# DreaMoving: A Human Video Generation Framework based on Diffusion Models

arXiv: https://arxiv.org/abs/2312.05107 · HTML: https://mlsanity.com/paper/2312.05107/

## Key facts

- Cited by 25 papers in the map (data through 14 Oct 2026).
- Placed in Video generation, one of 14 directions in Diffusion models.
- Builds on 10 of its 13 references that are in the map.
- First posted on arXiv 8 Dec 2023.

## Placed in

- Diffusion models / [Video generation](https://mlsanity.com/diffusion/video-generation/)

## Builds on (most cited first, 10 of 10)

- [High-Resolution Image Synthesis with Latent Diffusion Models](https://mlsanity.com/paper/2112.10752/) (2021)
- [LoRA: Low-Rank Adaptation of Large Language Models](https://mlsanity.com/paper/2106.09685/) (2021)
- [Adding Conditional Control to Text-to-Image Diffusion Models](https://mlsanity.com/paper/2302.05543/) (2023)
- [DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation](https://mlsanity.com/paper/2208.12242/) (2022)
- [IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models](https://mlsanity.com/paper/2308.06721/) (2023)
- [AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning](https://mlsanity.com/paper/2307.04725/) (2023)
- [Frozen in Time: A Joint Video and Image Encoder for End-to-End Retrieval](https://mlsanity.com/paper/2104.00650/) (2021)
- [ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depth](https://mlsanity.com/paper/2302.12288/) (2023)
- [MiniGPT-v2: large language model as a unified interface for vision-language multi-task learning](https://mlsanity.com/paper/2310.09478/) (2023)
- [Effective Whole-body Pose Estimation with Two-stages Distillation](https://mlsanity.com/paper/2307.15880/) (2023)

## Built on by (most cited first, 25 of 25)

- [Champ: Controllable and Consistent Human Image Animation with 3D Parametric Guidance](https://mlsanity.com/paper/2403.14781/) (2024)
- [MimicMotion: High-Quality Human Motion Video Generation with Confidence-aware Pose Guidance](https://mlsanity.com/paper/2406.19680/) (2024)
- [Direct-a-Video: Customized Video Generation with User-Directed Camera Movement and Object Motion](https://mlsanity.com/paper/2402.03162/) (2024)
- [InitNO: Boosting Text-to-Image Diffusion Models via Initial Noise Optimization](https://mlsanity.com/paper/2404.04650/) (2024)
- [Boximator: Generating Rich and Controllable Motions for Video Synthesis](https://mlsanity.com/paper/2402.01566/) (2024)
- [DeMamba: AI-Generated Video Detection on Million-Scale GenVideo Benchmark](https://mlsanity.com/paper/2405.19707/) (2024)
- [3DTrajMaster: Mastering 3D Trajectory for Multi-Entity Motion in Video Generation](https://mlsanity.com/paper/2412.07759/) (2024)
- [A Survey on Personalized Content Synthesis with Diffusion Models](https://mlsanity.com/paper/2405.05538/) (2024)
- [A Comprehensive Survey on Human Video Generation: Challenges, Methods, and Insights](https://mlsanity.com/paper/2407.08428/) (2024)
- [I4VGen: Image as Free Stepping Stone for Text-to-Video Generation](https://mlsanity.com/paper/2406.02230/) (2024)
- [DanceTogether! Identity-Preserving Multi-Person Interactive Video Generation](https://mlsanity.com/paper/2505.18078/) (2025)
- [MovieCharacter: A Tuning-Free Framework for Controllable Character Video Synthesis](https://mlsanity.com/paper/2410.20974/) (2024)
- [High Quality Human Image Animation using Regional Supervision and Motion Blur Condition](https://mlsanity.com/paper/2409.19580/) (2024)
- [GenHSI: Controllable Generation of Human-Scene Interaction Videos](https://mlsanity.com/paper/2506.19840/) (2025)
- [MagicFight: Personalized Martial Arts Combat Video Generation](https://mlsanity.com/paper/2601.02107/) (2026)
- [Enhancing Motion in Text-to-Video Generation with Decomposed Encoding and Conditioning](https://mlsanity.com/paper/2410.24219/) (2024)
- [CFSynthesis: Controllable and Free-view 3D Human Video Synthesis](https://mlsanity.com/paper/2412.11067/) (2024)
- [SignLLM: Sign Language Production Large Language Models](https://mlsanity.com/paper/2405.10718/) (2024)
- [Adaptive Multi-Modal Control of Digital Human Hand Synthesis Using a Region-Aware Cycle Loss](https://mlsanity.com/paper/2409.09149/) (2024)
- [AnyLogo: Symbiotic Subject-Driven Diffusion System with Gemini Status](https://mlsanity.com/paper/2409.17740/) (2024)
- [Toward Rich Video Human-Motion2D Generation](https://mlsanity.com/paper/2506.14428/) (2025)
- [CMTA: Leveraging Cross-Modal Temporal Artifacts for Generalizable AI-Generated Video Detection](https://mlsanity.com/paper/2605.00630/) (2026)
- [ATSS: Detecting AI-Generated Videos via Anomalous Temporal Self-Similarity](https://mlsanity.com/paper/2604.04029/) (2026)
- [Controllable Complex Human Motion Video Generation via Text-to-Skeleton Cascades](https://mlsanity.com/paper/2603.08028/) (2026)
- [MTOR: Generalizable AI-Generated Video Detection with Multimodal Semantics and Temporal Over-Regularity](https://mlsanity.com/paper/2610.06378/) (2026)

## Abstract (arXiv)

In this paper, we present DreaMoving, a diffusion-based controllable video generation framework to produce high-quality customized human videos. Specifically, given target identity and posture sequences, DreaMoving can generate a video of the target identity moving or dancing anywhere driven by the posture sequences. To this end, we propose a Video ControlNet for motion-controlling and a Content Guider for identity preserving. The proposed model is easy to use and can be adapted to most stylized diffusion models to generate diverse results. The project page is available at https://dreamoving.github.io/dreamoving