NEW Open Source AI Video (Multi-Consistent Characters + 30 Second Videos + More)

AI Samson
4 May 202415:33

TLDRStory Diffusion, an impressive open-source AI video model, is revolutionizing video generation with its ability to produce 30-second clips featuring consistent characters and realistic physics. It excels in maintaining character consistency across scenes, a significant leap from previous models like Sora. Capable of generating both realistic and animated content, Story Diffusion allows for the creation of AI comics and long-form video clips, showcasing remarkable expressiveness and fluidity. Despite minor imperfections, it demonstrates a major advancement in AI video technology, offering a glimpse into the future of AI-generated content.

Takeaways

  • 😲 Story Diffusion is a groundbreaking open-source AI video model that generates videos up to 30 seconds long with remarkable character consistency.
  • 🐶 It addresses issues like character morphing and extra character creation, improving realism in AI-generated videos.
  • 👍 The model excels in character consistency, not just in facial features, but also in clothing and body type across different shots and scenes.
  • 🎭 It enables the creation of AI comics by ensuring consistency in character appearance from one image to the next.
  • 🚴‍♀️ A demo video showcases a female character riding a bike with anatomical correctness and minimal distortion.
  • 🕒 The model can produce clips as long as 23 seconds, maintaining character consistency throughout the entire video.
  • 🎥 Despite minor issues like occasional jitteriness and square aspect ratios, the model demonstrates significant advancements in character clarity and consistency.
  • 😃 Notable expressiveness is achieved in character faces, particularly in reactions to music or actions within the video.
  • 🆚 Compared to other models like Sora, Story Diffusion produces longer, more consistent videos with less computational resources.
  • 🌟 It's capable of handling diverse scenes, from realistic to anime-style animations, and maintaining character consistency across different scenarios.
  • 🔍 While the model shows promise, there are still areas for improvement, such as handling occlusions and maintaining perfect consistency in details like clothing and markings.

Q & A

  • What is Story Diffusion and how does it differ from other AI video models?

    -Story Diffusion is an open-source AI video model that stands out for its ability to create videos up to 30 seconds long with high character consistency and adherence to reality and physics. It differs from other models by offering deeper understanding of reality and maintaining consistency not just in facial features but also in clothing and body type across different shots and scenes.

  • How does Story Diffusion handle the creation of AI comics?

    -Story Diffusion generates AI comics by creating a series of images for a sequence, ensuring consistency in terms of facial features and clothing. It then predicts the movement between those images and animates them using a motion prediction model.

  • What is the significance of the character consistency achieved by Story Diffusion?

    -The character consistency achieved by Story Diffusion is significant as it allows for the creation of believable characters that maintain perfect consistency between shots and scenes. This not only expands opportunities for AI video creation but also enables the generation of AI comics.

  • How does Story Diffusion handle the animation of occluded objects?

    -Story Diffusion faces challenges when animating occluded objects, as it must remember the object's appearance before it was obscured and accurately re-render it afterward without predicting its future state. There are instances where the animation does not appear natural due to this complexity.

  • What is the maximum video length that Story Diffusion can produce?

    -The maximum video length produced by Story Diffusion, as demonstrated in the script, is 30 seconds. This is a significant advancement compared to other models like Sora, which produced shorter clips.

  • How does Story Diffusion compare to Sora in terms of computational resources required for training?

    -Story Diffusion is notably more efficient than Sora in terms of computational resources. While Sora required 10,000 GPUs for training, Story Diffusion was trained using only eight GPUs, indicating a significantly lower computational requirement.

  • What are the potential applications of Story Diffusion's technology?

    -Story Diffusion's technology can be applied to create realistic AI videos, generate AI comics, and produce animations with consistent characters. It also opens up possibilities for creating full films in animated and anime styles.

  • How does Story Diffusion ensure the fluidity and naturalness of the generated videos?

    -Story Diffusion ensures fluidity and naturalness in its generated videos by using consistent self-attention to maintain visual coherence and story splitting to process multiple text prompts simultaneously, creating a sequence of images that depict the narrative.

  • What are the current limitations of Story Diffusion when it comes to character and scene consistency?

    -While Story Diffusion has made significant strides in character and scene consistency, there are still minor inconsistencies such as changes in clothing details or slight variations in facial markings between scenes.

  • How accessible is Story Diffusion for users who want to experiment with it?

    -Story Diffusion is open source and accessible to users who can download and install it or run it online on a cloud server. It also has a demo available on Hugging Face for users to explore.

Outlines

00:00

🚀 Introduction to Story Diffusion: A Revolutionary AI Video Model

The paragraph introduces 'Story Diffusion,' an open-source AI video model that stands out for its ability to create videos up to 30 seconds long with remarkable character consistency and realism. It highlights the model's advancement over previous models like Sora, which struggled with morphing and creating extra characters. Story Diffusion is praised for its deep understanding of reality, allowing for believable characters that maintain consistency across different shots and scenes. The paragraph also mentions the potential of this technology to revolutionize AI video creation and generate AI comics, with an example of a comic generated using Story Diffusion. The process involves creating a series of consistent images and then animating them using a motion prediction model.

05:02

🎭 Enhancing Character Consistency and Realism in AI Videos

This paragraph delves into the advancements of Story Diffusion in maintaining character consistency, not just in facial features but also in clothing and body type. It emphasizes the model's ability to create believable characters that remain consistent throughout videos, which is a significant step forward in AI video generation. The paragraph also discusses the model's output, including the length of the clips it produces, which are significantly longer than previous models. It mentions a specific 23-second clip as an example of the model's consistency and character clarity. Additionally, the paragraph touches on the model's expressiveness, particularly in facial animations, and compares it favorably to other AI video generators like Sora and Vidoo, noting the computational efficiency of Story Diffusion's training process.

10:02

🤖 Behind the Scenes: How Story Diffusion Achieves Coherence and Realism

The paragraph explores the technical aspects of how Story Diffusion maintains consistency and realism in its generated content. It discusses the use of consistent self-attention, which ensures that each generated image shares certain attributes or themes, making them visually coherent when viewed as a series. The paragraph also explains the 'story splitting' technique, where a story is broken down into multiple text prompts that are processed simultaneously to produce a sequence of images. These images are then animated using a motion prediction model to create fluid and natural-looking videos. The paragraph provides examples of how Story Diffusion handles diverse scenes and animations, from realistic videos to anime-style content, and how it effectively animates different elements within a scene.

15:03

🌟 The Future of AI Video and the Potential of Story Diffusion

The final paragraph summarizes the progress made by Story Diffusion in the field of AI video generation and invites viewers to consider its potential applications. It acknowledges the significant advancements in character consistency and realism, as well as the model's ability to create cohesive and realistic scenes. The paragraph also encourages viewers to explore other AI video models and to think about how they might utilize AI video technology in their own projects. It concludes with a call to action for viewers to reflect on their thoughts about Story Diffusion and to consider the possibilities it opens up for the future of video content creation.

Mindmap

Keywords

💡Story Diffusion

Story Diffusion is an open source AI video model that stands out for its ability to generate videos with remarkable character consistency and adherence to reality and physics. It represents a significant advancement in AI video technology, as it can produce videos up to 30 seconds long with minimal morphing or distortion. The model's name suggests its function of 'diffusing' a story across a sequence of consistent images, which is a core theme of the video.

💡Character Consistency

Character consistency refers to the ability of the AI model to maintain the same visual characteristics of characters across different frames or scenes in a video. This includes facial features, clothing, and body type. The video emphasizes the importance of this feature, as it allows for the creation of believable characters that appear natural and realistic, enhancing the overall quality of AI-generated content.

💡Reality and Physics

In the context of the video, 'reality and physics' pertains to the AI model's capacity to create videos that accurately reflect the laws of physics and the appearance of real-world scenarios. This includes correct animations of objects and characters, as well as the portrayal of natural movements and interactions that one would expect in the physical world.

💡AI Video Generators

AI video generators are systems that use artificial intelligence to create videos. They are highlighted in the video as tools that are rapidly evolving, with Story Diffusion being praised for its ability to generate longer, more consistent, and realistic videos compared to other models like Sora and Vidoo.

💡Morphing

Morphing, in the video, refers to the unintended transformation or distortion of characters or objects within a video sequence. The video discusses how Story Diffusion reduces morphing, maintaining character consistency and leading to more believable and higher-quality AI-generated videos.

💡Animation

Animation, as mentioned in the video, is a form of video content where each frame is individually crafted to create the illusion of movement. The video notes that Story Diffusion can handle animation effectively, suggesting its potential for creating full films in animated and anime styles.

💡Resolution

Resolution in the video refers to the number of pixels used to form the image in a video. While the white paper does not specify the resolution of Story Diffusion's output, the video suggests that the previews are at 832 pixels by 832, indicating a high level of detail that could potentially be upscaled for higher definition.

💡Consistent Self-Attention

Consistent self-attention is a technique used by Story Diffusion to ensure that each generated image shares certain attributes or themes, making them visually coherent when viewed as a series. This method is crucial for maintaining character and environmental consistency across the video, which is a key aspect of the model's effectiveness.

💡Story Splitting

Story splitting is a process described in the video where a narrative is divided into multiple text prompts, each describing a part of the story. These prompts are then used to generate a sequence of images that depict the story in a coherent manner. This technique is part of what allows Story Diffusion to create videos with a logical and consistent narrative flow.

💡Motion Prediction Model

The motion prediction model is an aspect of Story Diffusion that predicts how characters or objects will move between frames. This is essential for creating smooth animations and ensuring that the transitions between images in a video sequence are natural and believable.

Highlights

Story Diffusion is a new open source AI video model that creates videos up to 30 seconds long with high character consistency.

The model demonstrates an unbelievable level of character consistency and adherence to reality and physics.

Sora, another model, has issues with morphing and creating extra characters, unlike Story Diffusion.

Story Diffusion understands reality on a deeper level, improving on character consistency.

The model maintains consistency not just in facial features but also in clothing and body type.

Story Diffusion enables the creation of believable characters with perfect consistency across shots and scenes.

The model can generate AI comics by ensuring consistency in face and clothing across a series of images.

Videos generated by Story Diffusion feature little morphing or disfigurement, showcasing anatomically correct characters.

The model produces clips of impressive length, with one example being 23 seconds long.

Story Diffusion's videos show a consistent character throughout, without transformation into a different individual.

The model's expressiveness is notable, particularly in facial expressions and lip movements.

Story Diffusion outperforms other AI video generators in video length, surpassing a recent 16-second clip model.

The model has been developed in China, with ByteDance, the company behind TikTok, cited in the white paper.

There is no information on resolution in the white paper, but previews are rendered at 832 pixels by 832.

The model's lifelike movement and facial expressions are a significant improvement over previous AI video generators.

Story Diffusion can create both realistic videos and animations, with a consistent character rendering.

The model is capable of handling occlusion challenges, remembering the character's appearance before and after being obscured.

Story Diffusion uses consistent self-attention to ensure visual coherence between generated images.

The model employs story splitting, breaking down a story into multiple text prompts to produce a sequence of images.

Story Diffusion can generate consistent images in a training-free manner, transitioning them into fluid and natural videos.

The model shows a significant evolution in character consistency and the ability to create realistic and cohesive scenes.