Eutenacity

Eutenacity's Stars

• ngosang/trackerslist

  Updated list of public BitTorrent trackers

  47.3k1.3k4526.6k

• microsoft/unilm

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

  Language:Python20.2k3081.4k2.6k

• netchx/netch

  A simple proxy client

  Language:C#16.4k1898102.7k

• microsoft/nni

  An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

  Language:Python14.1k2842.1k1.8k

• miaomiaosoft/PandaOCR

  PandaOCR - 多功能OCR图文识别+翻译+朗读+弹窗+公式+表格+图床+搜图+二维码

  5.2k128266665

• Tianxiaomo/pytorch-YOLOv4

  PyTorch ,ONNX and TensorRT implementation of YOLOv4

  Language:Python4.5k525051.5k

• sovrasov/flops-counter.pytorch

  Flops counter for convolutional networks in pytorch framework

  Language:Python2.8k1598307

• sthalles/SimCLR

  PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations

  Language:Jupyter Notebook2.3k2158469

• ZFTurbo/Weighted-Boxes-Fusion

  Set of methods to ensemble boxes from different object detection models, including implementation of "Weighted boxes fusion (WBF)" method.

  Language:Python1.7k1756238

• dingjiansw101/AerialDetection

  Language:Python79814107184

• fengyang95/pyCFTrackers

  Python re-implementation of some correlation filter based tracker

  Language:Python5261827115

• tim-learn/SHOT

  code released for our ICML 2020 paper "Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation"

  Language:Python43673878

• nimarb/pytorch_influence_functions

  This is a PyTorch reimplementation of Influence Functions from the ICML2017 best paper: Understanding Black-box Predictions via Influence Functions by Pang Wei Koh and Percy Liang.

  Language:Python31773271

• krumo/Domain-Adaptive-Faster-RCNN-PyTorch

  Domain Adaptive Faster R-CNN in PyTorch

  Language:Python30775068

• RoyalVane/CLAN

  ( TPAMI2022 / CVPR2019 Oral ) Taking A Closer Look at Domain Shift: Category-level Adversaries for Semantics Consistent Domain Adaptation

  Language:Python295112645

• astra-vision/rain-rendering

  Rain Rendering for Evaluating and Improving Robustness to Bad Weather (Tremblay et al., 2020) (S. S. Halder et al., 2019)

  Language:Python13642723

• umautobots/GTAVisionExport

  Code to export full segmentations from GTA

  Language:C++126124742

• kevinhkhsu/DA_detection

  Progressive Domain Adaptation for Object Detection

  Language:Jupyter Notebook10472218

• David0tt/DeepGTAV

  A system to easily extract ground truth training data for different machine learning tasks from GTAV

  Language:C++942189

• xiangjjj/implicit_alignment

  Code for ICML2020 "Implicit Class-Conditioned Domain Alignment for Unsupervised Domain Adaptation"

  Language:Python906810

• Gorilla-Lab-SCUT/SRDC-CVPR2020

  Code release for Unsupervised Domain Adaptation via Structurally Regularized Deep Clustering (CVPR2020-Oral).

  Language:Python80101116

• psmmettes/hpn

  Hyperspherical Prototype Networks

  Language:Python67358

• penguinnnnn/Caffe2Pytorch

  A tool to convert Caffe model to Pytorch model.

  Language:Python421216

• MizzouINDFUL/UEUAVSim

  MINDFUL Unreal Engine Based UAV Repository

  Language:Python34209

• Daniil-Osokin/fully-learnable-group-convolution.pytorch

  Implementation of "Fully Learnable Group Convolution for Acceleration of Deep Neural Networks", CVPR'19

  Language:Python335610

• longxianlei/G-ResNeXt_GroupNet

  re-implement of Group ConvNet, also be called as G-ResNext. It's from the paper, reproduction of the paper "Differentiable Learning-to-Group Channels via Groupable Convolutional Neural Networks".

  Language:Python20231

• Ageliss/For_shared_codes

  Language:Python15210

• vc-nju/drfi_python

  DRFI For Region Dissection

  Language:Python13111

• JianboGuo/network-decoupling

  Code for the paper: Network Decoupling: From Regular to Depthwise Separable Convolutions

  Language:Python123

• Eutenacity/LdsConv

  Language:Python3102