dhw-master Goto Github PK

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.

caffe

Caffe: a fast open framework for deep learning.

caffe-segnet-cudnn5

This repository was a fork of BVLC/caffe and includes the upsample, bn, dense_image_data and softmax_with_loss (with class weighting) layers of caffe-segnet (https://github.com/alexgkendall/caffe-segnet) to run SegNet with cuDNN version 5.

cagnet

CAGNet: Content-Aware Guidance for Salient Object Detection

ceal

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.

channel-pruning

Channel Pruning for Accelerating Very Deep Neural Networks

cvpr2019_pyramid-feature-attention-network-for-saliency-detection

code and model of Pyramid Feature Selective Network for Saliency detection

deep-learning-papers-translation

深度学习论文翻译，包括分类论文，检测论文等

deepcompression-caffe

Caffe for Deep Compression

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

deeplearning-500-questions

深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，近30万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系[email protected] 版权所有，违权必究 Tan 2018.06

doc2edag

drv_package

Deep Robot Vision system for NEU household service robot

dsrg

Weakly-Supervised Semantic Segmentation Network with Deep Seeded Region Growing (CVPR2018)

enet

ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation

fcn.berkeleyvision.org

Fully Convolutional Networks for Semantic Segmentation by Jonathan Long*, Evan Shelhamer*, and Trevor Darrell. CVPR 2015 and PAMI 2016.

fcn.tensorflow

Tensorflow implementation of Fully Convolutional Networks for Semantic Segmentation (http://fcn.berkeleyvision.org)

fcn_train

The code includes all the file that you need in the training stage for FCN

fewshot_detection

Few-shot Object Detection via Feature Reweighting

fewshotdetection

(ECCV 2020) PyTorch implementation of paper "Few-Shot Object Detection and Viewpoint Estimation for Objects in the Wild"

first

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.

focal_loss_multi_class

mutil-class focal loss implemented in keras

focal_segmentation

semantic segmentation with focal loss

fs_pdd