OpenMMLab Multimodal Advanced, Generative, and Intelligent Creation Toolbox. Unlock the magic 🪄: Generative-AI (AIGC), easy-to-use APIs, awsome model zoo, diffusion models, for text-to-image generation, image/video restoration/enhancement, etc.

[CVPR 2024] Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data. Foundation Model for Monocular Depth Estimation

(ෆ`꒳´ෆ) A Survey on Text-to-Image Generation/Synthesis.

Fast Example-based Image Synthesis and Style Transfer

Photographic Image Synthesis with Cascaded Refinement Networks

ICCV 2023 Papers: Discover cutting-edge research from ICCV 2023, the leading computer vision conference. Stay updated on the latest in computer vision and deep learning, with code included. ⭐ support visual intelligence development!

Official PyTorch implementation for the paper High-Resolution Virtual Try-On with Misalignment and Occlusion-Handled Conditions (ECCV 2022).

Code for APDrawingGAN: Generating Artistic Portrait Drawings from Face Photos with Hierarchical GANs (CVPR 2019 Oral)

An official implementation of MobileStyleGAN in PyTorch

All About the GANs(Generative Adversarial Networks) - Summarized lists for GAN

[MSG-GAN] Any body can GAN! Highly stable and robust architecture. Requires little to no hyperparameter tuning. Pytorch Implementation

[ICCV 2021] Focal Frequency Loss for Image Reconstruction and Synthesis

MONAI Generative Models makes it easy to train, evaluate, and deploy generative models and related applications

[ICCV 2023] A latent space for stochastic diffusion models

[CVPR 2022] StyleSwin: Transformer-based GAN for High-resolution Image Generation

PITI: Pretraining is All You Need for Image-to-Image Translation

The Implementation of paper "Controllable Person Image Synthesis with Attribute-Decomposed GAN" CVPR 2020 (Oral); Pose and Appearance Attributes Transfer;

MSGAN: Mode Seeking Generative Adversarial Networks for Diverse Image Synthesis (CVPR2019)

ArtGAN + WikiArt: This work presents a series of new approaches to improve GAN for conditional image synthesis and we name the proposed model as “ArtGAN”.