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T2I -> T2V

IDYearNameNoteTagsLink
2025Wan. Wan-AI/Wan2.1-T2V-14Bhttps://huggingface.co/Wan-AI/Wan2.1-T2V-14B
2025CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer
2024Hunyuanvideo: A systematic framework for large video generative models
812024CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformers1. 使用预训练T2I模型CogView2
2. 先生成1 fps关键帧再递归向中间插帧
3. 引入temporal channel，并以混合因子\(\alpha\)与spatial channel混合		CogView2（60亿参数）, Transformer Basedlink
1072023Text2Video-Zero: Text-to-Image Diffusion Models are Zero-Shot Video Generatorslink
582023ModelScope Text-to-Video Technical Reportlink
2023ZeroScope✅ ZeroScope 在 ModelScope 上 finetune，使用了非常小但质量非常高的数据，得到了高分辨率的生成效果。
502023Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large DatasetsScaling latent video diffusion models to large datasets
Data Processing and Annotation		link
2023Wang et al., “LAVIE: High-Quality Video Generation with Cascaded Latent Diffusion Models,”Joint image-video finetuning with curriculum learning
✅ 提供了一套高质量数据集，生成的视频质量也更好（训练集很重要）。
2023Chen et al., “VideoCrafter1: Open Diffusion Models for High-Quality Video Generation,”LDM

T2V -> Improved Text-2-Video

IDYearNameNoteTagsLink
1052025.5.27Think Before You Diffuse: LLMs-Guided Physics-Aware Video Generation1. 使用LLM分析视频生成的预期效果，用于引导生成
2. LLM对生成结果的评价也作为模型训练的Loss项
3. 基于Wan大模型的LoRA微调		数据集, LLM, LoRA, 数据集，物理link

P74

其它相关工作
" Robot dancing in times square,” arXiv 2023." Clown fish swimming through the coral reef,” arXiv 2023." Melting ice cream dripping down the cone,” arXiv 2023." Hyper-realistic photo of an abandoned industrial site during a storm,” arXiv 2023.

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