这份资料并非传统意义上的视频教程，而是一套针对 OpenAI Sora 视频生成模型的实践素材库。它核心解决的问题不是教你如何搭建底层扩散模型架构，而是指导你如何通过自然语言提示词精准控制视频生成的画面内容、运动逻辑与视觉风格。对于打算转岗至 AIGC 应用层、短视频内容生成或交互式媒体开发的从业者，这直接填补了“会写代码但不懂如何驾驭多模态生成模型”的能力缺口。适合具备基础 Python 能力，但缺乏 AI 视频生成实战经验的学习者；如果你是纯零基础的程序员，建议先补习基本的提示工程（Prompt Engineering）概念再进入本资源。

建议优先研读配套的提示词清单，将其作为核心教材。不要漫无目的地刷看上百个演示视频，那样效率极低且容易陷入视觉疲劳。正确的方法是采用“逆向拆解”策略：先挑选几个具有代表性的高质量视频样本，例如涉及复杂物理交互或特定镜头语言的案例，严格对照旁边的提示词记录，逐字分析提示词中的时间顺序描述、主体动作定义、环境光影设定以及镜头运动指令（如推拉摇移）是如何映射到最终画面中的。通过这种对比，你可以建立起“意图-提示词-结果”的对应直觉，这是掌握生成式视频工具的关键。

学完这套资料后，你应当能够独立完成以下任务：面对一个特定的创意短片需求，在 10 分钟内编写出包含主体、环境、动作、风格、画质参数的高质量结构化提示词；能够根据生成的初步结果，通过调整否定提示词或优化空间描述，有效修正画面穿模、动作僵硬或光影不一致等常见问题；初步具备评估 AI 生成视频可商用性的判断能力。

在资料配合练习方面，不要只停留在阅读层面。你需要准备一个本地化的工作流，建议结合开源的视频生成框架或云服务平台。将资料中的提示词批量输入测试，记录每次生成结果的差异。重点练习如何控制视频的连贯性，比如如何让主角在连续镜头中保持外观一致，以及如何处理长视频中的叙事逻辑。通过反复调试提示词与观察画面反馈的闭环练习，才能真正将静态的文字知识转化为动态的内容生产能力，从而在未来涉及虚拟角色驱动、互动视频制作或品牌视觉资产生成的项目中找到立足之地。

课程目录

📁 Sora-AI视频全网最全收集（100多个）
📁 Promts
Sora-AI视频全网最全收集-对应提示词.xlsx [18.6 KB]
📁 Videos
XFQY4fgZUB6GMw9q.mp4 [4.5 MB]
closeup-man-in-glasses.mp4 [8.9 MB]
ssstwitter.com_1708027050964.mp4 [2.8 MB]
d0.mp4 [12.5 MB]
italian-pup.mp4 [4.9 MB]
paper-airplanes.mp4 [17.9 MB]
dogs-downtown.mp4 [5.8 MB]
Od5aGL5Ml4ycuR-x.mp4 [5.2 MB]
monster-with-melting-candle.mp4 [16.2 MB]
d2.mp4 [9.0 MB]
6.mp4 [2.8 MB]
OVgwFsijR_mmi6fY.mp4 [2.2 MB]
simulation_7.mp4 [12.3 MB]
robot-video-game.mp4 [10.5 MB]
CE6XePnWBZWTKNLc.mp4 [3.8 MB]
otter-on-surfboard.mp4 [16.0 MB]
suv-in-the-dust.mp4 [12.0 MB]
bike_1.mp4 [7.5 MB]
photoreal-train.mp4 [3.8 MB]
vlogger-corgi.mp4 [7.5 MB]
c1.mp4 [8.2 MB]
ssstwitter.com_1708295424095.mp4 [1.9 MB]
prompting_5.mp4 [564.0 KB]
happy-cat.mp4 [7.2 MB]
victoria-crowned-pigeon.mp4 [7.7 MB]
chameleon.mp4 [8.6 MB]
d1.mp4 [13.4 MB]
big-eyed-fluff-ball.mp4 [9.6 MB]
birds-over-river.mp4 [10.8 MB]
sampling_2.mp4 [10.4 MB]
octopus-and-crab.mp4 [3.5 MB]
simulation_4.mp4 [2.9 MB]
auBXTZ_s-sWYY4Xc.mp4 [2.8 MB]
prompting_1.mp4 [1.0 MB]
ssstwitter.com_1708027218755.mp4 [2.0 MB]
ships-in-coffee.mp4 [13.6 MB]
U7_eoLJ3HCUgIBu8.mp4 [2.2 MB]
tokyo-walk.mp4 [46.2 MB]
an-old-man-wearing-purple-overalls-and-cowboy-boots-taking-a-pleasant-stroll-in-Antarctica-during-a-winter-storm.mp4 [2.3 MB]
ssstwitter.com_1708242793064.mp4 [6.0 MB]
原搬运者弄太多水印了，我尽力去掉了一些……想要更多无水印版本请点这里.txt [98.0 B]
a-woman-wearing-a-green-dress-and-a-sun-hat-taking-a-pleasant-stroll-in-Mumbai-India-during-a-beautiful-sunset.mp4 [3.0 MB]
art-museum.mp4 [4.0 MB]
chinese-new-year-dragon.mp4 [13.5 MB]
a0.mp4 [10.2 MB]
prompting_3.mp4 [947.0 KB]
c0.mp4 [7.9 MB]
e1.mp4 [8.7 MB]
simulation_0.mp4 [12.7 MB]
HWv91bL5DRAhAHz8_1.mp4 [11.3 MB]
stack-of-tvs.mp4 [11.1 MB]
a2.mp4 [11.9 MB]
cloud-man.mp4 [10.7 MB]
origami-undersea.mp4 [61.5 MB]
15.mp4 [4.6 MB]
wzXcdViEEYGvz6kv.mp4 [3.7 MB]
LKvuCYNyu2IWkY8v.mp4 [4.9 MB]
ssstwitter.com_1708024200398.mp4 [3.8 MB]
wolves.mp4 [4.6 MB]
18.mp4 [2.2 MB]
e2.mp4 [14.6 MB]
a1.mp4 [10.2 MB]
flower-blooming.mp4 [1.3 MB]
a-toy-robot-wearing-blue-jeans-and-a-white-t-shirt-taking-a-pleasant-stroll-in-Antarctica-during-a-beautiful-sunset.mp4 [3.0 MB]
an-adorable-kangaroo-wearing-a-green-dress-and-a-sun-hat-taking-a-pleasant-stroll-in-Johannesburg-South-Africa-during-a-colorful-festival.mp4 [3.9 MB]
simulation_6.mp4 [10.9 MB]
b0.mp4 [8.8 MB]
CFzxxpSCn8IaARWi.mp4 [4.3 MB]
1ESXz6gPL_jYm6ox.mp4 [2.8 MB]
amalfi-coast.mp4 [8.5 MB]
e3HK1GSUAgNxC2EY.mp4 [4.0 MB]
zgD5gULAiUj4Mmro.mp4 [15.5 MB]
x-tDLpMBPun0BIYt.mp4 [2.3 MB]
train-window.mp4 [3.4 MB]
snow-dogs.mp4 [15.4 MB]
tUfDESZsQFhdDW9S.mp4 [4.4 MB]
simulation_1.mp4 [6.6 MB]
Several giant wooly mammoths.mp4 [12.4 MB]
puppy-cloning.mp4 [1.6 MB]
simulation_5.mp4 [2.6 MB]
lagos.mp4 [7.8 MB]
discussion_0.mp4 [1.2 MB]
uRkXLMR6UXciZNX8.mp4 [3.3 MB]
e0.mp4 [6.6 MB]
tiny-construction.mp4 [12.3 MB]
ssstwitter.com_1708024354050.mp4 [3.0 MB]
dancing-kangaroo.mp4 [2.8 MB]
backward-jogger.mp4 [4.1 MB]
Y-hqbC_qKQ6d7ZaN.mp4 [3.5 MB]
petri-dish-pandas.mp4 [2.4 MB]
2r6R4jfZdso_d6YU.mp4 [1.4 MB]
S18_Hii3-CRsx4Vo.mp4 [1.5 MB]
chair-archaeology.mp4 [6.4 MB]
basketball-explosion.mp4 [1.8 MB]
aquarium-nyc.mp4 [21.5 MB]
prompting_7.mp4 [5.2 MB]
yDF9Gv87H3tnHRoG.mp4 [5.2 MB]
wwaEhwkd7vryYZLs.mp4 [2.0 MB]
rNiKCJeJyf8Ue4gS.mp4 [2.8 MB]
UST-fn-RvhJwMR5S.mp4 [2.0 MB]
这些视频全都可以拿来配音，二创，发到网上，很火.txt [93.0 B]
📁 Sora学习论文
📁 sora学习论文-在线试看版
Scaling Autoregressive Models for Content-Rich Text-to-Image Generation.pdf [48.7 MB]
Attention Is All You Need.pdf [2.1 MB]
Photorealistic Video Generation with Diffusion Models.pdf [5.5 MB]
MoCoGAN- Decomposing Motion and Content for Video Generation.pdf [6.4 MB]
Masked Autoencoders Are Scalable Vision Learners.pdf [7.1 MB]
Generating Long Videos of Dynamic Scenes.pdf [10.3 MB]
Imagen Video- High Definition Video Generation with Diffusion Models.pdf [8.5 MB]
Improving Image Generation with Better Captions.pdf [26.8 MB]
Scalable Diffusion Models with Transformers .pdf [41.8 MB]
Improved Denoising Diffusion Probabilistic Models.pdf [11.9 MB]
Deep Unsupervised Learning using Nonequilibrium Thermodynamics.pdf [4.2 MB]
High-Resolution Image Synthesis with Latent Diffusion Models.pdf [39.0 MB]
Patch n' Pack- NaViT, a Vision Transformer for any Aspect Ratio and Resolution.pdf [1.8 MB]
ViViT- A Video Vision Transformer.pdf [4.5 MB]
World Models.pdf [3.0 MB]
Recurrent Environment Simulators.pdf [8.0 MB]
Diffusion Models Beat GANs on Image Synthesis.pdf [38.0 MB]
An Image is Worth 16x16 Words- Transformers for Image Recognition at Scale.pdf [3.6 MB]
NUWA- Visual Synthesis Pre-training for Neural visUal World creAtion .pdf [7.0 MB]
Hierarchical Text-Conditional Image Generation with CLIP Latents.pdf [40.9 MB]
VideoGPT- Video Generation using VQ-VAE and Transformers.pdf [2.6 MB]
Generative Pretraining From Pixels.pdf [2.0 MB]
Adversarial Video Generation on Complex Datasets.pdf [9.5 MB]
Language Models are Few-Shot Learners.pdf [6.5 MB]
SDEdit- Guided Image Synthesis and Editing with Stochastic Differential Equations .pdf [11.8 MB]
Auto-Encoding Variational Bayes.pdf [3.7 MB]
Denoising Diffusion Probabilistic Models.pdf [9.8 MB]
Elucidating the Design Space of Diffusion-Based Generative Models.pdf [18.3 MB]
Generating Videos with Scene Dynamics.pdf [2.0 MB]
Zero-Shot Text-to-Image Generation.pdf [9.7 MB]
Unsupervised Learning of Video Representations using LSTMs.pdf [2.2 MB]
Align your Latents- High-Resolution Video Synthesis with Latent Diffusion Models.pdf [11.5 MB]
sora学习论文-打包防和谐.exe [361.4 MB]
sora学习论文-打包防和谐.zip [370.1 MB]
📁 Sora专属提示词库
特殊环境篇.xlsx [12.4 KB]
天气篇.xlsx [14.3 KB]
场景篇.xlsx [15.9 KB]
动作与姿态偏.xlsx [14.4 KB]
故事线索篇.xlsx [17.7 KB]
📁 Sora专属教程
📁 3、进阶篇：构建高效提示词
📁 1、关键词优化技巧
使用具体、生动的词汇.docx [15.7 KB]
避免冗余和模糊表达.docx [15.9 KB]
📁 2、情感引导与观众共鸣
利用情感性提示词调动观众情绪.docx [15.9 KB]
创造共鸣与参与感.docx [16.5 KB]
📁 3、指令性提示词的巧妙运用
指导模型生成符合预期的视频内容.docx [14.3 KB]
应对复杂场景和特定需求.docx [16.0 KB]
📁 2、基础篇：了解提示词
📁 2、不同类型的提示词及其作用
指令性提示词及其作用.docx [15.7 KB]
描述性提示词及其作用.docx [15.9 KB]
情感性提示词及其作用.docx [15.5 KB]
1、提示词的定义与功能.docx [14.9 KB]
3、如何选择适合视频主题的提示词.docx [15.9 KB]
📁 5、实战篇：案例分析与操作指导
利用Sora文生视频模型生成视频内容.docx [17.7 KB]
针对不同主题的视频进行提示词设计.docx [16.6 KB]
根据生成结果调整和优化提示词的策略.docx [15.6 KB]
📁 6、总结与展望
本教程所学内容的回顾与总结.docx [14.0 KB]
Sora文生视频模型与提示词未来的发展趋势.docx [14.9 KB]
📁 1、前言
2、本教程的目标与学习内容.docx [14.8 KB]
1、sora提示词的重要性及其在视频创作中的应用.docx [16.6 KB]
📁 4、高级篇：提示词与视频创作的融合
3、风格塑造：通过提示词实现视频风格的多样化.docx [15.9 KB]
2、叙事构建：通过提示词规划视频结构和节奏.docx [17.7 KB]
1、创意启发：利用提示词激发创作灵感.docx [15.7 KB]
📁 Sora提示词技巧
Sora模型关于背景详细的提示词技巧.docx [15.8 KB]
Sora关于情感氛围的提示词技巧.docx [15.8 KB]
Sora关于透视和角度的提示词技巧.docx [15.3 KB]
Sora关于视频分镜的提示词技巧.docx [15.5 KB]
Sora对于动态元素的提示词技巧.docx [15.5 KB]
sora明确主体的提示词技巧.docx [15.2 KB]
Sora关于情境细节的提示词技巧.docx [15.1 KB]
sora关于详细描述的提示词技巧.docx [15.7 KB]
Sora关于风格和艺术元素的提示词技巧.docx [15.2 KB]
Sora大模型关于颜色和光线的提示词技巧.docx [17.4 KB]
SORA五个快速变现方向.docx [12.3 KB]
SoraAI视频工具优先体验资格.docx [128.1 KB]
关于Sora：什么是Sora？一文带你看懂Sora！.txt [54.0 B]