image-synthesis

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

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.

(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

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

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

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

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

[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;

Papers and resources on Controllable Generation using Diffusion Models, including ControlNet, DreamBooth, IP-Adapter.

CVPR 2023-2024 Papers: Dive into advanced research presented at the leading computer vision conference. Keep up to date with the latest developments in computer vision and deep learning. Code included. ⭐ support visual intelligence development!

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”.