AI Video Generation Step by Step — Motion Transfer, Diffusion & Flow Explained Visually

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Издатель
How does AI turn a single still image into moving video? This visual, ground-up guide to AI video generation explores motion transfer, diffusion, score matching, flow matching, and the surprising idea they share.

First, we look at motion transfer: copying real motion from a driving video onto a still image. Then we make the leap to diffusion — the foundation behind many of today's generative AI systems — where motion can emerge from noise.

From there, we build up the larger family of generative methods and reveal a common idea: predict a field, then follow it. We'll visualize flow matching, score matching and diffusion, normalizing flows, and even train two toy models on-screen so you can see what they're actually learning.

The explanation is grounded in the real algorithms and architectures: First-Order Motion Model, Stable Video Diffusion, DDPM, score-based SDEs, Flow Matching / Rectified Flow, RealNVP, latent diffusion, and VAEs.

This video is a companion to How Does AI Generate Pictures From Words? — Visualize Attention, VQ-GAN, and CLIP. If that video asked how words become pictures, this one asks: how does a picture become a video?

#AI #AIVideo #AIVideoGeneration #GenerativeAI #Diffusion #FlowMatching #MachineLearning

Chapters
0:00 A photo comes alive
0:20 Motion is a field (motion transfer)
1:06 Finding the keypoints
1:45 The dense motion field (U-Net)
2:30 How it learned (training)
3:19 The leap: copy → imagine
3:49 One photo, many futures (diffusion begins)
4:48 Diffusion works in a latent (the VAE)
5:32 Mixing in your photo (conditioning)
6:20 The U-Net denoiser
6:55 Spatial attention
7:39 Temporal attention
8:15 The denoising loop
8:47 How the denoiser learns (training)
9:52 The freedom: copy can't, imagine can
10:30 The reveal: copied vs. imagined
11:12 The space of all videos
11:44 Flow matching
12:09 Score matching / diffusion
12:45 Normalizing flows
13:14 The networks behind them
13:45 Trained for real: diffusion vs. flow
14:35 The normalizing-flow cousin
15:23 It was there all along
15:47 What it all means

Made with Manim · Narration: ElevenLabs ("Alice").

#AI #AIVideo #AIVideoGeneration #GenerativeAI #Diffusion #FlowMatching #MachineLearning
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