Text-to-video model

A text-to-video model is a machine learning model which takes as input a natural language description and produces a video matching that description.^[1]

Video prediction on making objects realistic in a stable background is performed by using recurrent neural network for a sequence to sequence model with a connector convolutional neural network encoding and decoding each frame pixel by pixel,^[2] creating video using deep learning.^[3]

Methodology

• Data collection and data set preparation using clear video from kinetic human action video.
• Training the convolutional neural network for making video.
• Keywords extraction from text using natural-language programming .
• Testing of Data set in conditional generative model for existing static and dynamic information from text by variational autoencoder and generative adversarial network.

Models

There are different models including open source models. CogVideo presented their code in GitHub.^[4] Meta Platforms uses text-to-video with makeavideo.studio.^[5][6][7]Google used Imagen Video for converting text-to-video.^{[8][9][10][11][12]}

Antonia Antonova presented another model.^[13]

In March 2023, a landmark research paper by Alibaba research was published, applying many of the principles found in latent image diffusion models to video generation.^[14][15] Many services like https://kaiber.ai/ or https://reemix.co/ have since adopted similar approaches to video generation in their respective products.

Although alternative approaches exist,^[16] full latent diffusion models are currently regarded to be state of the art for video diffusion.

References

1. Artificial Intelligence Index Report 2023 (PDF) (Report). Stanford Institute for Human-Centered Artificial Intelligence. p. 98. Multiple high quality text-to-video models, AI systems that can generate video clips from prompted text, were released in 2022.
2. "Leading India" (PDF).
3. Narain, Rohit (2021-12-29). "Smart Video Generation from Text Using Deep Neural Networks". Retrieved 2022-10-12.
4. CogVideo, THUDM, 2022-10-12, retrieved 2022-10-12
5. Davies, Teli (2022-09-29). "Make-A-Video: Meta AI's New Model For Text-To-Video Generation". W&B. Retrieved 2022-10-12.
6. Monge, Jim Clyde (2022-08-03). "This AI Can Create Video From Text Prompt". Medium. Retrieved 2022-10-12.
7. "Meta's Make-A-Video AI creates videos from text". www.fonearena.com. Retrieved 2022-10-12.
8. "google: Google takes on Meta, introduces own video-generating AI - The Economic Times". m.economictimes.com. Retrieved 2022-10-12.
9. Monge, Jim Clyde (2022-08-03). "This AI Can Create Video From Text Prompt". Medium. Retrieved 2022-10-12.
10. "Nuh-uh, Meta, we can do text-to-video AI, too, says Google". www.theregister.com. Retrieved 2022-10-12.
11. "Papers with Code - See, Plan, Predict: Language-guided Cognitive Planning with Video Prediction". paperswithcode.com. Retrieved 2022-10-12.
12. "Papers with Code - Text-driven Video Prediction". paperswithcode.com. Retrieved 2022-10-12.
13. "Text to Video Generation". Antonia Antonova. Retrieved 2022-10-12.
14. "Home - DAMO Academy". damo.alibaba.com. Retrieved 2023-08-12.
15. Luo, Zhengxiong; Chen, Dayou; Zhang, Yingya; Huang, Yan; Wang, Liang; Shen, Yujun; Zhao, Deli; Zhou, Jingren; Tan, Tieniu (2023). "VideoFusion: Decomposed Diffusion Models for High-Quality Video Generation". doi:10.48550/ARXIV.2303.08320. {{cite journal}}: Cite journal requires |journal= (help)
16. Text2Video-Zero, Picsart AI Research (PAIR), 2023-08-12, retrieved 2023-08-12