow-motion frames to your shots—I’d love to hear what you create with it.
It’s wild to think they matched that iconic effect with just ten phone cameras compared to the original 120-film-camera rig. As someone who dabbles in video editing, this makes me want to experiment with AI inpainting tools on some of my own shaky footage to see if I can smooth out the motion. What other classic film techniques do you think are ripe for an AI-powered DIY revival?
It’s amazing how they pulled off that bullet time effect with just ten phone cameras, isn’t it? For a DIY revival, I think AI is perfect for recreating techniques like the “Dolly Zoom” or even complex practical makeup effects through style transfer and deepfakes. A great next step is to check out free tools like EbSynth or the tutorials on the Corridor Digital YouTube channel to start experimenting. I’d love to hear what you discover when you smooth out your own footage!
It’s impressive that they recreated such an expensive shot using free AI tools.
Not for the camera company. AI is taking their jobs.
It’s wild to think they matched that iconic effect with just ten phone cameras compared to the original 120 film rigs. As someone who dabbles in video editing, this makes me want to experiment with AI inpainting tools for my own projects to smooth out some shaky shots. What other classic film techniques do you think are ripe for an AI-powered DIY revival?
Absolutely, the leap from 120 film rigs to ten phone cameras really highlights how much the tools have evolved. For a DIY revival, I think practical miniatures and matte paintings are prime candidates—AI upscaling and texture generation could breathe new life into those techniques on a small budget. You might start by experimenting with a tool like Stable Diffusion for generating background plates or extensions to your shots. I’d love to hear what you discover if you give it a try!
It’s wild to think they matched that iconic effect with just ten phone cameras and a single workstation, when the original needed 120 film rigs. As someone who dabbles in video editing, this makes me want to finally experiment with those AI inpainting tools I’ve been avoiding—maybe I can finally fix that shot where my mic stand was accidentally in frame. Has anyone here tried using AI for a similar VFX challenge?
That’s a great point—it’s incredible how ten phone cameras and a single workstation can now achieve what once took a massive rig. For your mic stand issue, AI inpainting tools like Runway ML’s Gen-2 or even free options like Stable Diffusion can work wonders for removing unwanted objects; just mask the area and let the AI generate a clean background. I’d love to hear how it goes if you give it a try, or if others have tackled similar VFX challenges with AI!
It’s wild to think they matched that iconic effect with just ten phone cameras, considering the original used 120 specialized film rigs. As someone who dabbles in video editing, this makes me want to experiment with AI inpainting tools for my own projects to clean up shaky footage. What other classic film techniques do you think are ripe for an AI-powered DIY revival?
I love that you’re inspired to try AI inpainting for stabilizing shaky footage—it’s a perfect starting point. For a DIY revival, consider AI-assisted rotoscoping or motion tracking, which used to be painstaking frame-by-frame work but can now be streamlined with tools like Runway ML or even Blender’s AI features. If you experiment, I’d be curious to hear how it goes or what other classic techniques you think could be reinvented next.
It’s wild to think they matched that iconic effect with just ten phones and a single workstation, when the original needed 120 film cameras. As someone who dabbles in video editing, this makes me want to finally experiment with those AI inpainting tools I’ve been avoiding—maybe I can finally fix that shot where my mic accidentally dipped into frame. What other classic VFX shots do you think are ripe for this kind of AI-powered DIY remake?
It’s amazing, right? That leap from 120 film cameras to a handful of phones really shows how the playing field has changed. For a classic VFX shot ripe for a DIY remake, I’d point to the “T-1000 liquid metal” effects from *Terminator 2*—AI-powered fluid simulation and texture work could make that surprisingly approachable now. If you’re diving into inpainting to fix that mic shot, starting with a tool like Runway ML’s Gen-2 is a great, user-friendly first step. I’d love to hear how your experiment goes or if you have another iconic effect in mind!
It’s wild to think they matched that iconic effect with just ten phone cameras, considering the original used 120 specialized film rigs. As someone who dabbles in video editing, this makes me want to experiment with AI inpainting tools for my own projects to smooth out some shaky shots. What other classic film techniques do you think are ripe for an AI-powered DIY revival?
It’s truly mind-blowing how they condensed that 120-camera rig down to a handful of phones, isn’t it? For a DIY revival, I think practical miniatures and matte paintings are prime candidates—AI upscaling and texture generation could let creators build stunning worlds on a tabletop. If you’re starting with inpainting for shaky shots, I’d recommend playing with a free tool like Stable Diffusion’s outpainting feature to get a feel for it. I’d love to hear what you experiment with first!
It’s wild to think they matched that iconic effect with just ten phones and a single workstation, compared to the original’s 120 film cameras. As someone who dabbles in video editing, this makes me want to finally try out some of those AI inpainting tools I’ve been avoiding. Do you think this accessibility will lead to a new wave of creative, low-budget VFX in indie films?
Absolutely, it’s mind-blowing how they condensed that massive camera rig into just ten phones! I do think this kind of accessibility is a game-changer for indie creators, as it shifts the bottleneck from budget and hardware to creativity and skill. A great first step is to experiment with a free, user-friendly tool like Runway ML’s inpainting features to get a feel for the process. I’d love to hear what you create if you give it a shot.
It’s wild to think they matched that iconic effect with just ten phone cameras and a single workstation, compared to the original’s 120 film rigs. As someone who dabbles in video editing, this makes me want to finally experiment with those AI inpainting tools I’ve been avoiding. What other classic VFX shots do you think are ripe for this kind of accessible AI remake?
It’s amazing how those ten phone cameras and a single workstation could stand in for that massive film rig, isn’t it? For other classic VFX, I think the liquid metal T-1000 from *Terminator 2* or the mirror scene from *Contact* could be fascinating to tackle with today’s AI tools. If you’re looking to start, I’d suggest trying out a free tool like Stable Diffusion’s inpainting feature on a simple test clip to get a feel for it—I’d love to hear what you create.
It’s wild to think they matched that iconic effect with just ten phone cameras, considering the original used 120 film rigs. As someone who dabbles in video editing, this makes me want to finally try using AI interpolation tools on some old action shots I have. What other classic VFX shots do you think are ripe for this kind of accessible AI remake?
It’s amazing, right? That leap from 120 film rigs to ten phone cameras really shows how the playing field has changed. For other classic VFX ripe for an AI remake, I’d look at the liquid-metal T-1000 from *Terminator 2* or the mirror scene from *Contact*—both were incredibly labor-intensive practical and digital composites that modern inpainting and element blending could simplify. If you’re diving into your old action shots, starting with a free tool like RIFE for interpolation is a great first step—I’d love to hear how your experiments turn out!
With the right AI software, I believe I could achieve this using just one phone camera.
This shot specifically avoids rotating around the actors by using 96 separate film cameras, as they determined the G-forces from a moving camera would have destroyed it. Film sets can certainly be dangerous places.
These creators are impressive. It’s unfortunate they faced so much harassment and death threats years ago over their AI-animated rock paper scissors short film.
I thought that video was generally well received.
The video was well-received by general audiences, but it also drew intense backlash from critics of AI. Those critics directed significant anger, threats, and harassment toward the creators, attempting to harm them and their channel.
It’s frustrating when people claim “this is what AI should be used for,” as if dismissing the many other valid applications. AI doesn’t need to please everyone, and we shouldn’t water down our advocacy just to appease critics. Instead, those opposed to AI should specify which uses they find objectionable and explain why. The burden of proof lies with them.
I’m not saying this is the only use for AI. My point is that it dramatically reduces the resources and equipment needed for technically demanding shots. It’s surprising to see people criticizing or questioning that. The title was limited to 300 characters, so I may not have communicated it clearly.
This expectation is unreasonable. It’s like saying canvas and paint should only be used for a masterpiece like a Rembrandt, never for the practice pieces that build the skill to create one. The technology is the same; you can’t go from A to C without passing through B.
For every harmful application of AI, there is someone who has used the same technology to benefit humanity. Critics often dismiss these positive uses, claiming they are not equivalent.
The statement “this is what AI should be used for” is accurate here. While AI models were used, I would still classify this as a human-made project. If someone had simply prompted a model and received this output, it would not be.
I think the “suck it up” attitude is less palatable when discussing technology that could erase many jobs—the very work people must do to survive in our current economy.
Sorting through trash is also a key purpose of AI, and while I love art, that application is far more important. AI can be used for millions of things, and its implementation will continue to grow in that direction.
What distinguishes this from green screening, and what makes it AI?
Watch the main video from Corridor Crew.
Consider how you would shoot this yourself. It’s not about green screens—removing the background is the easiest part.
This is a slow-motion shot, so you need to capture many images quickly, around 100-200 frames in just 0.2-0.3 seconds. Few cameras could shoot that fast back then. Additionally, the camera moves around the subject during the shot, covering 5-10 meters (20-30 feet) in that same brief time. That requires the camera to move at about 110 mph or 180 kph, which is difficult even with modern robots and dangerous around actors.
Instead, they used multiple static cameras triggered in sequence. The challenge is that everything between the cameras is missing and must be filled using the images from adjacent cameras. Larger gaps between cameras require more frames to fill, which is why they originally used 120 cameras, though gaps still remained.
Initially, they simply blended the two images together, but the results were poor. The breakthrough came with optical flow, which improved motion prediction but still didn’t understand limbs or body parts.
Around 2020, GAN-based machine learning interpolation allowed generating up to 16 in-between frames directly from two images.
Today, AI video can create several seconds of footage—hundreds of frames—from minimal input. This dramatically reduces the gaps in footage and cuts the number of cameras needed down to just a few, like the 10 phones they used.
You should watch the behind-the-scenes footage of The Matrix, because your description isn’t accurate.
This is an excellent case study for the potential of diffusion models. I’ve been saying for a while that this technology will streamline and democratize many traditional film techniques. It’s great to see it done in practice.
The Matrix did not use a device that rapidly spun around the actor.
I concede the point. Take care.
I wonder if they are using a public ComfyUI workflow. They didn’t mention their use of AI much, likely because they have received death threats for it in the past.
They included the full workflow in the description, which is great. It’s a shame they avoided using the term “AI” as much as possible, but that’s likely a necessary choice for revenue, even though the techniques are fundamentally the same. It’s an unfortunate reality of catering to public perception.
I’m frustrated that my 6900XT can’t run ComfyUI.