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stylealign

[ICCV 2019]Aggregation via Separation: Boosting Facial Landmark Detector with Semi-Supervised Style Transition

stylebank

Implementation of the paper: StyleBank: An Explicit Representation for Neural Image Style Transfer

styleflow

StyleFlow: Attribute-conditioned Exploration of StyleGAN-generated Images using Conditional Continuous Normalizing Flows

stylegan.pytorch

A PyTorch implementation for StyleGAN with full features.

stylegan2

StyleGAN2 - Official TensorFlow Implementation

stylegan2-encoder-pytorch

PyTorch Implementation of In-Domain GAN Inversion for StyleGAN2

stylegan2-pytorch

Simplest working implementation of Stylegan2, state of the art generative adversarial network, in Pytorch. Enabling everyone to experience disentanglement

stylegan3

Official PyTorch implementation of StyleGAN3

stylegan_latenteditor

stylemapgan

stylerenderer

Implementation for Paper "Inverting Generative Adversarial Renderer for Face Reconstruction"

stylescene

styleswin

StyleSwin: Transformer-based GAN for High-resolution Image Generation

styletransfer

Real-time neural style transfer via meta networks

styletransfertrilogy

风格迁移三部曲

super-convergence

Files to create the figures in the paper "Super-Convergence: Very Fast Training of Residual Networks Using Large Learning Rates"

super-fan

The PyTorch implement of the paper "Super-FAN: Integrated facial landmark localization and super-resolution of real-world low resolution faces in arbitrary poses with GANs"

super_resolution_with_cnns_and_gans

Image Super-Resolution Using SRCNN, DRRN, SRGAN, CGAN in Pytorch

supergluepretrainednetwork

SuperGlue: Learning Feature Matching with Graph Neural Networks (CVPR 2020, Oral)

superresolution

superstring

A fast and memory-optimized string library for C++

supervised_dispnet

Towards Good Practice for CNN Based Monocular Depth Estimation

supervision-by-registration

Supervision-by-Registration: An Unsupervised Approach to Improve the Precision of Facial Landmark Detectors

surface_normals

Code for the ICCV 2017 paper "Surface Normals in the Wild"

surfacenet-plus

2020 TPAMI, SurfaceNet+ is a volumetric learning framework for the very sparse MVS. The sparse-MVS benchmark is maintained here. Authors: Mengqi Ji#, Jinzhi Zhang#, Qionghai Dai, Lu Fang.

surfelmeshing

Real-time surfel-based mesh reconstruction from RGB-D video.

svnvs

self-supervised visibility learning for novel view synthesis, CVPR 2021

svoice

We provide a PyTorch implementation of the paper Voice Separation with an Unknown Number of Multiple Speakers In which, we present a new method for separating a mixed audio sequence, in which multiple voices speak simultaneously. The new method employs gated neural networks that are trained to separate the voices at multiple processing steps, while maintaining the speaker in each output channel fixed. A different model is trained for every number of possible speakers, and the model with the largest number of speakers is employed to select the actual number of speakers in a given sample. Our method greatly outperforms the current state of the art, which, as we show, is not competitive for more than two speakers.

swahr-humanpose

Bottom-up Human Pose Estimation

swift30projects

30 mini Swift Apps for self-study