Made this using mickmumpitz's ComfyUI workflow that lets you animate movement by manually shifting objects or images in the scene. I tested both my higher quality camera and my iPhone, and for this demo I chose the lower quality footage with imperfect lighting. That roughness made it feel more grounded, almost like the movement was captured naturally in real life. I might do another version with higher quality footage later, just to try a different approach. Here's mickmumpitz's tutorial if anyone is interested: https://youtu.be/pUb58eAZ3pc?si=EEcF3XPBRyXPH1BX
https://arstechnica.com/ai/2026/03/google-says-new-turboquant-compression-can-lower-ai-memory-usage-without-sacrificing-quality/
Why has no one created a QR Monster ControlNet for any of the newer models? I feel like this was the best ControlNet. Canny and depth are just not the same.
Thank you Chinese devs for providing for the community if it not for them we'll be still stuck at stable diffusion 1.5
Never forget…
Link: https://huggingface.co/Tongyi-MAI/Z-Image Comfy https://huggingface.co/Comfy-Org/z\_image/tree/main/split\_files/diffusion\_models
https://youtu.be/54IxX6FtKg8 A year ago, I never imagined I’d be able to generate a video like this on my own computer. (5070ti gpu) It’s still rough around the edges, but I wanted to share it anyway. All sound effects, excluding the background music, were generated with MMAudio, and the video was upscaled from 720p to 1080p using SeedVR2.
Workflows from the Neura Market marketplace related to this Stable Diffusion resource