[CVPR 2024] Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data. Foundation Model for Monocular Depth Estimation
#计算机科学#MMagic (Multimodal Advanced, Generative, and Intelligent Creation) 是一个供专业人工智能研究人员和机器学习工程师去处理、编辑和生成图像与视频的开源 AIGC 工具箱
(ෆ`꒳´ෆ) A Survey on Text-to-Image Generation/Synthesis.
Fast Example-based Image Synthesis and Style Transfer
翻译 - 基于示例的快速图像合成和样式转换
Photographic Image Synthesis with Cascaded Refinement Networks
#人脸识别#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 ...
Official PyTorch implementation for the paper High-Resolution Virtual Try-On with Misalignment and Occlusion-Handled Conditions (ECCV 2022).
#计算机科学#Code for APDrawingGAN: Generating Artistic Portrait Drawings from Face Photos with Hierarchical GANs (CVPR 2019 Oral)
翻译 - APDrawingGAN的代码:使用分层GAN从人脸照片生成艺术肖像画(CVPR 2019 Oral)
An official implementation of MobileStyleGAN in PyTorch
翻译 - PyTorch中MobileStyleGAN的正式实现
MONAI Generative Models makes it easy to train, evaluate, and deploy generative models and related applications
#计算机科学#All About the GANs(Generative Adversarial Networks) - Summarized lists for GAN
[ICCV 2021] Focal Frequency Loss for Image Reconstruction and Synthesis
#计算机科学#[MSG-GAN] Any body can GAN! Highly stable and robust architecture. Requires little to no hyperparameter tuning. Pytorch Implementation
翻译 - [MSG-GAN]任何人都可以GAN!高度稳定和强大的体系结构。几乎不需要或不需要超参数调整。
[ICCV 2023] A latent space for stochastic diffusion models
#计算机科学#[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;
#人脸识别#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...
Papers and resources on Controllable Generation using Diffusion Models, including ControlNet, DreamBooth, IP-Adapter.
#计算机科学#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”.