# Text-to-video

iMyFone Novi AI is an AI-powered video generator that can turn text content into high-quality videos, suitable for quickly creating story videos. The product offers diverse video styles, language support, and video size options.

text2video is a tool that can automatically convert text to video. It utilizes technologies like stable-diffusion and edge-tts to segment text into images and speech, then combines them using ffmpeg to create videos with subtitles and voiceover. This tool aims to realize the visualization of novel reading, helping users read textual content in a more vivid and engaging way. It offers free use and allows for customization based on individual needs.

DynamiCrafter is a text-to-video model capable of generating approximately 2-second dynamic videos based on input images and text. This model, trained to generate 576x1024 resolution videos, excels at capturing the dynamic effects of both input images and text descriptions, producing realistic short video content. Suitable for video production, animation creation, and other video generation scenarios, DynamiCrafter serves as a powerful productivity tool for content creators. The model is currently in the research stage and is available for personal and research use only.

VLOGGER is a method for generating text and audio-driven speaking human videos from a single input portrait image. It builds upon the success of recent generative diffusion models. Our method consists of 1) a random human-to-3D motion diffusion model, and 2) a novel diffusion-based architecture that enhances text-to-image models through temporal and spatial control. This approach enables the generation of high-quality videos of variable length, and is easily controllable through advanced expression of human faces and bodies. Unlike previous work, our method does not require individual training for each person, nor does it rely on face detection and cropping. It generates complete images (rather than just faces or lips), and takes into account the wide range of scenarios required for the correct synthesis of human communication (e.g., visible torsos or diverse subject identities).

OpenDiT is an open-source project providing a high-performance implementation of Diffusion Transformer (DiT) based on Colossal-AI. It is designed to enhance the training and inference efficiency of DiT applications, including text-to-video and text-to-image generation. OpenDiT achieves performance improvements through the following technologies: * GPU acceleration up to 80% and 50% memory reduction; * Core optimizations including FlashAttention, Fused AdaLN, and Fused layernorm; * Mixed parallelism methods such as ZeRO, Gemini, and DDP, along with model sharding for ema models to further reduce memory costs; * FastSeq: A novel sequence parallelism method particularly suitable for workloads like DiT, where activations are large but parameters are small. Single-node sequence parallelism can save up to 48% in communication costs and break through the memory limit of a single GPU, reducing overall training and inference time; * Significant performance improvements can be achieved with minimal code modifications; * Users do not need to understand the implementation details of distributed training; * Complete text-to-image and text-to-video generation workflows; * Researchers and engineers can easily use and adapt our workflows to real-world applications without modifying the parallelism part; * Training on ImageNet for text-to-image generation and releasing checkpoints.

MagicVideo-V2 is an end-to-end video generation pipeline that integrates text-to-image models, video motion generators, reference image embedding modules, and frame interpolation modules. Its architecture design enables MagicVideo-V2 to generate visually appealing, high-resolution videos with excellent fidelity and smoothness. Through large-scale user evaluations, it has demonstrated superior performance compared to leading text-to-video systems such as Runway, Pika 1.0, Morph, Moon Valley, and Stable Video Diffusion.

InstructVideo is a method for training text-to-video diffusion models using reward fine-tuning guided by human feedback. It employs an editing-based reward fine-tuning approach, which reduces fine-tuning cost while enhancing efficiency. Leveraging pre-established image reward models, it provides reward signals through segment-wise sparse sampling and temporal decay rewards, significantly improving the visual quality of generated videos. InstructVideo not only enhances the visual quality of generated videos but also maintains strong generalization capabilities. For more information, please visit the official website.

ShortVideoGen is a simple and easy-to-use text-to-video application that uses cutting-edge video and audio generation AI models to help you create personalized videos in seconds. Simply submit a text prompt, specify the frame rate and maximum frame number, choose whether to require sound, wait for the magic to happen, and a video that meets your requirements will be generated.

Polymorf is a text-to-video character generation tool designed for content creators, marketers, and educators. By inputting text and choosing or uploading custom character images, you can create AI videos in minutes. It supports over 40 languages, offers over 100 voice options, and allows you to upload your own voice. Whether you need to make videos for YouTube or TikTok, Polymorf has you covered. You can choose from existing character models or upload your own images. Polymorf works with various video sizes, including vertical, horizontal, and square formats. Sign up for a free trial today!