#video-generation

Generating moving pictures.

13 chapters, oldest era first: one idea traced across the books.

From Frames to Worlds 2014–2015 Ch. 1: Why Video Is Hard Dimensionality, temporal coherence, and the blurry-MSE lesson that frames the whole book.
From Frames to Worlds 2014–2026 Appendix: Timeline and Reading List A one-page dated timeline of video generation and every paper cited in this book.
From Frames to Worlds 2016–2019 Ch. 2: GAN Video Scene dynamics, content–motion decomposition, and DVD-GAN's attempt to scale adversarial video.
From Frames to Worlds 2020–2025 Ch. 13: Sound and Speech Lip sync, video-to-audio, and natively audiovisual generation.
From Frames to Worlds 2021–2022 Ch. 4: Tokens for Video VQ tokenization plus autoregressive transformers: VideoGPT, CogVideo, and Phenaki's variable-length generation.
From Frames to Worlds 2022 Ch. 5: Video Diffusion Models Factorized spatio-temporal attention, cascades, and joint image–video training.
From Frames to Worlds 2023 Ch. 6: Latent Video Diffusion Temporal layers bolted onto image LDMs, AnimateDiff, and Stable Video Diffusion's open weights.
From Frames to Worlds 2023 Ch. 7: Video-to-Video and Editing Structure-preserving synthesis — Runway's Gen-1 becomes a product before the model race begins.
From Frames to Worlds 2023 Ch. 8: Image-to-Video and Motion Control Animating stills, camera trajectories, and drag-based motion control.
From Frames to Worlds 2024–2025 Ch. 10: The Commercial Race Gen-3, Kling, Veo, Pika, Luma: capability versus cost per second of footage.
From Frames to Worlds 2024–2025 Ch. 11: Open Video Models The Stable-Diffusion moment for video: CogVideoX, HunyuanVideo, Mochi, and Wan.
From Frames to Worlds 2024–2026 Ch. 14: Making Video Cheap Step distillation for video, causal decoders, and the road to real-time generation.
From Frames to Worlds 2024 Ch. 15: Video Models Become Game Engines Action-conditioned generation: Genie, GameNGen, Oasis, and DIAMOND.