Pinned Repositories
Active-Learning
AdversarialNetsPapers
The classical papers and codes about generative adversarial nets
AdvSemiSeg
Adversarial Learning for Semi-supervised Semantic Segmentation, BMVC 2018
awesome-semantic-segmentation
:metal: awesome-semantic-segmentation
Binary-Segmentation-Evaluation-Tool
This repo is developed for evaluating binary image segmentation results. Measures, such as MAE, Precision, Recall, F-measure, PR curves and F-measure curves are included.
channel-pruning
Channel Pruning for Accelerating Very Deep Neural Networks
FS_PDD
NEU_Seg
SOD-CNNs-based-code-summary-
The summary of code and paper for salient object detection with deep learning
SSM
Towards Human-Machine Cooperation: Evolving Active Learning with Self-supervised Process for Object Detection
DHW-Master's Repositories
DHW-Master/SSM
Towards Human-Machine Cooperation: Evolving Active Learning with Self-supervised Process for Object Detection
DHW-Master/channel-pruning
Channel Pruning for Accelerating Very Deep Neural Networks
DHW-Master/Active-Learning
DHW-Master/awesome-semantic-segmentation
:metal: awesome-semantic-segmentation
DHW-Master/CEAL
DHW-Master/cfnet
(CVPR'17) Training a Correlation Filter end-to-end allows lightweight networks of 2 layers (600 kB) to achieve state-of-the-art performance in tracking, at high-speed.
DHW-Master/DeepCompression-caffe
Caffe for Deep Compression
DHW-Master/deeplab_v2
基于v2版本的deeplab,使用VGG16模型，在VOC2012，Pascal-context，NYU-v2等多个数据集上进行训练
DHW-Master/ENet
ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation
DHW-Master/fcn.berkeleyvision.org
Fully Convolutional Networks for Semantic Segmentation by Jonathan Long*, Evan Shelhamer*, and Trevor Darrell. CVPR 2015 and PAMI 2016.
DHW-Master/FCN_train
The code includes all the file that you need in the training stage for FCN
DHW-Master/Focal-Loss-implement-on-Tensorflow
The implementation of focal loss proposed on "Focal Loss for Dense Object Detection" by KM He and support for multi-label dataset.
DHW-Master/focal_segmentation
semantic segmentation with focal loss
DHW-Master/iCaRL
DHW-Master/keras
Deep Learning for humans
DHW-Master/KittiSeg
A Kitti Road Segmentation model implemented in tensorflow.
DHW-Master/Mask_RCNN
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
DHW-Master/NLDF
DHW-Master/OSVOS-caffe
One-Shot Video Object Segmentation
DHW-Master/PosematchAndRecognition
基于双目的人体姿态匹配与识别
DHW-Master/py-R-FCN
R-FCN with joint training and python support
DHW-Master/pytorch-semantic-segmentation
PyTorch for Semantic Segmentation
DHW-Master/RFCN
This is a Pytorch implementation of RFCN[1] for saliency detection.
DHW-Master/tensorflow-fcn
An Implementation of Fully Convolutional Networks in Tensorflow.
DHW-Master/TernausNet
UNet model with VGG11 encoder pre-trained on Kaggle Carvana dataset
DHW-Master/tf-Faster-RCNN
TensorFlow implementation of Faster R-CNN
DHW-Master/tfwss
Weakly Supervised Segmentation with Tensorflow. Implements instance segmentation as described in Simple Does It: Weakly Supervised Instance and Semantic Segmentation, by Khoreva et al. (CVPR 2017).
DHW-Master/TuSimple-DUC
Understanding Convolution for Semantic Segmentation
DHW-Master/video_prop_networks
Code for our CVPR17 paper on "Video Propagation Networks"
DHW-Master/Weakly-object-detection
Fast rcnn,Weakly-supervised-object-detection