A collection of resources and papers on Diffusion Models
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Updated
Jul 28, 2023 - HTML
A collection of resources and papers on Diffusion Models
OpenMMLab Multimodal Advanced, Generative, and Intelligent Creation Toolbox. Unlock the magic
OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference
Automatic Speech Recognition (ASR), Speaker Verification, Speech Synthesis, Text-to-Speech (TTS), Language Modelling, Singing Voice Synthesis (SVS), Voice Conversion (VC)
Diffusion model papers, survey, and taxonomy
MMGeneration is a powerful toolkit for generative models, based on PyTorch and MMCV.
Custom Diffusion: Multi-Concept Customization of Text-to-Image Diffusion (CVPR 2023)
Official PyTorch Code and Models of "RePaint: Inpainting using Denoising Diffusion Probabilistic Models", CVPR 2022
[ICCV 2023] Make-It-3D: High-Fidelity 3D Creation from A Single Image with Diffusion Prior
PyTorch implementation for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)
Official code for "DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps" (Neurips 2022 Oral)
Unofficial implementation of "Prompt-to-Prompt Image Editing with Cross Attention Control" with Stable Diffusion
Official code for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)
Official PyTorch Implementation of Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priors
Text2Room generates textured 3D meshes from a given text prompt using 2D text-to-image models (ICCV2023).
A curated list of recent diffusion models for video generation, editing, restoration, understanding, etc.
[ICLR 2023 Oral] Zero-Shot Image Restoration Using Denoising Diffusion Null-Space Model
Codes and Model of the paper "Text-to-Audio Generation using Instruction Tuned LLM and Latent Diffusion Model"
Chinese and English Multimodal Large Model Series (Chat and Paint) | 基于CPM基础模型的中英双语多模态大模型系列
Official Implementation of Paella https://arxiv.org/abs/2211.07292v1
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