Generating Video Using Stable Diffusion
Harnessing the power of the Stable Diffusion model, we can generate high-quality images using techniques such as LoRA, text embedding, and ControlNet. A natural progression from static images is toward dynamic content, that is, videos. Can we generate consistent videos using the Stable Diffusion model?
The Stable Diffusion model’s UNet architecture, while effective for single-image processing, lacks contextual awareness when dealing with multiple images. Consequently, generating identical or consistently related images with the same prompt and parameters but different seeds is challenging. The resulting images may vary significantly in color, shape, or style due to the randomness introduced by the model’s nature.
One might consider an image-to-image pipeline or a ControlNet approach, where a video clip is segmented into individual images, and each image is processed sequentially. However, maintaining consistency across the...
