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A repository for making an aesthetic prediction model based on the ConvneXt architecture.
A course in reinforcement learning in the wild
HunyuanVideo-1.5: A leading lightweight video generation model
[CVPR2024 Highlight] VBench - We Evaluate Video Generation
This is the homepage of a new book entitled "Mathematical Foundations of Reinforcement Learning."
The official paper summary of TMLR'25 paper "Survey of Video Diffusion Models: Foundations, Implementations, and Applications"
CVPRW 2025 paper Progressive Autoregressive Video Diffusion Models: https://arxiv.org/abs/2410.08151
基于AI的图片/视频硬字幕去除、文本水印去除,无损分辨率生成去字幕、去水印后的图片/视频文件。无需申请第三方API,本地实现。AI-based tool for removing hard-coded subtitles and text-like watermarks from videos or Pictures.
text and image to video generation: CogVideoX (2024) and CogVideo (ICLR 2023)
This project aim to reproduce Sora (Open AI T2V model), we wish the open source community contribute to this project.
A new multi-shot video understanding benchmark Shot2Story with comprehensive video summaries and detailed shot-level captions.
PyTorch code and models for VJEPA2 self-supervised learning from video.
Official Repo For "BindWeave: Subject-Consistent Video Generation via Cross-Modal Integration"
[ICCV 2025] TokensGen: Harnessing Condensed Tokens for Long Video Generation
Enjoy the magic of Diffusion models!
Official Implementations for Paper - HoloCine: Holistic Generation of Cinematic Multi-Shot Long Video Narratives
Lets make video diffusion practical!
Wan: Open and Advanced Large-Scale Video Generative Models
Wan: Open and Advanced Large-Scale Video Generative Models
Intelligence Integration System with AI and Workflow
"ViMax: Agentic Video Generation (Director, Screenwriter, Producer, and Video Generator All-in-One)"
"DeepCode: Open Agentic Coding (Paper2Code & Text2Web & Text2Backend)"
Resources of our paper "FilmAgent: A Multi-Agent Framework for End-to-End Film Automation in Virtual 3D Spaces". New versions in the making!
MovieAgent: Automated Movie Generation via Multi-Agent CoT Planning
The Best of Both Worlds: Integrating Language Models and Diffusion Models for Video Generation