| PASCALVOC |
The Pascal Visual Object Classes Challenge: A Retrospective |
IJCV 2015 |
| 翻译 |
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计算机视觉会议及期刊排名 |
|
| DeCAF |
DeCAF: A Deep Convolutional Activation Featurefor Generic Visual Recognition |
ICML 2014 |
| 翻译 |
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在计算机视觉中的应用 |
|
| 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 |