Blur Diffusion
sangyun884
Official PyTorch implementation of the paper Progressive Deblurring of Diffusion Models for Coarse-to-Fine Image Synthesis.
OPENAGENTSKILL / DIRECTORY
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sangyun884
Official PyTorch implementation of the paper Progressive Deblurring of Diffusion Models for Coarse-to-Fine Image Synthesis.
bryandlee
PyTorch Implementation of In-Domain GAN Inversion for StyleGAN2
caiyuanhao1998
"Learning to Generate Realistic Noisy Images via Pixel-level Noise-aware Adversarial Training" (NeurIPS 2021)
hp-l33
Official PyTorch Implementation of "Scalable Autoregressive Image Generation with Mamba"
yao-jason
Machine Learning and having it Deep and Structured (MLDS) in 2018 spring
bot66
Implement a MNIST(also minimal) version of denoising diffusion probabilistic model from scratch.The model only has 4.55MB.
chenhaoxing
This repository is the code of our paper "DiffUTE: Universal Text Editing Diffusion Model" (NeurIPS'2023).
eliahuhorwitz
Official Implementation for the "Conffusion: Confidence Intervals for Diffusion Models" paper.
Ha0Tang
[CVPR 2020] Local Class-Specific and Global Image-Level Generative Adversarial Networks for Semantic-Guided Scene Generation
sagiebenaim
Pytorch implementation of "One-Shot Unsupervised Cross Domain Translation" NIPS 2018
Alokia
This is a pytorch implementation of Denoising Diffusion Implicit Models
davide97l
AI agent to automatically generate and post short videos
showlab
[NeurIPS 2023] Customize spatial layouts for conditional image synthesis models, e.g., ControlNet, using GPT
mlpc-ucsd
(CVPR 2024) 🧩 TokenCompose: Text-to-Image Diffusion with Token-level Supervision
JIA-Lab-research
Wide-Context Semantic Image Extrapolation, CVPR2019
Owner-curated external sources. Not filtered by the scores or compatibility controls above; excluded from GitHub rankings and automatic installation.
RedSkill · 流白Livo · 1.0.0
Describe a rain curtain, growing flowering branches or a flock of swallows. This RedSkill package adapts three p5.js templates into sketch.js code with custom colors, density and speed.
Noncommercial use only · Local runtime recording · Use on the source platform