wooseok-shin

wooseok-shin's Stars

• BBBBchan/Awesome-Semi-Supervised-Semantic-Segmentation

  A summary of recent semi-supervised semantic segmentation methods

  12514

• google-research/semivl

  Official Implementation of SemiVL: Semi-Supervised Semantic Segmentation with Vision-Language Guidance

  Language:Python816

• LiheYoung/UniMatch

  [CVPR 2023] Revisiting Weak-to-Strong Consistency in Semi-Supervised Semantic Segmentation

  Language:Python42959

• williamium3000/diverse-cotraining

  Office implementation of Diverse Co-training (ICCV2023)

  Language:C9

• wooseok-shin/PrevMatch

  Official implementation of PrevMatch: Revisiting and Maximizing Temporal Knowledge in Semi-supervised Semantic Segmentation

  Language:Python71

• wooseok-shin/MetricGAN-OKD

  Official PyTorch implementation of "Multi-Metric Optimization of MetricGAN via Online Knowledge Distillation for Speech Enhancement" (ICML 2023)

  Language:Python192

• wooseok-shin/MetricGAN-plus-pytorch

  MetricGAN+ PyTorch Implementation

  Language:Python154

• Leebh-kor/Simple-code-Visualizing-the-Loss-Landscape-of-Neural-Nets

  Reimplmentation of Visualizing the Loss Landscape of Neural Nets with PyTorch 1.8

  Language:Python171

• winddori2002/MANNER

  MANNER: Multi-view Attention Network for Noise ERasure (Speech enhancement in time-domain)

  Language:Python549

• facebookresearch/denoiser

  Real Time Speech Enhancement in the Waveform Domain (Interspeech 2020)We provide a PyTorch implementation of the paper Real Time Speech Enhancement in the Waveform Domain. In which, we present a causal speech enhancement model working on the raw waveform that runs in real-time on a laptop CPU. The proposed model is based on an encoder-decoder architecture with skip-connections. It is optimized on both time and frequency domains, using multiple loss functions. Empirical evidence shows that it is capable of removing various kinds of background noise including stationary and non-stationary noises, as well as room reverb. Additionally, we suggest a set of data augmentation techniques applied directly on the raw waveform which further improve model performance and its generalization abilities.

  Language:Python1.6k296

• Karel911/TRACER

  TRACER: Extreme Attention Guided Salient Object Tracing Network (AAAI 2022) implementation in PyTorch

  Language:Python19141

• F2Wang/ObjectDatasetTools

  Tools to create pixel-wise object masks, bounding box labels (2D and 3D) and 3D object model (PLY triangle mesh) for object sequences filmed with an RGB-D camera. This project prepares training and testing data for various deep learning projects such as 6D object pose estimation projects singleshotpose, as well as object detection and instance segmentation projects.

  Language:Python39392

• demul/extrinsic2pyramid

  Visualize Camera's Pose Using Extrinsic Parameter by Plotting Pyramid Model on 3D Space

  Language:Python25034

• matjesg/deepflash2

  A deep-learning pipeline for segmentation of ambiguous microscopic images.

  Language:Jupyter Notebook5610

• ssut/py-hanspell

  파이썬 한글 맞춤법 검사 라이브러리. (네이버 맞춤법 검사기 사용)

  Language:Python320111

• ArcherFMY/sal_eval_toolbox

  evaluation toolbox for salient object detection

  Language:MATLAB14640

• HaohanWang/HFC

  Implementation for the paper (CVPR Oral): High Frequency Component Helps Explain the Generalization of Convolutional Neural Networks

  Language:Python23628

• NVIDIA/semantic-segmentation

  Nvidia Semantic Segmentation monorepo

  Language:Python1.8k388

• lessw2020/Ranger-Deep-Learning-Optimizer

  Ranger - a synergistic optimizer using RAdam (Rectified Adam), Gradient Centralization and LookAhead in one codebase

  Language:Python1.2k172

• hubutui/DiceLoss-PyTorch

  DiceLoss for PyTorch, both binary and multi-class.

  Language:Python14632

• DengPingFan/PraNet

  PraNet: Parallel Reverse Attention Network for Polyp Segmentation, MICCAI 2020 (Oral). Code using Jittor Framework is available.

  Language:Python416119

• ZJUGiveLab/UNet-Version

  Language:Python629134

• 4uiiurz1/pytorch-nested-unet

  PyTorch implementation of UNet++ (Nested U-Net).

  Language:Python812205

• yunjey/pytorch-tutorial

  PyTorch Tutorial for Deep Learning Researchers

  Language:Python29.4k8k

• huggingface/pytorch-image-models

  The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more

  Language:Python30.6k4.6k

• RWB0104/KorCham

  상공회의소 자격증 자리확인 매크로

  Language:Java2

• shaharazulay/adversarial-autoencoder-classifier

  PyTorch implementations of Non-parametric Unsupervised Classification with Adversarial Autoencoders

  Language:Python112

• ashaypathak/Recommendation-system

  This would inlude some the stuff i did in implementing various types of recommendation system.

  Language:Jupyter Notebook2233

• trent-b/iterative-stratification

  scikit-learn cross validators for iterative stratification of multilabel data

  Language:Python83276

• zhanghang1989/PyTorch-Encoding

  A CV toolkit for my papers.

  Language:Python2k451