How to Make Full 3 D AI Movies From Single Image Step by Step

AI filmmaking sounds way more complicated than it actually is. In reality, it's so simple that you can make full AI movie from just single image. That's why today I'm going to show you how did it myself. So, in the next 14 minutes, you'll see the entire process behind the scenes from the photo picked to the first AI generation all the way to the final result. And besides that, I'll tell you my little secret that let me save lot of credits without giving up on quality. So, here's the image I'll be using for this video. It's simple photo of myself, but it's the foundation of what's about to come. The first step inside the workflow is to turn this photo into an animated character. And for this, I'll because it has every AI model need on the same platform. So, if you want to follow along with me, I'll leave link in the description below. Once you're inside, let's head over to the image section and select GPT image 2 as the model. From here, I'll click on references and upload the photo of myself. Now, I'm going to create character sheet from this image. And the reason for that is quite obvious for any advanced AI creator. The more context you give the model, the better the output will be. So, instead of using just simple front-facing image, I'll give the AI sheet with multiple angles. This way, I'll make sure my future character stays consistent across all the shots. And this part is extremely important because once the model understands the face from multiple directions, it has way less room to guess. It can see the shape of my head, the proportions of my face, and the small details that make the character look like me. So, here's the exact prompt I'll write. As you can see, asked for multiple angles and even different parts of my face like the eyes and the chin. And here's the character sheet we get back. Now that we have it, we can move on to the second part and create the animated character. For this, I'll take the image we just generated and feed it back into the image model. So, I'll click on visual references and select the character sheet. But before add the prompt, let's make sure we have GPT image two selected as the image model. This new AI model was just released few weeks ago, and it's one of the best image generators out there. And in my opinion, it's actually way better than Nano Banana, especially when it comes to keeping the same face while changing the style. So, once you've selected it, let's go to the prompt section and paste this in. And this is the result we get back. As you can see, it created pixel character that actually looks like me. The eyes are the same, the hairstyle matches mine, and it even kept the goatee exactly like we showed it in the character sheet. So, the overall result already looks really good. And this is the image we're going to refer back to every time we generate scene from here on. So, with that done, the character is locked. The only thing missing now is starting frame for the opening scene, which is what we're going to build next. Now, you might be tempted to skip this step entirely and just throw the character straight into the video generator with long prompt. But that almost never ends up as you expect. And that's because you're giving the AI too much freedom to interpret the prompt as it wants. And because of that, it usually comes up with new things you might not want inside your generation. So, you'll end up burning through your credits before you even finish one project. That's why we're going to create starting frame for our first video right now before we generate any scene. For this, I'll click on references and select the Pixar character we just generated. From here, let's head to the prompt section and paste this in. As you can see, I'm not just describing the environment. I'm placing the character mid-action, sprinting down the corridor with debris falling around him and light cutting through the cracks in the ceiling. This gives the video model the exact type of movement that's happening in the first frame. Now, before press generate, I'll select the ratio to 16:9. And here's the starting frame we get after the generation. It perfectly integrated my character inside the environment. And on top of it, it has all the details asked for, from the debris falling to the warm lighting. So, with this image in place, we have everything we need for the first scene. So, we can finally move on to the video generation stage. And for this, we're going to use Dance 2.0, which is currently one of the best video models out there. So, let's head over to the video section and select Dance 2.0 as the model. Once we're in, there are few settings we need to configure before we start generating. First, I'll click on references and add both the Pixlr character and the starting frame we just created. Then, for the duration, I'll set it to 15 seconds. And for the aspect ratio, I'll go with 16 to 9, which gives me that cinematic widescreen look. Now, the main tip want to give you here is about the resolution. Instead of generating at 1080p, we're going to render at 720p. Yes, the resolution will be lower out of the gate, but there's specific reason why we're doing this. Dance is one of the best video models out there, but this also means it needs lot of credits to run. And at 1080p, it can get extremely expensive really quickly. One generation at 1080p costs around 3,000 credits, while at 720p, it's 1,200 credits per clip. That's almost three times less. So, here's the trick. We generate all three scenes at 720p, and once they are done, we'll run the final video through Openart's upscaler. That only costs 850 credits, and it actually takes the video to 4K instead of 1080p. The upscaler also handles animation cleanly without introducing any of the artifacts you'd get with photoreal footage. So, we save credits during the generations, then come out the other side with higher quality version of the film than if we generated at 1080p in the first place. So, now that you understand why we generate at 720p, we can move on to the prompt. Here, could simply paste it in and get to the next step. But if there are any of you who wonder how structure my prompts, use the multi-shot framework. And because see lot of people completely messing up this prompting part and then calling the AI model bad, I'm going to show you this framework that use. The idea behind it is really simple. Instead of writing big block of text, you break everything down into multiple shots, and then you go through each one in order and add its own action and description. In this way, the model reads your prompt as series of steps it needs to follow in order, which makes everything clearer for this. So, what this really means is that you get full control over your generation instead of letting the AI guess it. You can also include timing in the prompt, like which shot starts at which second, if you want even tighter control over the pacing. But for this scene, I'll let SeaArt handle the timing. Here's what that looks like. As you can see, split the scene into three shots. Shot one is the sprint and the camera tracking back. Shot two is the stone block dropping and the slide under it. Shot three is the camera pivot and the corridor collapsing behind him. Each one is beat want to land in specific order. And then, at the bottom, add the audio line. This tells SeaArt the kind of sound design want, like stone rumbling, footsteps, and sharp breaths. The model uses that to time the beats and add the right kind of atmosphere on top of the visuals. This multi-shot approach is what gives me direct control over what happens in every clip, instead of hoping the model lands the right action. It might seem like more work, but the payoff is 10 times the effort you put in. So, let me press generate and show you the scene. And here it is. The character stays consistent across the entire video, and the lighting cutting through the dust gives the shot real cinematic depth. The motion also lands across all three shots in the exact order wrote. First, he sprints through the corridor. Then, the debris starts falling around him. And finally, the camera keeps that intense movement while the whole scene feels like it's collapsing around the character. On top of that, the audio matches the action really well with the right cracks, footsteps, and heavy breaths. So, the overall result already looks really good, which means we can step into the second scene. And here's where things get interesting. For scene two, we don't need new starting frame. We're going to use the video we just generated as our visual anchor instead. This is the chain technique mentioned earlier. Inside SeaArt 2.0, there's video reference field that lets you upload previous scene as the visual baseline for the next generation. The model reads the motion, the character, and the overall look of that clip, and uses it all as the anchor for what comes next. This is one of those features that very few AI model tools have right now. Most platforms make you start each clip from scratch with new image and new prompt, and you end up burning credits trying to keep the look consistent. SeaDance 2.0 lets you build on top of what you already generated, which means continuity is built into the workflow itself. So, instead of replacing the starting frame with new image, I'll head back to references and pull out the starting frame, then drop video one into the video reference field. Then, I'll write the prompt for scene two. And as you can see, I'm using the same shot list framework as before. But now, let's go ahead and press generate. And here's what we get back. The character looks just like he did in scene one. And also, the style stays consistent while the lighting still feels like it belongs to the same world. But what like the most is that the action doesn't feel random. The bridge starts to break in way that naturally pushes the character into the jump. And once he lands, the audio gives the whole scene enough weight to make it feel cinematic. But here's the part that matters most. When place scene one and scene two next to each other, it doesn't really feel like cut. It just feels like the same action continues from one shot into the next. And this is exactly what the chain technique gives you. Because instead of creating separate clips that barely connect, you're using each result as the reference for the next one. That's why I'm going to apply the same strategy for the third scene. I'll head back to references, pull out video one, and drop video two into the video reference field this time. Then, I'll write the prompt for scene three. And let's go ahead and press generate. And here it is. What like here is that the scene doesn't feel like separate generation, even though it technically is. He gets back up, pushes toward the door, and the whole moment builds into that final escape. And once he bursts out onto the jungle ledge, the sound of the impact and the temple collapsing behind him makes the scene feel complete. But the cool part about this whole thing is that the chain technique scales. If we wanted 16-film instead of three, we just keep using each video as reference for the next one. However, there's one thing you need to know. In the previous generation, didn't actually use the entire video two as the reference video. And the reason for that is not what you think. You see, when most people get bad results from generation, they simply change the prompt and try again. But, that wastes full batch of credits every time. The honest truth is that scene two's first generation wasn't great. There was actually moment toward the end that completely broke the clip. But, instead of throwing it away, used an advanced technique to save everything. And use this technique for all my generations because not only does it give me the best results, but paradoxically, it also saves me ton of wasted credits. You see, not every generation lands the way you want it from the first try. know this is not great, but the AI is not perfect at this moment, and it still makes mistakes from time to time. Sometimes, the action is not the one described, the character doesn't have specific detail on it, or maybe the lighting is off. So, here's what do instead. When generation doesn't fully land, don't delete it. go through it and pick only the parts that like. So, let me walk you through exactly how did this for scene two. As you can see, after the character runs across the falling bridge, he jumps and lands on this big rock on the other side. But then, instead of staying there, he jumps down to the ground and immediately climbs back up to the same rock, which doesn't make any logical sense. So, instead of throwing the whole clip away and regenerating from scratch, kept the parts that worked and only used those for scene three. And here's how did it. went into the video section in SeaArt. Then, instead of uploading the full scene two video into the video reference field, used the trim option to select only the part of the clip wanted to keep. SeaArt lets you pick up to 15 seconds of any video as the reference, which is more than enough to trim scene two down to the first 11 seconds. The glitch starts right after that mark, so cut it off before it happens. Then, pressed confirm. And now, the video reference was just good 11 seconds of scene two without any glitches inside. Then wrote the prompt to continue the action from there. told Dance to pick up where the trimmed clip ended with the character standing up off the rock and moving into the final escape. And that's exactly the scene three you saw earlier. The character lands on the rock cleanly and moves into the next action without any of the bouncing back and forth. So the technique works perfectly. And by the way, you can do the same thing with screenshots instead of video clips. Instead of trimming section of the video, you can just take screenshot of the exact frame you want and drop it in as new start frame. Now it really depends on the situation which method I'm choosing. If it's single moment like the character hitting specific pose, go with simple screenshot. But if it's an action that plays out over few seconds like it did here, go with the video reference option. But what this really means is that even my failed generations end up working for me. And this is huge for the credit budget because every generation costs the same whether it works or not. So if just throw away every bad clip, I'm basically paying for nothing. But if take the parts that actually worked and use them as references for the next try, the workflow keeps moving forward instead of starting from zero again. And now that we have all our shots with zero problems inside, let's stitch them all together. For this, we're going to use simple editing tool. So let me head over to CapCut and create new project. From here, I'll just drop scene one, scene two, and scene three onto the timeline in order. I'm not adding any transitions or fades here. The scenes already flow into each other because of the chain technique. So if we add anything extra now, it would only make the sequence feel less natural. And that would break the continuity we were trying to build in the first place. So let me export the video as it is right now. And here's what we get. The three scenes play back as one continuous sequence, but we're not done yet. We still need to bring the video up to higher resolution because right now we're at 720p. So, I'll head back into OpenArt, click on upscale video, and upscale the first 20 seconds. I'll upload the CapCut export, choose the highest resolution, and let it run. Repeat the process for the remainder of the video, and just like that, the final video is ready. The upscaler took 720p all the way to 4K, and the whole project cost us 850 credits at this stage. So, when you add up all the savings from generating at 720p across the three scenes, plus the upscale at the end, we end up with finished 4K AI movie that cost fraction of what it would have cost to generate at 1080p natively from the start. So, if you want to create high-quality videos even from single image, go sign up to OpenArt with the link in the description. Thanks for watching, and I'll see you in the next one.