AI video generators typically create videos from text prompts. However, technology is making progress in allowing creators to generate videos from images. These AI video generators from images can alter your pictures to create videos. Using this technology, creators can get the output closest to their vision.
As we know, text prompts have some limitations regarding AI video generation. So, these AI image-to-video makers will overcome these restrictions for content creation. Here, we will get to know about image-to-video AI tools and models they use for video creation.
In this article
Part 1: OpenAI Sora and Image-To-Video Generation: An Overview
OpenAI has launched its own AI tool that generates videos from text or image prompts. Sora is an AI video generation tool anyone can use to create engaging videos without any skills. All you have to do is put in text prompts and let Sora AI do the magic. Plus, this AI tool will be able to create complex scenes with multiple characters. For video creation from text, Sora takes assistance from the ChatGPT. Other than generating videos from text, Sora may also be capable of turning images into videos. It means that we can provide an image as a prompt and tell it what to do with the image.
Part 2: Understanding the Different Foundational Models of Video Generation
AI images-to-video tools work on multiple models to give a suitable output to users. These models help to optimize the results of videos through different built-in mechanisms. Let's dig deep into the technical workings of these models to get a better idea.
1.Generative Adversarial Networks (GAN)
This AI video generator from images is based on two neural networks. One is a generator that aims to create realistic videos by adding details to random noise. While the other is a discriminator that differentiates between real data and samples. With training, generators learn to create realistic sample videos from prompts.
In contrast, discriminators intend to become better at distinguishing real from fake. In video creation, GANs can generate new frames by predicting the next frame. This helps them create realistic videos for the users.
2.Autoregressive Model (AM)
Using this AI image video generator model, you can create videos frame-by-frame. This model does so by predicting the next frame based on the previous ones. For this, the model analyzes the sequence of past frames and predicts the content of the following frame.
They typically use RNNs or transformers to generate a consistent sequence of frames. However, it is error-prone as dependencies grow with frame sequence. Therefore, you cannot use this model to make longer videos.
3.Stable Video Diffusion (SVD)
SVD turns the image into video AI by adding noise to a real video and then de-noising it to obtain a new frame. As mentioned, noise is added to the current frame. Afterward, the resulting noisy frame is then denoised to produce the next frame.
It carries out this process multiple times to gradually decrease noise for high-quality output. With this technology, this model overcomes the error-prone nature of autoregressive models. As a result, it becomes suitable to create longer videos.
4.Contrastive Language-Image Pre-training (CLIP)
CLIP is a deep learning model that trains other AI models on images and text prompts. By doing so, this image-to-video AI model helps AI learn to associate pictures and text. It's pre-trained on a large dataset of images and associated text descriptions.
While CLIP isn't a video generation model, it can be used with other models. For example, you can use it with GANs to guide video generation based on text prompts.
Stable video diffusion stands out as the best AI video generation model. As we have discussed, SVD doesn’t make errors with growing frame sequences. So, it is better for longer video creation compared to autoregressive models. Plus, this AI images-to-video model requires less training to create high-quality visuals.
Part 3: Top 5 Image-To-Video Tools for Creative Content Generation
Now, you have understood the workings of AI video creation models. Let’s discuss the image-to-video AI generators that utilize these models for video creation. After going through this list, you can choose the best tool for creative content generation.
1.PixVerse
If you want to create an engaging video with simple image prompts, PixVerse is the perfect tool. Moreover, you can add additional text prompts to tell AI what to do with the image. This image-to-video AI creator also allows you to adjust the strength of the motion. In addition, creators can turn on the HD option to generate video in the best possible quality.
After generating the AI video, you can upscale it by using the text prompts. However, if you still don’t like the output, this tool allows you to re-create the motion. The technology of its AI model aligns with that of GANs. Nevertheless, we don't know the exact model on which it works.
2.Runway
Runway is one of the most advanced AI image video generators with multiple features. Upon adding the image prompt, you can set the camera movement to apply a creative touch. Also, it has a motion brush that allows you to control specific areas for movements. Creators even get the option to add text prompts to get visuals that match their ideas.
With its general motion feature, you can adjust the intensity of motion in your AI video. Other than that, you can extend the video up to 4 seconds after the generation. The workings of this tool depend on two AI models, Gen-1 and Gen-2.
3.Pika
Creators who want to attract audiences on their social platforms can use Pika for video generation. This AI image-to-video creator allows you to add text prompts to achieve desired movements. Plus, you can use the lip-sync feature to add AI voiceovers to the video. For this, you get to import an MP3 file or generate an AI voice for perfect narration.
Moreover, you can control the camera and strength of motion with the help of this tool. Pika even lets you add sound effects to the video for background music. We don't know about the exact AI model it uses for the video generation process. However, it seems Pika utilizes models like GANs due to the tool's workings.
4.Neural Frames
Neural Frames is an excellent images-to-video AI maker that allows you to add image prompts for video creation. After you upload an image, it automatically creates a text prompt for video generation. You can also use the Pimp My Prompt feature to further optimize the instructions. Plus, creators get to adjust the flicker style and movement settings for desired visuals.
The best thing about this AI-powered tool is that it allows you to set the duration of the AI-generated video. Neural Frames generally utilize the Stable Diffusion model for video creation. However, it can use up to 9 other models for different styles.
5.Leia Pix
With the presence of multiple features to control video animation, Leia Pix will optimize your video creation. You can determine the amount of motion to optimize movements in video. Also, creators can set a focus point to determine the area of movement. Using the animation style feature, you can decide how your image will move during the video.
Leia Pix utilizes deep learning algorithms trained on 2D images. Moreover, this AI video generator from images makes use of image analysis methods to create visuals.
Final Thoughts
In conclusion, we can say that AI image-to-video generators work on advanced models to create high-quality output. Throughout this article, you got to know about different AI models for this operation. Also, you have been introduced to some of the best tools to convert images to video with AI. So, utilize this knowledge to innovate the way you create video content.
