津南数字制造 unet解决方案

Implementation code of the paper: FishNet: A Versatile Backbone for Image, Region, and Pixel Level Prediction, NeurIPS 2018

This is a keras implementation of MobileNetV3 architecture as described in the paper "Searching for MobileNetV3"

SiamRPN, SiamRPN++, unofficial implementation of "SiamRPN++" (CVPR2019), multi-GPUs, LMDB.

my solution with 0.67 accuracy

天池医疗AI大赛[第一季]：肺部结节智能诊断 UNet/VGG/Inception/ResNet/DenseNet

Object detection, 3D detection, and pose estimation using center point detection:

Code for CVPR 2019 paper "Libra R-CNN: Towards Balanced Learning for Object Detection"

第五届百度西交大大数据竞赛 城市区域功能分类 Baseline

天池比赛，kaggle，点石

use pytorch to do image classfiication tasks

Segmentation models with pretrained backbones. PyTorch.

fast image augmentation library and easy to use wrapper around other libraries

Train the HRNet model on ImageNet

liver cancer classify model with DL(3D-Conv)大数据医疗—肝癌影像AI诊断比赛

A DenseBlock-Unet for Retinal Blood Vessel Segmentation

The project is an official implement of our CVPR2019 paper "Recurrent Back-Projection Network for Video Super-Resolution"

cvpr2019 papers

[CVPR2019] Fast Online Object Tracking and Segmentation: A Unifying Approach

A collection of state-of-the-art video or single-image super-resolution architectures, reimplemented in tensorflow.

visualization tools for Tianchi_jinnan2_season2 data

This repo will contain source code and materials for the TecoGAN project, i.e. code for a TEmporally COherent GAN

Repo for counting stars and contributing. Press F to pay respect to glorious developers.

A PyTorch-Based Framework for Deep Learning in Computer Vision

Segmentation models with pretrained backbones. Keras.

The manuscript has been accepted in TMI.

The project is an official implement of our CVPR2018 paper "Deep Back-Projection Networks for Super-Resolution" (Winner of NTIRE2018 and PIRM2018)

mixup: Beyond Empirical Risk Minimization

TMI 2018. H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation from CT Volumes

Codes for paper "Mask Scoring R-CNN".