MiniSora 社区

👋 加入我们的 微信

MiniSora 开源社区定位为由社区成员自发组织的社区驱动型倡议。MiniSora 社区旨在探索 Sora 的实现路径及未来发展方向。

• 将定期与 Sora 团队及社区举行圆桌讨论，探讨各种可能性。
• 深入研究现有的视频生成技术路径。
• 引领复现与 Sora 相关的论文或研究成果，例如 DiT（MiniSora-DiT）等。
• 对 Sora 相关技术和其实现进行全面回顾，即“从 DDPM 到 Sora：基于扩散模型的视频生成模型综述”。

热点新闻

• OpenAI Sora 即将发布！
• Movie Gen：一系列媒体基础模型
• Stable Diffusion 3：MM-DiT：用于高分辨率图像合成的缩放修正流变换器
• MiniSora-DiT：使用 XTuner 复现 DiT 论文
• MiniSora 简介及复现 Sora 的最新进展

MiniSora 社区复现小组

MiniSora 复现 Sora 的目标

1. GPU 友好：理想情况下，对 GPU 显存大小和 GPU 数量的要求较低，例如能够使用类似 8 张 A100 80G 显卡、8 张 A6000 48G 显卡或 RTX4090 24G 显卡的算力进行训练和推理。
2. 训练效率：无需长时间训练即可取得良好效果。
3. 推理效率：在推理生成视频时，无需高长度或高分辨率；可接受的参数包括 3–10 秒长度和 480p 分辨率。

MiniSora-DiT：使用 XTuner 复现 DiT 论文

https://github.com/mini-sora/minisora-DiT

要求

我们正在招募 MiniSora 社区贡献者，使用 XTuner 复现 DiT。

我们希望社区成员具备以下特点：

1. 熟悉 OpenMMLab MMEngine 机制。
2. 熟悉 DiT。

背景

1. DiT 的作者与 Sora 的作者相同。
2. XTuner 具有高效训练长度为 1000K 序列的核心技术。

支持

1. 计算资源：2 张 A100。
2. 来自 XTuner 核心开发者 P佬@pppppM 的大力支持。

最近的圆桌讨论

Stable Diffusion 3 论文解读：MM-DiT

演讲者：MMagic 核心贡献者

直播时间：12 月 3 日 20:00

亮点：MMagic 核心贡献者将带领大家解读 Stable Diffusion 3 论文，讨论 Stable Diffusion 3 的架构细节和设计原则。

PPT：飞书链接

往期讨论亮点

与 Sora 的夜间谈话：视频扩散概述

知乎笔记：生成式扩散模型综述：生成式扩散模型概览

论文阅读计划

• Sora：从文本创建视频

• 技术报告：视频生成模型作为世界模拟器

• Latte：Latte：用于视频生成的潜在扩散 Transformer

  • Latte 论文解读（简体中文），知乎（简体中文）

• DiT：具有 Transformer 的可扩展扩散模型

• Stable Cascade（ICLR 24 论文）：Würstchen：用于大规模文本到图像扩散模型的高效架构

• Stable Diffusion 3：MM-DiT：用于高分辨率图像合成的缩放修正流变换器

  • SD3 论文解读（简体中文），知乎（简体中文）

• 更新中...

演讲者招募

• DiT（ICCV 23 论文）
• Stable Cascade（ICLR 24 论文）

相关工作

• 01 扩散模型
• 02 扩散Transformer
• 03 基准视频生成模型
• 04 扩散UNet
• 05 视频生成
• 06 数据集
  • 6.1 公开数据集
  • 6.2 视频增强方法
    • 6.2.1 基础变换
    • 6.2.2 特征空间
    • 6.2.3 基于GAN的增强
    • 6.2.4 基于编码器/解码器的方法
    • 6.2.5 仿真
• 07 补丁化方法
• 08 长上下文
• 09 音频相关资源
• 10 一致性
• 11 提示工程
• 12 安全性
• 13 世界模型
• 14 视频压缩
• 15 Mamba
  • 15.1 理论基础与模型架构
  • 15.2 图像生成与视觉应用
  • 15.3 视频处理与理解
  • 15.4 医学图像处理
• 16 现有高质量资源
• 17 高效训练
  • 17.1 基于并行的方法
    • 17.1.1 数据并行(DP)
    • 17.1.2 模型并行(MP)
    • 17.1.3 流水线并行(PP)
    • 17.1.4 广义并行(GP)
    • 17.1.5 ZeRO并行(ZP)
  • 17.2 非并行方法
    • 17.2.1 减少激活内存
    • 17.2.2 CPU卸载
    • 17.2.3 内存高效的优化器
  • 17.3 新型结构
• 18 高效推理
  • 18.1 减少采样步数
    • 18.1.1 连续步数
    • 18.1.2 快速采样
    • 18.1.3 步数蒸馏
  • 18.2 优化推理
    • 18.2.1 低比特量化
    • 18.2.2 并行/稀疏推理

01 Diffusion Models
Paper	Link
1) Guided-Diffusion: Diffusion Models Beat GANs on Image Synthesis	NeurIPS 21 Paper, GitHub
2) Latent Diffusion: High-Resolution Image Synthesis with Latent Diffusion Models	CVPR 22 Paper, GitHub
3) EDM: Elucidating the Design Space of Diffusion-Based Generative Models	NeurIPS 22 Paper, GitHub
4) DDPM: Denoising Diffusion Probabilistic Models	NeurIPS 20 Paper, GitHub
5) DDIM: Denoising Diffusion Implicit Models	ICLR 21 Paper, GitHub
6) Score-Based Diffusion: Score-Based Generative Modeling through Stochastic Differential Equations	ICLR 21 Paper, GitHub, Blog
7) Stable Cascade: Würstchen: An efficient architecture for large-scale text-to-image diffusion models	ICLR 24 Paper, GitHub, Blog
8) Diffusion Models in Vision: A Survey	TPAMI 23 Paper, GitHub
9) Improved DDPM: Improved Denoising Diffusion Probabilistic Models	ICML 21 Paper, Github
10) Classifier-free diffusion guidance	NIPS 21 Paper
11) Glide: Towards photorealistic image generation and editing with text-guided diffusion models	Paper, Github
12) VQ-DDM: Global Context with Discrete Diffusion in Vector Quantised Modelling for Image Generation	CVPR 22 Paper, Github
13) Diffusion Models for Medical Anomaly Detection	Paper, Github
14) Generation of Anonymous Chest Radiographs Using Latent Diffusion Models for Training Thoracic Abnormality Classification Systems	Paper
15) DiffusionDet: Diffusion Model for Object Detection	ICCV 23 Paper, Github
16) Label-efficient semantic segmentation with diffusion models	ICLR 22 Paper, Github, Project
02 Diffusion Transformer
Paper	Link
1) UViT: All are Worth Words: A ViT Backbone for Diffusion Models	CVPR 23 Paper, GitHub, ModelScope
2) DiT: Scalable Diffusion Models with Transformers	ICCV 23 Paper, GitHub, Project, ModelScope
3) SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers	ArXiv 23, GitHub, ModelScope
4) FiT: Flexible Vision Transformer for Diffusion Model	ArXiv 24, GitHub
5) k-diffusion: Scalable High-Resolution Pixel-Space Image Synthesis with Hourglass Diffusion Transformers	ArXiv 24, GitHub
6) Large-DiT: Large Diffusion Transformer	GitHub
7) VisionLLaMA: A Unified LLaMA Interface for Vision Tasks	ArXiv 24, GitHub
8) Stable Diffusion 3: MM-DiT: Scaling Rectified Flow Transformers for High-Resolution Image Synthesis	Paper, Blog
9) PIXART-Σ: Weak-to-Strong Training of Diffusion Transformer for 4K Text-to-Image Generation	ArXiv 24, Project
10) PIXART-α: Fast Training of Diffusion Transformer for Photorealistic Text-To-Image Synthesis	ArXiv 23, GitHub ModelScope
11) PIXART-δ: Fast and Controllable Image Generation With Latent Consistency Model	ArXiv 24,
12) Lumina-T2X: Transforming Text into Any Modality, Resolution, and Duration via Flow-based Large Diffusion Transformers	ArXiv 24, GitHub
13) DDM: Deconstructing Denoising Diffusion Models for Self-Supervised Learning	ArXiv 24
14) Autoregressive Image Generation without Vector Quantization	ArXiv 24, GitHub
15) Transfusion: Predict the Next Token and Diffuse Images with One Multi-Modal Model	ArXiv 24
16) Scaling Diffusion Language Models via Adaptation from Autoregressive Models	ArXiv 24
17) Large Language Diffusion Models	ArXiv 25
03 Baseline Video Generation Models
Paper	Link
1) ViViT: A Video Vision Transformer	ICCV 21 Paper, GitHub
2) VideoLDM: Align your Latents: High-Resolution Video Synthesis with Latent Diffusion Models	CVPR 23 Paper
3) DiT: Scalable Diffusion Models with Transformers	ICCV 23 Paper, Github, Project, ModelScope
4) Text2Video-Zero: Text-to-Image Diffusion Models are Zero-Shot Video Generators	ArXiv 23, GitHub
5) Latte: Latent Diffusion Transformer for Video Generation	ArXiv 24, GitHub, Project, ModelScope
04 Diffusion UNet
Paper	Link
1) Taming Transformers for High-Resolution Image Synthesis	CVPR 21 Paper,GitHub ,Project
2) ELLA: Equip Diffusion Models with LLM for Enhanced Semantic Alignment	ArXiv 24 Github
05 Video Generation
Paper	Link
1) Animatediff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning	ICLR 24 Paper, GitHub, ModelScope
2) I2VGen-XL: High-Quality Image-to-Video Synthesis via Cascaded Diffusion Models	ArXiv 23, GitHub, ModelScope
3) Imagen Video: High Definition Video Generation with Diffusion Models	ArXiv 22
4) MoCoGAN: Decomposing Motion and Content for Video Generation	CVPR 18 Paper
5) Adversarial Video Generation on Complex Datasets	Paper
6) W.A.L.T: Photorealistic Video Generation with Diffusion Models	ArXiv 23, Project
7) VideoGPT: Video Generation using VQ-VAE and Transformers	ArXiv 21, GitHub
8) Video Diffusion Models	ArXiv 22, GitHub, Project
9) MCVD: Masked Conditional Video Diffusion for Prediction, Generation, and Interpolation	NeurIPS 22 Paper, GitHub, Project, Blog
10) VideoPoet: A Large Language Model for Zero-Shot Video Generation	ArXiv 23, Project, Blog
11) MAGVIT: Masked Generative Video Transformer	CVPR 23 Paper, GitHub, Project, Colab
12) EMO: Emote Portrait Alive - Generating Expressive Portrait Videos with Audio2Video Diffusion Model under Weak Conditions	ArXiv 24, GitHub, Project
13) SimDA: Simple Diffusion Adapter for Efficient Video Generation	Paper, GitHub, Project
14) StableVideo: Text-driven Consistency-aware Diffusion Video Editing	ICCV 23 Paper, GitHub, Project
15) SVD: Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets	Paper, GitHub
16) ADD: Adversarial Diffusion Distillation	Paper, GitHub
17) GenTron: Diffusion Transformers for Image and Video Generation	CVPR 24 Paper, Project
18) LFDM: Conditional Image-to-Video Generation with Latent Flow Diffusion Models	CVPR 23 Paper, GitHub
19) MotionDirector: Motion Customization of Text-to-Video Diffusion Models	ArXiv 23, GitHub
20) TGAN-ODE: Latent Neural Differential Equations for Video Generation	Paper, GitHub
21) VideoCrafter1: Open Diffusion Models for High-Quality Video Generation	ArXiv 23, GitHub
22) VideoCrafter2: Overcoming Data Limitations for High-Quality Video Diffusion Models	ArXiv 24, GitHub
23) LVDM: Latent Video Diffusion Models for High-Fidelity Long Video Generation	ArXiv 22, GitHub
24) LaVie: High-Quality Video Generation with Cascaded Latent Diffusion Models	ArXiv 23, GitHub, Project
25) PYoCo: Preserve Your Own Correlation: A Noise Prior for Video Diffusion Models	ICCV 23 Paper, Project
26) VideoFusion: Decomposed Diffusion Models for High-Quality Video Generation	CVPR 23 Paper
27) Movie Gen: A Cast of Media Foundation Models	Paper, Project
28) Step-Video-T2V Technical Report: The Practice, Challenges, and Future of Video Foundation Model	ArXiv 25, Project
06 Dataset
6.1 Public Datasets
Dataset Name - Paper	Link
1) Panda-70M - Panda-70M: Captioning 70M Videos with Multiple Cross-Modality Teachers 70M Clips, 720P, Downloadable	CVPR 24 Paper, Github, Project, ModelScope
2) InternVid-10M - InternVid: A Large-scale Video-Text Dataset for Multimodal Understanding and Generation 10M Clips, 720P, Downloadable	ArXiv 24, Github
3) CelebV-Text - CelebV-Text: A Large-Scale Facial Text-Video Dataset 70K Clips, 720P, Downloadable	CVPR 23 Paper, Github, Project
4) HD-VG-130M - VideoFactory: Swap Attention in Spatiotemporal Diffusions for Text-to-Video Generation 130M Clips, 720P, Downloadable	ArXiv 23, Github, Tool
5) HD-VILA-100M - Advancing High-Resolution Video-Language Representation with Large-Scale Video Transcriptions 100M Clips, 720P, Downloadable	CVPR 22 Paper, Github
6) VideoCC - Learning Audio-Video Modalities from Image Captions 10.3M Clips, 720P, Downloadable	ECCV 22 Paper, Github
7) YT-Temporal-180M - MERLOT: Multimodal Neural Script Knowledge Models 180M Clips, 480P, Downloadable	NeurIPS 21 Paper, Github, Project
8) HowTo100M - HowTo100M: Learning a Text-Video Embedding by Watching Hundred Million Narrated Video Clips 136M Clips, 240P, Downloadable	ICCV 19 Paper, Github, Project
9) UCF101 - UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild 13K Clips, 240P, Downloadable	CVPR 12 Paper, Project
10) MSVD - Collecting Highly Parallel Data for Paraphrase Evaluation 122K Clips, 240P, Downloadable	ACL 11 Paper, Project
11) Fashion-Text2Video - A human video dataset with rich label and text annotations 600 Videos, 480P, Downloadable	ArXiv 23, Project
12) LAION-5B - A dataset of 5,85 billion CLIP-filtered image-text pairs, 14x bigger than LAION-400M 5B Clips, Downloadable	NeurIPS 22 Paper, Project
13) ActivityNet Captions - ActivityNet Captions contains 20k videos amounting to 849 video hours with 100k total descriptions, each with its unique start and end time 20k videos, Downloadable	Arxiv 17 Paper, Project
14) MSR-VTT - A large-scale video benchmark for video understanding 10k Clips, Downloadable	CVPR 16 Paper, Project
15) The Cityscapes Dataset - Benchmark suite and evaluation server for pixel-level, instance-level, and panoptic semantic labeling Downloadable	Arxiv 16 Paper, Project
16) Youku-mPLUG - First open-source large-scale Chinese video text dataset Downloadable	ArXiv 23, Project, ModelScope
17) VidProM - VidProM: A Million-scale Real Prompt-Gallery Dataset for Text-to-Video Diffusion Models 6.69M, Downloadable	ArXiv 24, Github
18) Pixabay100 - A video dataset collected from Pixabay Downloadable	Github
19) WebVid - Large-scale text-video dataset, containing 10 million video-text pairs scraped from the stock footage sites Long Durations and Structured Captions	ArXiv 21, Project , ModelScope
20) MiraData(Mini-Sora Data): A Large-Scale Video Dataset with Long Durations and Structured Captions 10M video-text pairs	Github, Project
21) IDForge: A video dataset featuring scenes of people speaking. 300k Clips, Downloadable	ArXiv 24, Github
6.2 Video Augmentation Methods
6.2.1 Basic Transformations
Three-stream CNNs for action recognition	PRL 17 Paper
Dynamic Hand Gesture Recognition Using Multi-direction 3D Convolutional Neural Networks	EL 19 Paper
Intra-clip Aggregation for Video Person Re-identification	ICIP 20 Paper
VideoMix: Rethinking Data Augmentation for Video Classification	CVPR 20 Paper
mixup: Beyond Empirical Risk Minimization	ICLR 17 Paper
CutMix: Regularization Strategy to Train Strong Classifiers With Localizable Features	ICCV 19 Paper
Video Salient Object Detection via Fully Convolutional Networks	ICIP 18 Paper
Illumination-Based Data Augmentation for Robust Background Subtraction	SKIMA 19 Paper
Image editing-based data augmentation for illumination-insensitive background subtraction	EIM 20 Paper
6.2.2 Feature Space
Feature Re-Learning with Data Augmentation for Content-based Video Recommendation	ACM 18 Paper
GAC-GAN: A General Method for Appearance-Controllable Human Video Motion Transfer	Trans 21 Paper
6.2.3 GAN-based Augmentation
Deep Video-Based Performance Cloning	CVPR 18 Paper
Adversarial Action Data Augmentation for Similar Gesture Action Recognition	IJCNN 19 Paper
Self-Paced Video Data Augmentation by Generative Adversarial Networks with Insufficient Samples	MM 20 Paper
GAC-GAN: A General Method for Appearance-Controllable Human Video Motion Transfer	Trans 20 Paper
Dynamic Facial Expression Generation on Hilbert Hypersphere With Conditional Wasserstein Generative Adversarial Nets	TPAMI 20 Paper
CrowdGAN: Identity-Free Interactive Crowd Video Generation and Beyond	TPAMI 22 Paper
6.2.4 Encoder/Decoder Based
Rotationally-Temporally Consistent Novel View Synthesis of Human Performance Video	ECCV 20 Paper
Autoencoder-based Data Augmentation for Deepfake Detection	ACM 23 Paper
6.2.5 Simulation
A data augmentation methodology for training machine/deep learning gait recognition algorithms	CVPR 16 Paper
ElderSim: A Synthetic Data Generation Platform for Human Action Recognition in Eldercare Applications	IEEE 21 Paper
Mid-Air: A Multi-Modal Dataset for Extremely Low Altitude Drone Flights	CVPR 19 Paper
Generating Human Action Videos by Coupling 3D Game Engines and Probabilistic Graphical Models	IJCV 19 Paper
Using synthetic data for person tracking under adverse weather conditions	IVC 21 Paper
Unlimited Road-scene Synthetic Annotation (URSA) Dataset	ITSC 18 Paper
SAIL-VOS 3D: A Synthetic Dataset and Baselines for Object Detection and 3D Mesh Reconstruction From Video Data	CVPR 21 Paper
Universal Semantic Segmentation for Fisheye Urban Driving Images	SMC 20 Paper
07 Patchifying Methods
Paper	Link
1) ViT: An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale	CVPR 21 Paper, Github
2) MAE: Masked Autoencoders Are Scalable Vision Learners	CVPR 22 Paper, Github
3) ViViT: A Video Vision Transformer (-)	ICCV 21 Paper, GitHub
4) DiT: Scalable Diffusion Models with Transformers (-)	ICCV 23 Paper, GitHub, Project, ModelScope
5) U-ViT: All are Worth Words: A ViT Backbone for Diffusion Models (-)	CVPR 23 Paper, GitHub, ModelScope
6) FlexiViT: One Model for All Patch Sizes	Paper, Github
7) Patch n’ Pack: NaViT, a Vision Transformer for any Aspect Ratio and Resolution	ArXiv 23, Github
8) VQ-VAE: Neural Discrete Representation Learning	Paper, Github
9) VQ-GAN: Neural Discrete Representation Learning	CVPR 21 Paper, Github
10) LVT: Latent Video Transformer	Paper, Github
11) VideoGPT: Video Generation using VQ-VAE and Transformers (-)	ArXiv 21, GitHub
12) Predicting Video with VQVAE	ArXiv 21
13) CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformers	ICLR 23 Paper, Github
14) TATS: Long Video Generation with Time-Agnostic VQGAN and Time-Sensitive Transformer	ECCV 22 Paper, Github
15) MAGVIT: Masked Generative Video Transformer (-)	CVPR 23 Paper, GitHub, Project, Colab
16) MagViT2: Language Model Beats Diffusion -- Tokenizer is Key to Visual Generation	ICLR 24 Paper, Github
17) VideoPoet: A Large Language Model for Zero-Shot Video Generation (-)	ArXiv 23, Project, Blog
18) CLIP: Learning Transferable Visual Models From Natural Language Supervision	CVPR 21 Paper, Github
19) BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation	ArXiv 22, Github
20) BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models	ArXiv 23, Github
08 Long-context
Paper	Link
1) World Model on Million-Length Video And Language With RingAttention	ArXiv 24, GitHub
2) Ring Attention with Blockwise Transformers for Near-Infinite Context	ArXiv 23, GitHub
3) Extending LLMs' Context Window with 100 Samples	ArXiv 24, GitHub
4) Efficient Streaming Language Models with Attention Sinks	ICLR 24 Paper, GitHub
5) The What, Why, and How of Context Length Extension Techniques in Large Language Models – A Detailed Survey	Paper
6) MovieChat: From Dense Token to Sparse Memory for Long Video Understanding	CVPR 24 Paper, GitHub, Project
7) MemoryBank: Enhancing Large Language Models with Long-Term Memory	Paper, GitHub
09 Audio Related Resource
Paper	Link
1) Stable Audio: Fast Timing-Conditioned Latent Audio Diffusion	ArXiv 24, Github, Blog
2) MM-Diffusion: Learning Multi-Modal Diffusion Models for Joint Audio and Video Generation	CVPR 23 Paper, GitHub
3) Pengi: An Audio Language Model for Audio Tasks	NeurIPS 23 Paper, GitHub
4) Vast: A vision-audio-subtitle-text omni-modality foundation model and dataset	NeurlPS 23 Paper, GitHub
5) Macaw-LLM: Multi-Modal Language Modeling with Image, Audio, Video, and Text Integration	ArXiv 23, GitHub
6) NaturalSpeech: End-to-End Text to Speech Synthesis with Human-Level Quality	TPAMI 24 Paper, GitHub
7) NaturalSpeech 2: Latent Diffusion Models are Natural and Zero-Shot Speech and Singing Synthesizers	ICLR 24 Paper, GitHub
8) UniAudio: An Audio Foundation Model Toward Universal Audio Generation	ArXiv 23, GitHub
9) Diffsound: Discrete Diffusion Model for Text-to-sound Generation	TASLP 22 Paper
10) AudioGen: Textually Guided Audio Generation	ICLR 23 Paper, Project
11) AudioLDM: Text-to-audio generation with latent diffusion models	ICML 23 Paper, GitHub, Project, Huggingface
12) AudioLDM2: Learning Holistic Audio Generation with Self-supervised Pretraining	ArXiv 23, GitHub, Project, Huggingface
13) Make-An-Audio: Text-To-Audio Generation with Prompt-Enhanced Diffusion Models	ICML 23 Paper, GitHub
14) Make-An-Audio 2: Temporal-Enhanced Text-to-Audio Generation	ArXiv 23
15) TANGO: Text-to-audio generation using instruction-tuned LLM and latent diffusion model	ArXiv 23, GitHub, Project, Huggingface
16) AudioLM: a Language Modeling Approach to Audio Generation	ArXiv 22
17) AudioGPT: Understanding and Generating Speech, Music, Sound, and Talking Head	ArXiv 23, GitHub
18) MusicGen: Simple and Controllable Music Generation	NeurIPS 23 Paper, GitHub
19) LauraGPT: Listen, Attend, Understand, and Regenerate Audio with GPT	ArXiv 23
20) Seeing and Hearing: Open-domain Visual-Audio Generation with Diffusion Latent Aligners	CVPR 24 Paper
21) Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding	EMNLP 23 Paper
22) Audio-Visual LLM for Video Understanding	ArXiv 23
23) VideoPoet: A Large Language Model for Zero-Shot Video Generation (-)	ArXiv 23, Project, Blog
24) Movie Gen: A Cast of Media Foundation Models	Paper, Project
10 Consistency
Paper	Link
1) Consistency Models	Paper, GitHub
2) Improved Techniques for Training Consistency Models	ArXiv 23
3) Score-Based Diffusion: Score-Based Generative Modeling through Stochastic Differential Equations (-)	ICLR 21 Paper, GitHub, Blog
4) Improved Techniques for Training Score-Based Generative Models	NIPS 20 Paper, GitHub
4) Generative Modeling by Estimating Gradients of the Data Distribution	NIPS 19 Paper, GitHub
5) Maximum Likelihood Training of Score-Based Diffusion Models	NIPS 21 Paper, GitHub
6) Layered Neural Atlases for Consistent Video Editing	TOG 21 Paper, GitHub, Project
7) StableVideo: Text-driven Consistency-aware Diffusion Video Editing	ICCV 23 Paper, GitHub, Project
8) CoDeF: Content Deformation Fields for Temporally Consistent Video Processing	Paper, GitHub, Project
9) Sora Generates Videos with Stunning Geometrical Consistency	Paper, GitHub, Project
10) Efficient One-stage Video Object Detection by Exploiting Temporal Consistency	ECCV 22 Paper, GitHub
11) Bootstrap Motion Forecasting With Self-Consistent Constraints	ICCV 23 Paper
12) Enforcing Realism and Temporal Consistency for Large-Scale Video Inpainting	Paper
13) Enhancing Multi-Camera People Tracking with Anchor-Guided Clustering and Spatio-Temporal Consistency ID Re-Assignment	CVPRW 23 Paper, GitHub
14) Exploiting Spatial-Temporal Semantic Consistency for Video Scene Parsing	ArXiv 21
15) Semi-Supervised Crowd Counting With Spatial Temporal Consistency and Pseudo-Label Filter	TCSVT 23 Paper
16) Spatio-temporal Consistency and Hierarchical Matching for Multi-Target Multi-Camera Vehicle Tracking	CVPRW 19 Paper
17) VideoDirectorGPT: Consistent Multi-scene Video Generation via LLM-Guided Planning (-)	ArXiv 23
18) VideoDrafter: Content-Consistent Multi-Scene Video Generation with LLM (-)	ArXiv 24
19) MaskDiffusion: Boosting Text-to-Image Consistency with Conditional Mask	ArXiv 23
11 Prompt Engineering
Paper	Link
1) RealCompo: Dynamic Equilibrium between Realism and Compositionality Improves Text-to-Image Diffusion Models	ArXiv 24, GitHub, Project
2) Mastering Text-to-Image Diffusion: Recaptioning, Planning, and Generating with Multimodal LLMs	ArXiv 24, GitHub
3) LLM-grounded Diffusion: Enhancing Prompt Understanding of Text-to-Image Diffusion Models with Large Language Models	TMLR 23 Paper, GitHub
4) LLM BLUEPRINT: ENABLING TEXT-TO-IMAGE GEN-ERATION WITH COMPLEX AND DETAILED PROMPTS	ICLR 24 Paper, GitHub
5) Progressive Text-to-Image Diffusion with Soft Latent Direction	ArXiv 23
6) Self-correcting LLM-controlled Diffusion Models	CVPR 24 Paper, GitHub
7) LayoutLLM-T2I: Eliciting Layout Guidance from LLM for Text-to-Image Generation	MM 23 Paper
8) LayoutGPT: Compositional Visual Planning and Generation with Large Language Models	NeurIPS 23 Paper, GitHub
9) Gen4Gen: Generative Data Pipeline for Generative Multi-Concept Composition	ArXiv 24, GitHub
10) InstructEdit: Improving Automatic Masks for Diffusion-based Image Editing With User Instructions	ArXiv 23, GitHub
11) Controllable Text-to-Image Generation with GPT-4	ArXiv 23
12) LLM-grounded Video Diffusion Models	ICLR 24 Paper
13) VideoDirectorGPT: Consistent Multi-scene Video Generation via LLM-Guided Planning	ArXiv 23
14) FlowZero: Zero-Shot Text-to-Video Synthesis with LLM-Driven Dynamic Scene Syntax	ArXiv 23, Github, Project
15) VideoDrafter: Content-Consistent Multi-Scene Video Generation with LLM	ArXiv 24
16) Free-Bloom: Zero-Shot Text-to-Video Generator with LLM Director and LDM Animator	NeurIPS 23 Paper
17) Empowering Dynamics-aware Text-to-Video Diffusion with Large Language Models	ArXiv 23
18) MotionZero: Exploiting Motion Priors for Zero-shot Text-to-Video Generation	ArXiv 23
19) GPT4Motion: Scripting Physical Motions in Text-to-Video Generation via Blender-Oriented GPT Planning	ArXiv 23
20) Multimodal Procedural Planning via Dual Text-Image Prompting	ArXiv 23, Github
21) InstructCV: Instruction-Tuned Text-to-Image Diffusion Models as Vision Generalists	ICLR 24 Paper, Github
22) DreamSync: Aligning Text-to-Image Generation with Image Understanding Feedback	ArXiv 23
23) TaleCrafter: Interactive Story Visualization with Multiple Characters	SIGGRAPH Asia 23 Paper
24) Reason out Your Layout: Evoking the Layout Master from Large Language Models for Text-to-Image Synthesis	ArXiv 23, Github
25) COLE: A Hierarchical Generation Framework for Graphic Design	ArXiv 23
26) Knowledge-Aware Artifact Image Synthesis with LLM-Enhanced Prompting and Multi-Source Supervision	ArXiv 23
27) Vlogger: Make Your Dream A Vlog	CVPR 24 Paper, Github
28) GALA3D: Towards Text-to-3D Complex Scene Generation via Layout-guided Generative Gaussian Splatting	Paper
29) MuLan: Multimodal-LLM Agent for Progressive Multi-Object Diffusion	ArXiv 24
Recaption
Paper	Link
1) LAVIE: High-Quality Video Generation with Cascaded Latent Diffusion Models	ArXiv 23, GitHub
2) Reuse and Diffuse: Iterative Denoising for Text-to-Video Generation	ArXiv 23, GitHub
3) CoCa: Contrastive Captioners are Image-Text Foundation Models	ArXiv 22, Github
4) CogView3: Finer and Faster Text-to-Image Generation via Relay Diffusion	ArXiv 24
5) VideoChat: Chat-Centric Video Understanding	CVPR 24 Paper, Github
6) De-Diffusion Makes Text a Strong Cross-Modal Interface	ArXiv 23
7) HowToCaption: Prompting LLMs to Transform Video Annotations at Scale	ArXiv 23
8) SELMA: Learning and Merging Skill-Specific Text-to-Image Experts with Auto-Generated Data	ArXiv 24
9) LLMGA: Multimodal Large Language Model based Generation Assistant	ArXiv 23, Github
10) ELLA: Equip Diffusion Models with LLM for Enhanced Semantic Alignment	ArXiv 24, Github
11) MyVLM: Personalizing VLMs for User-Specific Queries	ArXiv 24
12) A Picture is Worth a Thousand Words: Principled Recaptioning Improves Image Generation	ArXiv 23, Github
13) Mastering Text-to-Image Diffusion: Recaptioning, Planning, and Generating with Multimodal LLMs(-)	ArXiv 24, Github
14) FlexCap: Generating Rich, Localized, and Flexible Captions in Images	ArXiv 24
15) Video ReCap: Recursive Captioning of Hour-Long Videos	ArXiv 24, Github
16) BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation	ICML 22, Github
17) PromptCap: Prompt-Guided Task-Aware Image Captioning	ICCV 23, Github
18) CIC: A framework for Culturally-aware Image Captioning	ArXiv 24
19) Improving Image Captioning Descriptiveness by Ranking and LLM-based Fusion	ArXiv 24
20) FuseCap: Leveraging Large Language Models for Enriched Fused Image Captions	WACV 24, Github
12 Security
Paper	Link
1) BeaverTails: Towards Improved Safety Alignment of LLM via a Human-Preference Dataset	NeurIPS 23 Paper, Github
2) LIMA: Less Is More for Alignment	NeurIPS 23 Paper
3) Jailbroken: How Does LLM Safety Training Fail?	NeurIPS 23 Paper
4) Safe Latent Diffusion: Mitigating Inappropriate Degeneration in Diffusion Models	CVPR 23 Paper
5) Stable Bias: Evaluating Societal Representations in Diffusion Models	NeurIPS 23 Paper
6) Ablating concepts in text-to-image diffusion models	ICCV 23 Paper
7) Diffusion art or digital forgery? investigating data replication in diffusion models	ICCV 23 Paper, Project
8) Eternal Sunshine of the Spotless Net: Selective Forgetting in Deep Networks	ICCV 20 Paper
9) Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks	ICML 20 Paper
10) A pilot study of query-free adversarial attack against stable diffusion	ICCV 23 Paper
11) Interpretable-Through-Prototypes Deepfake Detection for Diffusion Models	ICCV 23 Paper
12) Erasing Concepts from Diffusion Models	ICCV 23 Paper, Project
13) Ablating Concepts in Text-to-Image Diffusion Models	ICCV 23 Paper, Project
14) BEAVERTAILS: Towards Improved Safety Alignment of LLM via a Human-Preference Dataset	NeurIPS 23 Paper, Project
15) Stable Bias: Evaluating Societal Representations in Diffusion Models	NeurIPS 23 Paper
16) Threat Model-Agnostic Adversarial Defense using Diffusion Models	Paper
17) How well can Text-to-Image Generative Models understand Ethical Natural Language Interventions?	Paper, Github
18) Differentially Private Diffusion Models Generate Useful Synthetic Images	Paper
19) Unsafe Diffusion: On the Generation of Unsafe Images and Hateful Memes From Text-To-Image Models	SIGSAC 23 Paper, Github
20) Forget-Me-Not: Learning to Forget in Text-to-Image Diffusion Models	Paper, Github
21) Unified Concept Editing in Diffusion Models	WACV 24 Paper, Project
22) Diffusion Model Alignment Using Direct Preference Optimization	ArXiv 23
23) RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment	TMLR 23 Paper , Github
24) Self-Alignment of Large Language Models via Monopolylogue-based Social Scene Simulation	Paper, Github, Project
13 World Model
Paper	Link
1) NExT-GPT: Any-to-Any Multimodal LLM	ArXiv 23, GitHub
14 Video Compression
Paper	Link
1) H.261: Video codec for audiovisual services at p x 64 kbit/s	Paper
2) H.262: Information technology - Generic coding of moving pictures and associated audio information: Video	Paper
3) H.263: Video coding for low bit rate communication	Paper
4) H.264: Overview of the H.264/AVC video coding standard	Paper
5) H.265: Overview of the High Efficiency Video Coding (HEVC) Standard	Paper
6) H.266: Overview of the Versatile Video Coding (VVC) Standard and its Applications	Paper
7) DVC: An End-to-end Deep Video Compression Framework	CVPR 19 Paper, GitHub
8) OpenDVC: An Open Source Implementation of the DVC Video Compression Method	Paper, GitHub
9) HLVC: Learning for Video Compression with Hierarchical Quality and Recurrent Enhancement	CVPR 20 Paper, Github
10) RLVC: Learning for Video Compression with Recurrent Auto-Encoder and Recurrent Probability Model	J-STSP 21 Paper, Github
11) PLVC: Perceptual Learned Video Compression with Recurrent Conditional GAN	IJCAI 22 Paper, Github
12) ALVC: Advancing Learned Video Compression with In-loop Frame Prediction	T-CSVT 22 Paper, Github
13) DCVC: Deep Contextual Video Compression	NeurIPS 21 Paper, Github
14) DCVC-TCM: Temporal Context Mining for Learned Video Compression	TM 22 Paper, Github
15) DCVC-HEM: Hybrid Spatial-Temporal Entropy Modelling for Neural Video Compression	MM 22 Paper, Github
16) DCVC-DC: Neural Video Compression with Diverse Contexts	CVPR 23 Paper, Github
17) DCVC-FM: Neural Video Compression with Feature Modulation	CVPR 24 Paper, Github
18) SSF: Scale-Space Flow for End-to-End Optimized Video Compression	CVPR 20 Paper, Github
15 Mamba
15.1 Theoretical Foundations and Model Architecture
Paper	Link
1) Mamba: Linear-Time Sequence Modeling with Selective State Spaces	ArXiv 23, Github
2) Efficiently Modeling Long Sequences with Structured State Spaces	ICLR 22 Paper, Github
3) Modeling Sequences with Structured State Spaces	Paper
4) Long Range Language Modeling via Gated State Spaces	ArXiv 22, GitHub
15.2 Image Generation and Visual Applications
Paper	Link
1) Diffusion Models Without Attention	ArXiv 23
2) Pan-Mamba: Effective Pan-Sharpening with State Space Model	ArXiv 24, Github
3) Pretraining Without Attention	ArXiv 22, Github
4) Block-State Transformers	NIPS 23 Paper
5) Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model	ArXiv 24, Github
6) VMamba: Visual State Space Model	ArXiv 24, Github
7) ZigMa: Zigzag Mamba Diffusion Model	ArXiv 24, Github
8) MambaVision: A Hybrid Mamba-Transformer Vision Backbone	ArXiv 24, GitHub
15.3 Video Processing and Understanding
Paper	Link
1) Long Movie Clip Classification with State-Space Video Models	ECCV 22 Paper, Github
2) Selective Structured State-Spaces for Long-Form Video Understanding	CVPR 23 Paper
3) Efficient Movie Scene Detection Using State-Space Transformers	CVPR 23 Paper, Github
4) VideoMamba: State Space Model for Efficient Video Understanding	Paper, Github
15.4 Medical Image Processing
Paper	Link
1) Swin-UMamba: Mamba-based UNet with ImageNet-based pretraining	ArXiv 24, Github
2) MambaIR: A Simple Baseline for Image Restoration with State-Space Model	ArXiv 24, Github
3) VM-UNet: Vision Mamba UNet for Medical Image Segmentation	ArXiv 24, Github
16 Existing high-quality resources
Resources	Link
1) Datawhale - AI视频生成学习	Feishu doc
2) A Survey on Generative Diffusion Model	TKDE 24 Paper, GitHub
3) Awesome-Video-Diffusion-Models: A Survey on Video Diffusion Models	ArXiv 23, GitHub
4) Awesome-Text-To-Video：A Survey on Text-to-Video Generation/Synthesis	GitHub
5) video-generation-survey: A reading list of video generation	GitHub
6) Awesome-Video-Diffusion	GitHub
7) Video Generation Task in Papers With Code	Task
8) Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models	ArXiv 24, GitHub
9) Open-Sora-Plan (PKU-YuanGroup)	GitHub
10) State of the Art on Diffusion Models for Visual Computing	Paper
11) Diffusion Models: A Comprehensive Survey of Methods and Applications	CSUR 24 Paper, GitHub
12) Generate Impressive Videos with Text Instructions: A Review of OpenAI Sora, Stable Diffusion, Lumiere and Comparable	Paper
13) On the Design Fundamentals of Diffusion Models: A Survey	Paper
14) Efficient Diffusion Models for Vision: A Survey	Paper
15) Text-to-Image Diffusion Models in Generative AI: A Survey	Paper
16) Awesome-Diffusion-Transformers	GitHub, Project
17) Open-Sora (HPC-AI Tech)	GitHub, Blog
18) LAVIS - A Library for Language-Vision Intelligence	ACL 23 Paper, GitHub, Project
19) OpenDiT: An Easy, Fast and Memory-Efficient System for DiT Training and Inference	GitHub
20) Awesome-Long-Context	GitHub1, GitHub2
21) Lite-Sora	GitHub
22) Mira: A Mini-step Towards Sora-like Long Video Generation	GitHub, Project
17 Efficient Training
17.1 Parallelism based Approach
17.1.1 Data Parallelism (DP)
1) A bridging model for parallel computation	Paper
2) PyTorch Distributed: Experiences on Accelerating Data Parallel Training	VLDB 20 Paper
17.1.2 Model Parallelism (MP)
1) Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism	ArXiv 19 Paper
2) TeraPipe: Token-Level Pipeline Parallelism for Training Large-Scale Language Models	PMLR 21 Paper
17.1.3 Pipeline Parallelism (PP)
1) GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism	NeurIPS 19 Paper
2) PipeDream: generalized pipeline parallelism for DNN training	SOSP 19 Paper
17.1.4 Generalized Parallelism (GP)
1) Mesh-TensorFlow: Deep Learning for Supercomputers	ArXiv 18 Paper
2) Beyond Data and Model Parallelism for Deep Neural Networks	MLSys 19 Paper
17.1.5 ZeRO Parallelism (ZP)
1) ZeRO: Memory Optimizations Toward Training Trillion Parameter Models	ArXiv 20
2) DeepSpeed: System Optimizations Enable Training Deep Learning Models with Over 100 Billion Parameters	ACM 20 Paper
3) ZeRO-Offload: Democratizing Billion-Scale Model Training	ArXiv 21
4) PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel	ArXiv 23
17.2 Non-parallelism based Approach
17.2.1 Reducing Activation Memory
1) Gist: Efficient Data Encoding for Deep Neural Network Training	IEEE 18 Paper
2) Checkmate: Breaking the Memory Wall with Optimal Tensor Rematerialization	MLSys 20 Paper
3) Training Deep Nets with Sublinear Memory Cost	ArXiv 16 Paper
4) Superneurons: dynamic GPU memory management for training deep neural networks	ACM 18 Paper
17.2.2 CPU-Offloading
1) Training Large Neural Networks with Constant Memory using a New Execution Algorithm	ArXiv 20 Paper
2) vDNN: Virtualized deep neural networks for scalable, memory-efficient neural network design	IEEE 16 Paper
17.2.3 Memory Efficient Optimizer
1) Adafactor: Adaptive Learning Rates with Sublinear Memory Cost	PMLR 18 Paper
2) Memory-Efficient Adaptive Optimization for Large-Scale Learning	Paper
17.3 Novel Structure
1) ELLA: Equip Diffusion Models with LLM for Enhanced Semantic Alignment	ArXiv 24 Github
18 Efficient Inference
18.1 Reduce Sampling Steps
18.1.1 Continuous Steps
1) Generative Modeling by Estimating Gradients of the Data Distribution	NeurIPS 19 Paper
2) WaveGrad: Estimating Gradients for Waveform Generation	ArXiv 20
3) Noise Level Limited Sub-Modeling for Diffusion Probabilistic Vocoders	ICASSP 21 Paper
4) Noise Estimation for Generative Diffusion Models	ArXiv 21
18.1.2 Fast Sampling
1) Denoising Diffusion Implicit Models	ICLR 21 Paper
2) DiffWave: A Versatile Diffusion Model for Audio Synthesis	ICLR 21 Paper
3) On Fast Sampling of Diffusion Probabilistic Models	ArXiv 21
4) DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps	NeurIPS 22 Paper
5) DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Models	ArXiv 22
6) Fast Sampling of Diffusion Models with Exponential Integrator	ICLR 22 Paper
18.1.3 Step distillation
1) On Distillation of Guided Diffusion Models	CVPR 23 Paper
2) Progressive Distillation for Fast Sampling of Diffusion Models	ICLR 22 Paper
3) SnapFusion: Text-to-Image Diffusion Model on Mobile Devices within Two Seconds	NeurIPS 23 Paper
4) Tackling the Generative Learning Trilemma with Denoising Diffusion GANs	ICLR 22 Paper
18.2 Optimizing Inference
18.2.1 Low-bit Quantization
1) Q-Diffusion: Quantizing Diffusion Models	CVPR 23 Paper
2) Q-DM: An Efficient Low-bit Quantized Diffusion Model	NeurIPS 23 Paper
3) Temporal Dynamic Quantization for Diffusion Models	NeurIPS 23 Paper
18.2.2 Parallel/Sparse inference
1) DistriFusion: Distributed Parallel Inference for High-Resolution Diffusion Models	CVPR 24 Paper
2) Efficient Spatially Sparse Inference for Conditional GANs and Diffusion Models	NeurIPS 22 Paper
3) PipeFusion: Displaced Patch Pipeline Parallelism for Inference of Diffusion Transformer Models	ArXiv 24

引用

如果本项目对您的工作有所帮助，请使用以下格式引用：

@misc{minisora,
    title={MiniSora},
    author={MiniSora社区},
    url={https://github.com/mini-sora/minisora},
    year={2024}
}

@misc{minisora,
    title={从DDPM到Sora的基于扩散模型的视频生成模型综述},
    author={MiniSora社区综述论文组},
    url={https://github.com/mini-sora/minisora},
    year={2024}
}

Minisora社区微信群

星标历史

如何为Mini Sora社区贡献力量

我们非常感谢您对Mini Sora开源社区的贡献，帮助我们让它比现在更加出色！

更多详情，请参阅贡献指南。

社区贡献者

MiniSora 快速上手指南

MiniSora 是一个由社区驱动的开源项目，旨在探索 Sora 视频生成模型的实现路径。本项目目前主要聚焦于复现相关论文（如 DiT）、技术调研以及组织圆桌讨论，而非直接提供一个“一键生成视频”的成品软件。

以下是参与 MiniSora 社区核心复现任务（基于 XTuner 复现 DiT）及获取学习资源的快速指南。

环境准备

在开始之前，请确保您的开发环境满足以下要求，特别是如果您计划参与模型复现训练：

• 操作系统: Linux (推荐 Ubuntu 20.04+)
• Python: 3.8 或更高版本
• GPU 要求:
  • 推理/轻量实验: 建议至少 16GB 显存 (如 RTX 3090/4090)。
  • 训练复现 (DiT): 官方推荐配置为 2x A100 (80G) 或同等算力。社区目标是在 8x A100/A6000 或消费级显卡集群上实现训练。
• 前置依赖:
  • CUDA 11.7+
  • PyTorch 2.0+
  • Git

安装步骤

MiniSora 的核心复现工作主要依托于 XTuner 框架进行。请按照以下步骤搭建基础环境：

1. 克隆仓库

   git clone https://github.com/mini-sora/minisora.git
   cd minisora
   

2. 安装核心依赖 (XTuner) 由于 MiniSora-DiT 项目深度集成 XTuner，建议优先安装 XTuner 及其依赖。国内开发者推荐使用镜像源加速安装。

   # 创建虚拟环境 (推荐)
   conda create -n minisora python=3.10 -y
   conda activate minisora
   
   # 安装 PyTorch (根据实际 CUDA 版本调整，此处以 CUDA 11.8 为例)
   pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
   
   # 安装 XTuner (使用国内镜像加速)
   pip install -U xtuner[all] -i https://pypi.tuna.tsinghua.edu.cn/simple
   

3. 安装 MiniSora 特定依赖 进入具体的复现子模块（如 MiniSora-DiT）安装额外需求：

   cd codes/minisora-DiT  # 路径可能随项目更新变动，请以实际目录结构为准
   pip install -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple
   

基本使用

MiniSora 目前主要提供代码复现参考、技术文档和论文解读。最直接的使用方式是运行社区复现的 DiT 模型或阅读技术综述。

1. 运行 DiT 复现示例 (基于 XTuner)

如果您已配置好环境，可以使用 XTuner 启动 DiT 的训练或推理流程。以下是一个典型的训练配置启动命令示例：

# 使用 XTuner 启动 DiT 训练 (需替换为具体的配置文件路径)
xtuner train ./configs/dit_config.py --work-dir ./work_dirs/dit_output

注意：具体的配置文件 (dit_config.py) 和数据集路径需要在 minisora-DiT 子目录中根据官方文档进行详细配置。

2. 获取技术资源与论文解读

对于大多数开发者，快速上手的最佳方式是查阅社区整理的技术综述和论文笔记：

• 查看 Sora 技术综述: 访问 docs/survey_README.md 获取从 DDPM 到 Sora 的视频生成模型全面回顾。

• 阅读论文解读笔记: 项目 notes/ 目录下包含了社区对关键论文的详细中文解读，包括：

  • Sora: Video generation models as world simulators
  • DiT: Scalable Diffusion Models with Transformers
  • Stable Diffusion 3 (MM-DiT): 详见 notes/SD3_zh-CN.md
  • Latte: Latent Diffusion Transformer for Video Generation

3. 加入社区交流

MiniSora 强调社区协作，建议加入微信群参与圆桌讨论和获取最新进展：

• 微信群二维码: 点击此处查看
• GitHub Discussions: 关注 Reproduction Group 获取最新的复现目标和招募信息。