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Starred repositories
The collection of pre-trained, state-of-the-art AI models for ailia SDK
FlipSketch: Flipping Static Drawings to Text-Guided Sketch Animations
Open standard for machine learning interoperability
A collection of GPT system prompts and various prompt injection/leaking knowledge.
a 2D rigid body physics engine for the web ▲● ■
开源的SSL证书管理工具，可以帮助你自动申请、部署SSL证书，并在证书即将过期时自动续期。An open-source SSL certificate management tool that helps you automatically apply for and deploy SSL certificates, as well as automatically renew them w…
(CVPR 2023) E4S: Fine-grained Face Swapping via Regional GAN Inversion
StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.
PyTorch implementation of slicing adversarial network (SAN)
Awesome Deep Graph Clustering is a collection of SOTA, novel deep graph clustering methods (papers, codes, and datasets).
Barbershop: GAN-based Image Compositing using Segmentation Masks (SIGGRAPH Asia 2021)
Synthetic Faces High Quality (SFHQ) Dataset. 425,000 curated 1024x1024 synthetic face images
[ICCV 2023] HairCLIPv2: Unifying Hair Editing via Proxy Feature Blending
(CVPR 2022) HairMapper: Removing Hair from Portraits Using GANs.
Various applications based on Stylegan2 Style mixing that can be inference on cpu.
Re-implementation of e4e that use mobilenet-v3 and stylegan2-1024p
👤🔍 | BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation | In PyTorch >> ONNX
Official PyTorch implementation of SegFormer
StyleGAN-Human: A Data-Centric Odyssey of Human Generation
A collection of pre-trained StyleGAN 2 models to download
EasyPortrait - Face Parsing and Portrait Segmentation Dataset
Industry leading face manipulation platform
A flutter plugin that implements Google's standalone ML Kit
Cool colorful backgrounds, generated by JS
A generative speech model for daily dialogue.
[ICML'23] StyleGAN-T: Unlocking the Power of GANs for Fast Large-Scale Text-to-Image Synthesis
A game theoretic approach to explain the output of any machine learning model.