jpthu17/GraphMotion
[NeurIPS 2023] Act As You Wish: Fine-Grained Control of Motion Diffusion Model with Hierarchical Semantic Graphs
This project helps animators, game developers, or filmmakers generate highly specific character movements from text descriptions. You provide a phrase like "a person slowly walked forward," and the system outputs a detailed 3D animation of that action. It's designed for anyone needing precise control over animated human motion, from overall movement to subtle specifics.
128 stars. No commits in the last 6 months.
Use this if you need to create realistic and finely-tuned human animations based on textual input, with the ability to adjust individual aspects like speed or direction.
Not ideal if you are looking for a simple drag-and-drop animation tool or if you do not have a technical background in machine learning model training and configuration.
Stars
128
Forks
7
Language
Python
License
Apache-2.0
Category
Last pushed
Nov 15, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/diffusion/jpthu17/GraphMotion"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
hao-ai-lab/FastVideo
A unified inference and post-training framework for accelerated video generation.
ModelTC/LightX2V
Light Image Video Generation Inference Framework
thu-ml/TurboDiffusion
TurboDiffusion: 100–200× Acceleration for Video Diffusion Models
PKU-YuanGroup/Helios
Helios: Real Real-Time Long Video Generation Model
PKU-YuanGroup/MagicTime
[TPAMI 2025🔥] MagicTime: Time-lapse Video Generation Models as Metamorphic Simulators