PASCALVOC | The Pascal Visual Object Classes Challenge: A Retrospective | IJCV 2015 |
翻譯 | SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation | TPAMI 2015 |
Deeplab v1 & v2 | Semantic Image Segmentation with Deep Convolutional Nets and Fully | ICLR 2015, TPAMI 2017 |
Segnet | SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image | TPAMI 2015 |
fcCRFs | Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials | NIPS 2011, CVPR 2012 |
ICNet | ICNet for Real-Time Semantic Segmentation on High-Resolution Images |
A Review on Deep Learning Techniques Applied to Semantic Segmentation |
DeconvNet | Learning Deconvolution Network for Semantic Segmentation | ICCV 2015 |
CRFasRNN | Conditional Random Fields as Recurrent Neural Networks | ICCV 2015 |
SqueezeNet | SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size | ICLR 2017 |
CNN-CRF | Efficient Piecewise Training of Deep Structured Models for Semantic Segmentation | CVPR 2016 |
TuSimple | Understanding convolution for semantic segmentation |
Batch Norm | Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift | CVPR 2016 |
PSPNet | Pyramid Scene Parsing Network | CVPR 2017 |
Caffe | Caffe: Convolutional architecture for fast feature embedding | CVPR 2015 |
CCF計算機視覺會議及期刊排名 |
DeCAF | DeCAF: A Deep Convolutional Activation Featurefor Generic Visual Recognition | ICML 2014 |
翻譯 | A review on image segmentation techniques | Pattern Recognition 1993 |
Predicting Deeper into the Future of Semantic Segmentation | ICCV 2017 |
Netwarp | Semantic Video CNNs through Representation Warping | ICCV 2017 |
SDS | Simultaneous Detection and Segmentation | ECCV2014 |
Learning Hierarchical Features for Scene Labeling | TPAMI 2013 |
DIS | Deep Dual Learning for Semantic Image Segmentation | ICCV 2017 |
SDN | Stacked Deconvolutional Network for Semantic Segmentation |
IDW-CNN | Learning Object Interactions and Descriptions for Semantic Image Segmentation | CVPR 2017 |
Residual Networks Behave Like Ensembles of Relatively Shallow Networks | NIPS 2016 |
Deep networks with stochastic depth | ECCV 2016 |
mAP在計算機視覺中的應用 |
U-Net | U-Net: Convolutional Networks for Biomedical Image Segmentation | ICMICCAI 2015 |
Residual attention network for image classification | CVPR 2017 |
ParseNet | ParseNet: Looking Wider to See Better | ICLR 2016 |
Recurrent Convolutional Neural Networks for Scene Labeling | ICML 2014 |
zoom-out | Feedforward semantic segmentation with zoom-out features | CVPR 2015 |
Deeplab v3 | Rethinking Atrous Convolution for Semantic Image Segmentation |
Deeplab v3+ | Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation |
SGN | SGN: Sequential Grouping Networks for Instance Segmentation | ICCV 2017 |
GCPNet | Scene Parsing with Global Context Embedding | ICCV 2017 |
FoveaNet | FoveaNet: Perspective-aware Urban Scene Parsing | ICCV 2017 |