YangLing0818/consistency_flow_matching
Official Implementation for "Consistency Flow Matching: Defining Straight Flows with Velocity Consistency"
This project provides an efficient method for generating high-quality images from random noise. By defining a direct path between noise and desired images, it allows for faster training and better visual outputs compared to other techniques. It's designed for researchers and practitioners working on advanced image synthesis.
260 stars. No commits in the last 6 months.
Use this if you need to generate realistic images from scratch with a focus on both speed of training and the quality of the generated output.
Not ideal if your primary goal is simple image manipulation or if you don't require high-fidelity generative modeling.
Stars
260
Forks
10
Language
Python
License
MIT
Category
Last pushed
Jan 17, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/diffusion/YangLing0818/consistency_flow_matching"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
milad1378yz/MOTFM
Flow Matching for Medical Image Synthesis: Bridging the Gap Between Speed and Quality
OpenImagingLab/FlashVSR
[CVPR 2026] Towards Real-Time Diffusion-Based Streaming Video Super-Resolution — An efficient...
X-GenGroup/Flow-Factory
A unified framework for easy reinforcement learning in Flow-Matching models
fallenshock/FlowEdit
Official implementation of the paper: "FlowEdit: Inversion-Free Text-Based Editing Using...
haidog-yaqub/MeanFlow
Pytorch Implementation (unofficial) of the paper "Mean Flows for One-step Generative Modeling"...