xinxinww

xinxinww's Stars

• udlbook/udlbook

  Understanding Deep Learning - Simon J.D. Prince

  Language:Jupyter Notebook5.5k1.2k

• halfrost/Halfrost-Field

  ✍🏻 这里是写博客的地方 —— Halfrost-Field 冰霜之地

  Language:Go12.8k1.9k

• black0017/MedicalZooPytorch

  A pytorch-based deep learning framework for multi-modal 2D/3D medical image segmentation

  Language:Python1.7k296

• hoya012/deep_learning_object_detection

  A paper list of object detection using deep learning.

  Language:Python11.3k2.8k

• sail-sg/poolformer

  PoolFormer: MetaFormer Is Actually What You Need for Vision (CVPR 2022 Oral)

  Language:Python1.3k116

• yue-zhongqi/gcm-cf

  [CVPR 2021] Released code for Counterfactual Zero-Shot and Open-Set Visual Recognition

  Language:Python15325

• declare-lab/multimodal-deep-learning

  This repository contains various models targetting multimodal representation learning, multimodal fusion for downstream tasks such as multimodal sentiment analysis.

  Language:OpenEdge ABL688143

• thunlp/OpenKE

  An Open-Source Package for Knowledge Embedding (KE)

  Language:Python3.8k984

• 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:Python30.8k4.6k

• rakshithShetty/adversarial-object-removal

  Code base for our paper " Adversarial Scene Editing: Automatic Object Removal from Weak Supervision" appearing in NIPS 2018.

  Language:Python5912

• lucidrains/stylegan2-pytorch

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

  Language:Python3.7k592

• mit-han-lab/data-efficient-gans

  [NeurIPS 2020] Differentiable Augmentation for Data-Efficient GAN Training

  Language:Python1.3k174

• yunjey/show-attend-and-tell

  TensorFlow Implementation of "Show, Attend and Tell"

  Language:Jupyter Notebook905324

• google-research/google-research

  Google Research

  Language:Jupyter Notebook33.5k7.8k

• google-research/uda

  Unsupervised Data Augmentation (UDA)

  Language:Python2.2k313

• tkwoo/anogan-keras

  Unsupervised anomaly detection with generative model, keras implementation

  Language:Python17861

• tSchlegl/f-AnoGAN

  Code for reproducing f-AnoGAN training and anomaly scoring

  Language:Python24564

• xtarx/Unsupervised-Anomaly-Detection-with-Generative-Adversarial-Networks

  Unsupervised Anomaly Detection with Generative Adversarial Networks on MIAS dataset

  Language:Python10135

• tkarras/progressive_growing_of_gans

  Progressive Growing of GANs for Improved Quality, Stability, and Variation

  Language:Python6.1k1.1k

• abachaa/VQA-Med-2019

  Visual Question Answering in the Medical Domain VQA-Med 2019

  7924

• MingchaoZhu/DeepLearning

  Python for《Deep Learning》，该书为《深度学习》(花书) 数学推导、原理剖析与源码级别代码实现

  Language:Python6.2k1.3k

• Project-MONAI/MONAI

  AI Toolkit for Healthcare Imaging

  Language:Python5.5k1k

• davidtellez/contrastive-predictive-coding

  Keras implementation of Representation Learning with Contrastive Predictive Coding

  Language:Python517120

• dev-sungman/Awesome-Self-Supervised-Papers

  Paper bank for Self-Supervised Learning

  57559

• zongyuange/medical-data

  8

• ChanChiChoi/awesome-Face_Recognition

  papers about Face Detection; Face Alignment; Face Recognition && Face Identification && Face Verification && Face Representation; Face Reconstruction; Face Tracking; Face Super-Resolution && Face Deblurring; Face Generation && Face Synthesis; Face Transfer; Face Anti-Spoofing; Face Retrieval;

  4.4k961

• abhijitbendale/OSDN

  Code and data for the research paper "Towards Open Set Deep Networks" A Bendale, T Boult, CVPR 2016

  Language:Python23756

• iCGY96/awesome_OpenSetRecognition_list

  A curated list of papers & resources linked to open set recognition, out-of-distribution, open set domain adaptation and open world recognition

  1k145

• chenjoya/sampling-free

  IEEE TIP: Is heuristic sampling necessary in training deep object detectors? Try sampling-free object detectors!

  Language:Python29425

• JiahuiYu/generative_inpainting

  DeepFill v1/v2 with Contextual Attention and Gated Convolution, CVPR 2018, and ICCV 2019 Oral

  Language:Python3.2k777