sunguwei

sunguwei's Stars

• 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:Python32.8k3189484.8k

• microsoft/unilm

  Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities

  Language:Python20.5k3071.4k2.6k

• microsoft/Swin-Transformer

  This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".

  Language:Python14.2k1273182.1k

• utkuozbulak/pytorch-cnn-visualizations

  Pytorch implementation of convolutional neural network visualization techniques

  Language:Python7.9k1151061.5k

• JingyunLiang/SwinIR

  SwinIR: Image Restoration Using Swin Transformer (official repository)

  Language:Python4.6k53154558

• facebookresearch/deit

  Official DeiT repository

  Language:Python4.1k47197562

• princeton-vl/RAFT

  Language:Python3.4k38170640

• HobbitLong/PyContrast

  PyTorch implementation of Contrastive Learning methods

  Language:Python1.9k4228185

• Tencent/TFace

  A trusty face analysis research platform developed by Tencent Youtu Lab

  Language:Python1.4k34134229

• berniwal/swin-transformer-pytorch

  Implementation of the Swin Transformer in PyTorch.

  Language:Python8121025129

• Mikoto10032/AutomaticWeightedLoss

  Multi-task learning using uncertainty to weigh losses for scene geometry and semantics, Auxiliary Tasks in Multi-task Learning

  Language:Python59351883

• pterhoer/FaceImageQuality

  Code and information for face image quality assessment with SER-FIQ

  Language:Python544124891

• GT-RIPL/Continual-Learning-Benchmark

  Evaluate three types of task shifting with popular continual learning algorithms.

  Language:Python515151191

• huawei-noah/Pretrained-IPT

  Language:Python453105963

• liruoteng/OpticalFlowToolkit

  Python-based optical flow toolkit for existing popular dataset

  Language:Python30381479

• CYang828/transformer-all-in-one

  Language:Jupyter Notebook2625045

• Tushar-N/pytorch-resnet3d

  I3D Nonlocal ResNets in Pytorch

  Language:Python24952039

• GMvandeVen/brain-inspired-replay

  A brain-inspired version of generative replay for continual learning with deep neural networks (e.g., class-incremental learning on CIFAR-100; PyTorch code).

  Language:Python22871265

• isalirezag/TReS

  No-Reference Image Quality Assessment via Transformers, Relative Ranking, and Self-Consistency

  Language:Python1524017

• wenguanwang/DHF1K

  Revisiting Video Saliency: A Large-scale Benchmark and a New Model (CVPR18, PAMI19)

  Language:MATLAB139112028

• pavancm/CONTRIQUE

  Official implementation for "Image Quality Assessment using Contrastive Learning"

  Language:Python12832813

• anse3832/MUSIQ

  Unofficial implementation of MUSIQ (Multi-Scale Image Quality Transformer)

  Language:Python10811114

• lidq92/LinearityIQA

  [official] Norm-in-Norm Loss with Faster Convergence and Better Performance for Image Quality Assessment (ACM MM 2020)

  Language:Python9731614

• researchmm/CKDN

  [ICCV'21] CKDN: Learning Conditional Knowledge Distillation for Degraded-Reference Image Quality Assessment

  Language:Python56385

• ShipengWang/Adam-NSCL

  PyTorch implementation of our Adam-NSCL algorithm from our CVPR2021 (oral) paper "Training Networks in Null Space for Continual Learning"

  Language:Python53142

• ch-andrei/VTAMIQ

  Full-Reference Vision Transformer (ViT)-based IQA method

  Language:Python20230

• cpf0079/UCDA

  Source codes for "Unsupervised Curriculum Domain Adaptation for No-Reference Video Quality Assessment"

  Language:Python17273

• weizhou-geek/SFSN

  Implementation of QoMEX 2021 "Image Super-Resolution Quality Assessment: Structural Fidelity Versus Statistical Naturalness"

  Language:MATLAB17101

• junyongyou/lsct_phiqnet

  LSCT-PHIQNet

  Language:Python12231

• rr8shah/TSARA

  Official PyTorch implementations of our ICASSP 2021 paper "REAL VERSUS FAKE 4K - AUTHENTIC RESOLUTION ASSESSMENT"

  Language:Python3112