-
Scale-Aware Trident Networks for Object Detection
- Yanghao Li, Yuntao Chen, Naiyan Wang, Zhaoxiang Zhang
- (arXiv: 1901)
-
Semantic Instance Meets Salient Object: Study on Video Semantic Salient Instance Segmentation
- Trung-Nghia Le, Akihiro Sugimoto
- (arXiv: 1807 | WACV 19)
-
Pixel-wise Attentional Gating for Scene Parsing
- Shu Kong, Charless Fowlkes
- (WACV 19)
-
A New Ensemble Learning Framework for 3D Biomedical Image Segmentation
- Hao Zheng, Yizhe Zhang, Lin Yang, Peixian Liang, Zhuo Zhao, Chaoli Wang, Danny Z. Chen
- (arXiv:1812 | AAAI 19 | code)
-
Gradient Harmonized Single-stage Detector
- Buyu Li, Yu Liu, Xiaogang Wang
- (arXiv: 1811 | AAAI 19 oral | pytorch, code)
-
Multiview Cross-supervision for Semantic Segmentation
- Yuan Yao, Hyun Soo Park
- (arXiv: 1812)
-
CCNet: Criss-Cross Attention for Semantic Segmentation
- Z Huang, X Wang, L Huang, C Huang, Y Wei, W Liu
-
ShelfNet for Real-time Semantic Segmentation
- J Zhuang, J Yang
- (arxiv: 1811)
-
See and Think: Disentangling Semantic Scene Completio [pytorch]
- Shice Liu, YU HU, Yiming Zeng, Qiankun Tang, Beibei Jin, Yinhe Han, Xiaowei Li
- (PDF | Supplemental | Poster)
-
Symbolic Graph Reasoning Meets Convolutions
- X Liang, Zhiting Hu, H Zhang, L Lin, EP Xing
- (PDF | Supplemental)
-
Unsupervised domain adaptation for medical imaging segmentation with self-ensembling
- Christian S. Perone, Pedro Ballester, Rodrigo C. Barros, Julien Cohen-Adad
- (arXiv: 1811)
-
Scene Parsing via Dense Recurrent Neural Networks with Attentional Selection
- Heng Fan, Peng Chu, Longin Jan Latecki, Haibin Ling
- (arXiv: 1811)
-
Self-Erasing Network for Integral Object Attention
- Qibin Hou, Peng-Tao Jiang, Yunchao Wei, Ming-Ming Cheng
- (arXiv: 1810 | NIPS 18)
-
Smoothed Dilated Convolutions for Improved Dense Prediction [tensorflow]
- Zhengyang Wang, Shuiwang Ji
- (arXiv: 1808 | KDD 18)
-
Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells
- Vladimir Nekrasov, Hao Chen, Chunhua Shen, Ian Reid
- (arXiv: 1810)
- NAS
-
Segmenting Unknown 3D Objects from Real Depth Images using Mask R-CNN Trained on Synthetic Point Clouds [temsorflow]
- Michael Danielczuk, Matthew Matl, Saurabh Gupta, Andrew Li, Andrew Lee, Jeffrey Mahler, Ken Goldberg
- (arXiv: 1809)
-
Searching for Efficient Multi-Scale Architectures for Dense Image Prediction [tensorflow]
- Liang-Chieh Chen, M. D. Collins, Y. Zhu, G. Papandreou, B. Zoph, F. Schroff, H. Adam, J. Shlens
- (arXiv: 1809 | NIPS 18)
- deeplab, neural architecture search (NAS), meta learning
-
DifNet: Semantic Segmentation by Diffusion Networks
- Peng Jiang, Fanglin Gu, Yunhai Wang, Changhe Tu, Baoquan Chen
- (arXiv: 1805 | NIPS 18)
-
Autofocus Layer for Semantic Segmentation [pytorch]
- Yao Qin, K. Kamnitsas, S. Ancha, J. Nanavati, G. Cottrell, A. Criminisi, A. Nori
- (arXiv: 1805 | MICCAI 18)
-
Convolutional CRFs for Semantic Segmentation [pytorch]
- Marvin T. T. Teichmann, Roberto Cipolla
- (arXiv: 1805)
-
Context Encoding for Semantic Segmentation [pytorch]
- Hang Zhang, K. Dana, Jianping Shi, Z. Zhang, Xiaogang Wang, A. T., A. Agrawal,
- (arXiv: 1803 | CVPR 18 oral | slides)
- Segmentation Results: VOC2012 [EncNet], mean: 85.9
-
Learning to Adapt Structured Output Space for Semantic Segmentation [pytorch]
- Yi-Hsuan Tsai, W.-C. Hung, S. Schulter, K. Sohn, Ming-Hsuan Yang, M. Chandraker,
- (arXiv: 1802 | CVPR 18 spotlight)
-
Weakly Supervised Instance Segmentation using Class Peak Response
- Yanzhao Zhou, Yi Zhu, Qixiang Ye, Qiang Qiu, Jianbin Jiao
- (arXiv: 1804 | CVPR 18 Spotligh | pytorch)
-
Learning a Discriminative Feature Network for Semantic Segmentation [pytorch] [temsorflow]
- Changqian Yu, Jingbo Wang, Chao Peng, Changxin Gao, Gang Yu, Nong Sang,
- (arXiv: 1804 | CVPR 18)
-
Recurrent Pixel Embedding for Instance Grouping [matlab]
- Shu Kong, Charless Fowlkes
- (arXiv: 1712 | CVPR 18 spotlight | project | slides)
-
Recurrent Scene Parsing with Perspective Understanding in the Loop [matlab]
-
Quantization of Fully Convolutional Networks for Accurate Biomedical Image Segmentation
- Xiaowei Xu, Qing Lu, Lin Yang, Sharon Hu, Danny Chen, Yu Hu, Yiyu Shi
- (arXiv: 1803 | CVPR 18)
-
Dense Decoder Shortcut Connections for Single-Pass Semantic Segmentation
- Piotr Bilinski, Victor Prisacariu
- CVPR 18
-
DenseASPP for Semantic Segmentation in Street Scenes [pytorch]
- Maoke Yang, Kun Yu, Chi Zhang, Zhiwei Li, Kuiyuan Yang
- CVPR 18
-
Dynamic-structured Semantic Propagation Network
- Xiaodan Liang, Hongfei Zhou, Eric P. Xing
- (arXiv: 1803 | CVPR 18)
-
Fully Convolutional Adaptation Networks for Semantic Segmentation
- Yiheng Zhang, Zhaofan Qiu, Ting Yao, Dong Liu, Tao Mei
- arXiv: 1804 | CVPR 18)
-
ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation [pytorch]
- Sachin Mehta, Mohammad Rastegari, Anat Caspi, Linda Shapiro, Hannaneh Hajishirzi
- (arXiv: 1803 | ECCV 18)
-
Adversarial Learning for Semi-supervised Semantic Segmentation [pytorch]
- Wei-Chih Hung, Yi-Hsuan Tsai, Yan-Ting Liou, Yen-Yu Lin, and Ming-Hsuan Yang
- (arXiv: 1802 | BMVC 18)
-
Light-Weight RefineNet for Real-Time Semantic Segmentation [pytorch]
-
Multi-Scale Context Intertwining for Semantic Segmentation
-
Dual Attention Network for Scene Segmentation [pytorch]
- Jun Fu, Jing Liu, Haijie Tian, Zhiwei Fang, Hanqing Lu
- (arxiv: 1809 | AAAI19?)
-
BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation
- Changqian Yu, Jingbo Wang, Chao Peng, Changxin Gao, Gang Yu, Nong Sang
- (arXiv: 1808 | ECCV 18)
-
Adaptive Affinity Field for Semantic Segmentation [tensorflow]
- Tsung-Wei Ke, Jyh-Jing Hwang, Ziwei Liu, Stella X. Yu
- (arXiv: 1803 | ECCV 18 | Project)
-
Pyramid Attention Network for Semantic Segmentation
- Hanchao Li, Pengfei Xiong, Jie An, Lingxue Wang
- (arXiv: 1805 | BMVC 18)
- [PAN] Segmentation Results: VOC2012, mean: 84.0
-
ExFuse: Enhancing Feature Fusion for Semantic Segmentation [pytorch]
- Zhenli Zhang, Xiangyu Zhang, Chao Peng, Dazhi Cheng, Jian Sun
- (arXiv: 1804 | ECCV 18)
-
ContextNet: Exploring Context and Detail for Semantic Segmentation in Real-time [keras]
- Rudra P K Poudel, Ujwal Bonde, Stephan Liwicki, Christopher Zach
- (arXiv: 1805 | BMVC 18 | cn)
-
Vortex Pooling: Improving Context Representation in Semantic Segmentation
- Chen-Wei Xie, Hong-Yu Zhou, Jianxin Wu
- (arXiv: 1804)
-
A Multi-Layer Approach to Superpixel-based Higher-order Conditional Random Field for Semantic Image Segmentation
- Li Sulimowicz, Ishfaq Ahmad, Alexander Aved
- (arXiv: 1804)
-
ShuffleSeg: Real-time Semantic Segmentation Network [tensorflow]
- Mostafa Gamal, Mennatullah Siam, Moemen Abdel-Razek
- (arXiv: 1803 | ICIP 18)
-
RTSeg: Real-time Semantic Segmentation Comparative Study [tensorflow]
- Mennatullah Siam, Mostafa Gamal, M. Abdel-Razek, S. Yogamani, M. Jagersand
- (arXiv: 1803 | ICIP 18)
-
Decoupled Spatial Neural Attention for
Weakly Supervised
Semantic Segmentation- Tianyi Zhang, Guosheng Lin, Jianfei Cai, Tong Shen, Chunhua Shen, Alex C. Kot
- (arXiv: 1803)
-
Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation [tensorflow] [keras] [pytorch]
- Liang-Chieh Chen, Yukun Zhu, George Papandreou, Florian Schroff, Hartwig Adam
- (arXiv: 1802 | ECCV 18)
- DeepLab v3+
-
Locally Adaptive Learning Loss for Semantic Image Segmentation
- Jinjiang Guo, Pengyuan Ren, Aiguo Gu, Jian Xu, Weixin Wu
- (arXiv: 1802)
-
TernausNet: U-Net with VGG11 Encoder Pre-Trained on ImageNet for Image Segmentation [PyTorch]
- Vladimir Iglovikov, Alexey Shvets
- (arXiv: 1801)
-
MobileNetV2: Inverted Residuals and Linear Bottlenecks
- Mark Sandler, Andrew Howard, Menglong Zhu, Andrey Zhmoginov, Liang-Chieh Chen
- (arXiv: 1801)
-
Mix-and-Match Tuning for Self-Supervised Semantic Segmentation [caffe]
- Xiaohang Zhan, Ziwei Liu, Ping Luo, Xiaoou Tang, Chen Change Loy
- (arXiv: 1712 | AAAI 18)
-
Domain Adaptation for Semantic Segmentation via Class-Balanced Self-Training [mxnet]
- Yang Zou, Zhiding Yu, B. V. K. Vijaya Kumar, Jinsong Wang
- (arXiv: 1810 | ECCV 18)
-
Joint Learning of Intrinsic Images and Semantic Segmentation
- Anil S. Baslamisli, T. T. Groenestege, P. Das, Hoang-An Le, S. Karaoglu, T. Gevers
- (arXiv: 1807 | ECCV 18 | project & dataset)
-
Characterizing Adversarial Examples Based on Spatial Consistency Information for Semantic Segmentation
- Chaowei Xiao, Ruizhi Deng, Bo Li, Fisher Yu, Mingyan Liu, Dawn Song
- (arXiv: 1810 | ECCV 18)
-
Effective Use of Synthetic Data for Urban Scene Semantic Segmentation
- Fatemeh Sadat Saleh, Mohammad Sadegh Aliakbarian, Mathieu Salzmann, Lars Petersson, Jose M. Alvarez
- (ECCV 18)
-
ICNet for Real-Time Semantic Segmentation on High-Resolution Images [caffe]
- Hengshuang Zhao, Xiaojuan Qi, Xiaoyong Shen, Jianping Shi, Jiaya Jia
- (arXiv: 1704 | ECCV 18 | project)
-
End-to-End Joint Semantic Segmentation of Actors and Actions in Video
- Jingwei Ji, Shyamal Buch, Alvaro Soto, Juan Carlos Niebles
- (ECCV 18)
-
Efficient Uncertainty Estimation for Semantic Segmentation in Videos [pytorch]
- (arXiv: 1807 | ECCV 18)
-
Multichannel Semantic Segmentation with Unsupervised Domain Adaptation
-
Kohei Watanabe, Kuniaki Saito, Yoshitaka Ushiku, Tatsuya Harada
-
(arXiv: | ECCV 18 workshop)
-
Cascade Mask Generation Framework for Fast Small Object Detection
-
Efficient Coarse-to-Fine Non-Local Module for the Detection of Small Objects
- H Levi, S Ullman
- (arXiv:1811)
-
Focal Loss in 3D Object Detection [tensorflow]
- Peng Yun, Lei Tai, Yuan Wang, and Ming Liu
- (arXiv:1809)
-
Receptive Field Block Net for Accurate and Fast Object Detection [RFBnet, pytorch]
- Songtao Liu, Di Huang, Yunhong Wang
- (arXiv: 1711 | ECCV 18)
- SSD: ECCV 2016 [pytorch] [caffe] arXiv:1512.02325
-
Revisiting RCNN: On Awakening the Classification Power of Faster RCNN [mxnet]
- Bowen Cheng, Yunchao Wei, Honghui Shi, Rogerio Feris, Jinjun Xiong, Thomas Huang
- (arXiv: 1803 | ECCV 18)
- SPFTN: A Joint Learning Framework for Localizing and Segmenting Objects in Weakly Labeled Videos
- Dingwen Zhang ; Junwei Han ; Le Yang ; Dong Xu
- (| TPAMI)
-
End-to-end Learning of Convolutional Neural Net and Dynamic Programming for Left Ventricle Segmentation
- Nhat M. Nguyen, Nilanjan Ray
- (arXiv)
-
Adversarial Examples for Semantic Segmentation and Object Detection [caffe]
- Cihang Xie, Jianyu Wang, Zhishuai Zhang, Yuyin Zhou, Lingxi Xie, Alan Yuille
- (arXiv: 1703 | ICCV 17)
-
Learning to Segment Every Thing
- (arXiv: 1711 | 2017 )
-
Deep Dual Learning for Semantic Image Segmentation
- Ping Luo, Guangrun Wang, Liang Lin, Xiaogang Wan, 2017
-
Scene Parsing with Global Context Embedding [caffe]
- Wei-Chih Hung, Yi-Hsuan Tsai, X. Shen, Zhe Lin, K. Sunkavalli, X. Lu, and Ming-Hsuan Yang, ICCV/1710
-
FoveaNet: Perspective-aware Urban Scene Parsing
- Xin Li, Zequn Jie, Wei Wang, Changsong Liu, Jimei Yang, Xiaohui Shen, Zhe Lin, Qiang Chen, Shuicheng Yan, Jiashi Feng
- arXiv:1708.02421
- ICCV 17
-
Segmentation-Aware Convolutional Networks Using Local Attention Masks - 2017
-
Stacked Deconvolutional Network for Semantic Segmentation-2017
-
Semantic Segmentation via Structured Patch Prediction, Context CRF and Guidance CRF [caffe]
- Falong Shen, Rui Gan, Shuicheng Yan, Gang Zeng, CVPR/17 [cn]
-
[RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation [matlab]
- Guosheng Lin, Anton Milan, Chunhua Shen, Ian Reid,
- CVPR
- arXiv:1611
- Code: MatConvNet [matlab]
-
BlitzNet: A Real-Time Deep Network for Scene Understanding
- 2017
-
Efficient Yet Deep Convolutional Neural Networks for Semantic Segmentation
- 2017
-
LinkNet: Exploiting Encoder Representations for Efficient Semantic Segmentation
- 2017
-
Rethinking Atrous Convolution for Semantic Image Segmentation
- 2017(DeeplabV3)
-
Learning Object Interactions and Descriptions for Semantic Image Segmentation
- 2017
-
Pixel Deconvolutional Networks
- 2017
-
Dilated Residual Networks
- 2017
-
Improved Image Segmentation via Cost Minimization of Multiple Hypotheses [BMVC, pdf][Matlab]
- Marc Bosch, Christopher M. Gifford, Austin G. Dress, Clare W. Lau, Jeffrey G. Skibo, Gordon A. Christie, BMVC/17
-
A Review on Deep Learning Techniques Applied to Semantic Segmentation
- 2017
-
BiSeg: Simultaneous Instance Segmentation and Semantic Segmentation with Fully Convolutional Networks
-
Efficient ConvNet for Real-time Semantic Segmentation - 2017
-
Not All Pixels Are Equal: Difficulty-Aware Semantic Segmentation via Deep Layer Cascade
- 2017
-
Loss Max-Pooling for Semantic Image Segmentation
- 2017
-
Annotating Object Instances with a Polygon-RNN
- 2017
-
Feature Forwarding: Exploiting Encoder Representations for Efficient Semantic Segmentation
- 2017
-
Reformulating Level Sets as Deep Recurrent Neural Network Approach to Semantic Segmentation
- 2017
-
Adversarial Examples for Semantic Image Segmentation -2017
-
Large Kernel Matters - Improve Semantic Segmentation by Global Convolutional Network -2017
-
Label Refinement Network for Coarse-to-Fine Semantic Segmentation
- 2017
-
PixelNet: Representation of the pixels, by the pixels, and for the pixels
- 2017
-
LabelBank: Revisiting Global Perspectives for Semantic Segmentation
- 2017
-
Progressively Diffused Networks for Semantic Image Segmentation
- 2017
-
Understanding Convolution for Semantic Segmentation
- 2017
-
Predicting Deeper into the Future of Semantic Segmentation -2017
-
Pyramid Scene Parsing Network [caffe]
- Hengshuang Zhao, Jianping Shi, Xiaojuan Qi, Xiaogang Wang, Jiaya Jia
- PSPnet [project]
-
FCNs in the Wild: Pixel-level Adversarial and Constraint-based Adaptation
- 2016
-
FusionNet: A deep fully residual convolutional neural network for image segmentation in connectomics
- 2016
-
Learning from Weak and Noisy Labels for Semantic Segmentation - 2017
-
The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation
-
Full-Resolution Residual Networks for Semantic Segmentation in Street Scenes
-
PixelNet: Towards a General Pixel-level Architecture-2016
-
Recalling Holistic Information for Semantic Segmentation-2016
-
Semantic Segmentation using Adversarial Networks-2016
-
Region-based semantic segmentation with end-to-end training-2016
-
Exploring Context with Deep Structured models for Semantic Segmentation-2016
-
Better Image Segmentation by Exploiting Dense Semantic Predictions-2016
-
Boundary-aware Instance Segmentation-2016
-
Improving Fully Convolution Network for Semantic Segmentation-2016
-
Deep Structured Features for Semantic Segmentation-2016
-
Deep Learning Markov Random Field for Semantic Segmentation-2016
-
Convolutional Random Walk Networks for Semantic Image Segmentation-2016
-
ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation-2016
-
High-performance Semantic Segmentation Using Very Deep Fully Convolutional Networks-2016
-
ScribbleSup: Scribble-Supervised Convolutional Networks for Semantic Segmentation-2016
-
Object Boundary Guided Semantic Segmentation-2016
-
Segmentation from Natural Language Expressions-2016
-
Seed, Expand and Constrain: Three Principles for Weakly-Supervised Image Segmentation-2016
-
Global Deconvolutional Networks for Semantic Segmentation-2016
-
Semantic Image Segmentation With Deep Convolutional Nets and Fully Connected CRFs [caffe-m] [caffe-py]
- Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos, Kevin Murphy, Alan L. Yuille, ICLR/1412
- DeepLab
- Weakly- and Semi-Supervised Learning of a DCNN for Semantic Image Segmentation
- PAMI version, DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs
- cn
-
Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network-2015
-
Learning Dense Convolutional Embeddings for Semantic Segmentation-2015
-
ParseNet: Looking Wider to See Better-2015
-
Decoupled Deep Neural Network for Semi-supervised Semantic Segmentation [caffe] [nips, pdf]
- Seunghoon Hong, Hyeonwoo Noh, Bohyung Han, NIPS/1506
-
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation-2015
-
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Robust Semantic Pixel-Wise Labelling-2015
-
Semantic Image Segmentation with Task-Specific Edge Detection Using CNNs and a Discriminatively Trained Domain Transform-2015
-
Semantic Segmentation with Boundary Neural Fields-2015
-
Semantic Image Segmentation via Deep Parsing Network-2015
-
What’s the Point: Semantic Segmentation with Point Supervision-2015
-
U-Net: Convolutional Networks for Biomedical Image Segmentation-2015 <Code+Data>
-
Learning Deconvolution Network for Semantic Segmentation(DeconvNet)-2015
-
Multi-scale Context Aggregation by Dilated Convolutions [caffe]
- Fisher Yu and Vladlen Koltun, ICLR/1511
- Dilated Residual Networks
-
ReSeg: A Recurrent Neural Network-based Model for Semantic Segmentation-2015
-
BoxSup: Exploiting Bounding Boxes to Supervise Convolutional Networks for Semantic Segmentation-2015
-
Feedforward semantic segmentation with zoom-out features-2015
-
Conditional Random Fields as Recurrent Neural Networks-2015
-
Efficient Piecewise Training of Deep Structured Models for Semantic Segmentation-2015
-
Fully Convolutional Networks for Semantic Segmentation-2015
-
Deep Joint Task Learning for Generic Object Extraction -2014
-
Highly Efficient Forward and Backward Propagation of Convolutional Neural Networks for Pixelwise Classification -2014
-
Rich feature hierarchies for accurate object detection and semantic segmentation [caffe]
- R-CNN
- Ross Girshick, Jeff Donahue, Trevor Darrell, Jitendra Malik, CVPR 14/arxiv 1311
- Panoptic Segmentation - 2018
- Macro-Micro Adversarial Network for Human Parsing - ECCV2018
- Holistic, Instance-level Human Parsing - 2017
- Semi-Supervised Hierarchical Semantic Object Parsing - 2017
- Towards Real World Human Parsing: Multiple-Human Parsing in the Wild - 2017
- Look into Person: Self-supervised Structure-sensitive Learning and A New Benchmark for Human Parsing-2017
- Efficient and Robust Deep Networks for Semantic Segmentation - 2017
- Face Parsing via Recurrent Propagation
- Sifei Liu, Jianping Shi, Ji Liang, Ming-Hsuan Yang, BMVC
- Deep Learning for Human Part Discovery in Images-2016
- A CNN Cascade for Landmark Guided Semantic Part Segmentation-2016
- Deep Learning for Semantic Part Segmentation With High-level Guidance-2015
- Neural Activation Constellations-Unsupervised Part Model Discovery with Convolutional Networks-2015
- Human Parsing with Contextualized Convolutional Neural Network-2015
- Part detector discovery in deep convolutional neural networks-2014
- Looking at Outfit to Parse Clothing-2017
- Semantic Object Parsing with Local-Global Long Short-Term Memory-2015
- A High Performance CRF Model for Clothes Parsing-2014
- Clothing co-parsing by joint image segmentation and labeling-2013
- Parsing clothing in fashion photographs-2012
- Bayesian Semantic Instance Segmentation in Open Set World
- Trung Pham, Vijay Kumar B. G., Thanh-Toan Do, Gustavo Carneiro, Ian Reid, ECCV/18
- A Pyramid CNN for Dense-Leaves Segmentation - 2018
- Predicting Future Instance Segmentations by Forecasting Convolutional Features - 2018
- Path Aggregation Network for Instance Segmentation - CVPR2018
- PixelLink: Detecting Scene Text via Instance Segmentation - AAAI2018
- MaskLab: Instance Segmentation by Refining Object Detection with Semantic and Direction Features - 2017 - google
- Recurrent Neural Networks for Semantic Instance Segmentation-2017
- Pixelwise Instance Segmentation with a Dynamically Instantiated Network-2017
- Semantic Instance Segmentation via Deep Metric Learning-2017
- Mask R-CNN-2017
- Pose2Instance: Harnessing Keypoints for Person Instance Segmentation-2017
- Pixelwise Instance Segmentation with a Dynamically Instantiated Network-2017
- Semantic Instance Segmentation with a Discriminative Loss Function-2017
- Fully Convolutional Instance-aware Semantic Segmentation-2016
- End-to-End Instance Segmentation with Recurrent Attention
- Instance-aware Semantic Segmentation via Multi-task Network Cascades-2015
- Recurrent Instance Segmentation-2015
- FastMask: Segment Object Multi-scale Candidates in One Shot-2016
- Learning to Refine Object Segments-2016
- Learning to Segment Object Candidates-2015
- Pixel Objectness-2017
- A Deep Convolutional Neural Network for Background Subtraction-2017