stellali-0501,github

attention-gated-networks

Use of Attention Gates in a Convolutional Neural Network / Medical Image Classification and Segmentation

attention-transfer

Improving Convolutional Networks via Attention Transfer (ICLR 2017)

cross-stitch-networks-for-multi-task-learning

A Tensorflow implementation of the paper arXiv:1604.03539

cycle-shape-gan-chainer

#The demo of Cycle-Shape-GAN using chainer

d-sne

Implementation of our proposed algorithm in domain adaptation for image classification

This project is an implementation of the Generative Adversarial Network proposed in our CVPR 2017 paper - DeLiGAN : Generative Adversarial Networks for Diverse and Limited Data. DeLiGAN is a simple but effective modification of the GAN framework and aims to improve performance on datasets which are diverse yet small in size.

fewshot_gan-unet3d

Tensorflow implementation of our paper: Few-shot 3D Multi-modal Medical Image Segmentation using Generative Adversarial Learning

funit

Translate images to unseen domains in the test time with few example images.

mean-teacher

A state-of-the-art semi-supervised method for image recognition

miccai17-mmwhs-hybrid

If the code is helpful for your work, please cite our paper "Hybrid Loss Guided Convolutional Networks for Whole Heart Parsing" in STACOM Workshop of MICCAI 2017.

mtan

The implementation of "End-to-End Multi-Task Learning with Attention" [CVPR'19].

papers

CV和NLP结合的任务，侧重于图像生成文字

pwc

Papers with code. Sorted by stars. Updated weekly.

pyramid-attention-networks-pytorch

Implementation of Pyramid Attention Networks for Semantic Segmentation.

sc-cam

SC-CAM: Weakly-Supervised Semantic Segmentation via Sub-category Exploration (CVPR 2020)

seam

Self-supervised Equivariant Attention Mechanism for Weakly Supervised Semantic Segmentation, CVPR 2020 (Oral)

semi-supervised-segmentation-cyclegan

Pytorch implementation of our paper: Revisting Cycle-GAN for semi-supervised segmentation

task_driven_data_augmentation

semi-supervised and task driven data augmentation code to improve segmentation performance

ua-mt

code for MICCAI 2019 paper 'Uncertainty-aware Self-ensembling Model for Semi-supervised 3D Left Atrium Segmentation'.

wshp

Code for CVPR'18 spotlight "Weakly and Semi Supervised Human Body Part Parsing via Pose-Guided Knowledge Transfer"

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