nicholasxin Goto Github PK

adaptsegnet

Learning to Adapt Structured Output Space for Semantic Segmentation, CVPR 2018 (spotlight)

amrsegnet

attention-nas-reid

This is the code for the paper ''Person Re-Identification Baseline Based on Attention Block Neural Architecture Search''.

awesome-self-supervised-learning

A curated list of awesome self-supervised methods

axial-deeplab

This is a PyTorch re-implementation of Axial-DeepLab (ECCV 2020 Spotlight)

beal

code for paper Boundary and Entropy-driven Adversarial Learning for Fundus Image Segmentation

cbst

Code for <Domain Adaptation for Semantic Segmentation via Class-Balanced Self-Training> in ECCV18

dal

Domain agnostic learning with disentangled representations

deep-learning

deepmedic

Efficient Multi-Scale 3D Convolutional Neural Network for Segmentation of 3D Medical Scans

deit

Official DeiT repository

domain-generalization

All about domain generalization

fcmi_vi_reid

Visible-infrared Person Re-identification Model Based on Feature Consistency and Modal Indistinguishability

generative-models

Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.

medical-cross-modality-domain-adaptation

[IJCAI'18] Unsupervised Cross-Modality Domain Adaptation of ConvNets for Biomedical Image Segmentations with Adversarial Loss (code&data)

medical-transformer

Pytorch Code for "Medical Transformer: Gated Axial-Attention for Medical Image Segmentation"

ml-visuals

Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.

multimodal_segmentation

Code for Disentangle Align and Fuse for Multimodal and Zero-shot Image Segmentation

pvt

pytorch-cyclegan-and-pix2pix

Image-to-Image Translation in PyTorch

pytorch-revgrad

A gradient reversal layer for pytorch.

ra_fa_cardiac

repvgg

RepVGG: Making VGG-style ConvNets Great Again

sdnet_abus

self-attention-gan

Pytorch implementation of Self-Attention Generative Adversarial Networks (SAGAN)

senet-pytorch

setr

Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers

squeeze_and_excitation

PyTorch Implementation of 2D and 3D 'squeeze and excitation' blocks for Fully Convolutional Neural Networks

synseg-net

SynSeg-Net: Synthetic Segmentation Without Target Modality Ground Truth

tps_stn_pytorch

PyTorch implementation of Spatial Transformer Network (STN) with Thin Plate Spline (TPS)