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Semantic segmentation arises as the backbone of many vision systems, spanning from self-driving cars and robot navigation to augmented reality and teleconferencing.
ImageNet: A Large-Scale Hierarchical Image Database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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The Pascal Visual Object Classes (VOC) Challenge
Mark Everingham, Luc Van Gool, Christopher KI Williams, John Winn, and Andrew Zisserman · 2010
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Semantic Contours from Inverse Detectors
Bharath Hariharan, Pablo Arbeláez, Lubomir Bourdev, Subhransu Maji, and Jitendra Malik · 2011
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Distilling the Knowledge in a Neural Network
Geoffrey Hinton, Oriol Vinyals, and Jeff Dean · 2014
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Microsoft COCO: Common Objects in Context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
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Fully Convolutional Networks for Semantic Segmentation
Jonathan Long, Evan Shelhamer, and Trevor Darrell · 2015
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Learning Deconvolution Network for Semantic Segmentation
Hyeonwoo Noh, Seunghoon Hong, and Bohyung Han · 2015
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U-Net: Convolutional Networks for Biomedical Image Segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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Going Deeper with Convolutions
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2015
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Laplacian pyramid reconstruction and refinement for semantic segmentation
Golnaz Ghiasi and Charless C Fowlkes · 2016
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Deep Residual Learning for Image Recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Semantic Segmentation using Adversarial Networks
Pauline Luc, Camille Couprie, Soumith Chintala, and Jakob Verbeek · 2016
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BranchyNet: Fast Inference via Early Exiting from Deep Neural Networks
Surat Teerapittayanon, Bradley McDanel, and Hsiang-Tsung Kung · 2016
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Multi-Scale Context Aggregation by Dilated Convolutions
Fisher Yu and Vladlen Koltun · 2016
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SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
Vijay Badrinarayanan, Alex Kendall, and Roberto Cipolla · 2017
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Adaptive Neural Networks for Efficient Inference
Tolga Bolukbasi, Joseph Wang, Ofer Dekel, and Venkatesh Saligrama · 2017
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DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs
Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos, Kevin Murphy, and Alan L Yuille · 2017
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Rethinking Atrous Convolution for Semantic Image Segmentation
Liang-Chieh Chen, George Papandreou, Florian Schroff, and Hartwig Adam · 2017
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Spatially Adaptive Computation Time for Residual Networks
Michael Figurnov, Maxwell D Collins, Yukun Zhu, Li Zhang, Jonathan Huang, Dmitry Vetrov, and Ruslan Salakhutdinov · 2017
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On Calibration of Modern Neural Networks
Chuan Guo, Geoff Pleiss, Yu Sun, and Kilian Q. Weinberger · 2017
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Densely Connected Convolutional Networks
Gao Huang, Zhuang Liu, Laurens Van Der Maaten, and Kilian Q Weinberger · 2017
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Not All Pixels Are Equal: Difficulty-aware Semantic Segmentation via Deep Layer Cascade
Xiaoxiao Li, Ziwei Liu, Ping Luo, Chen Change Loy, and Xiaoou Tang · 2017
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Refinenet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation
Guosheng Lin, Anton Milan, Chunhua Shen, and Ian Reid · 2017
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Runtime Neural Pruning
Ji Lin, Yongming Rao, Jiwen Lu, and Jie Zhou · 2017
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SemanticFusion: Dense 3D Semantic Mapping with Convolutional Neural Networks
John McCormac, Ankur Handa, Andrew Davison, and Stefan Leutenegger · 2017
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Large Kernel Matters–Improve Semantic Segmentation by Global Convolutional Network
Chao Peng, Xiangyu Zhang, Gang Yu, Guiming Luo, and Jian Sun · 2017
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End-to-end learning of driving models from large-scale video datasets
Huazhe Xu, Yang Gao, Fisher Yu, and Trevor Darrell · 2017
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Dilated Residual Networks
Fisher Yu, Vladlen Koltun, and Thomas Funkhouser · 2017
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Pyramid Scene Parsing Network
Hengshuang Zhao, Jianping Shi, Xiaojuan Qi, Xiaogang Wang, and Jiaya Jia · 2017
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Searching for efficient multi-scale architectures for dense image prediction
Liang-Chieh Chen, Maxwell Collins, Yukun Zhu, George Papandreou, Barret Zoph, Florian Schroff, Hartwig Adam, and Jon Shlens · 2018
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Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
Liang-Chieh Chen, Yukun Zhu, George Papandreou, Florian Schroff, and Hartwig Adam · 2018
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NestDNN: Resource-Aware Multi-Tenant On-Device Deep Learning for Continuous Mobile Vision
Structured Knowledge Distillation for Semantic Segmentation
Yifan Liu, Ke Chen, Chris Liu, Zengchang Qin, Zhenbo Luo, and Jingdong Wang · 2019
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MSD: Multi-Self-Distillation Learning via Multi-classifiers within Deep Neural Networks
Yunteng Luan, Hanyu Zhao, Zhi Yang, and Yafei Dai · 2019
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Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells
Vladimir Nekrasov, Hao Chen, Chunhua Shen, and Ian Reid · 2019
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Distillation-based Training for Multi-Exit Architectures
Mary Phuong and Christoph H Lampert · 2019
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ADVENT: Adversarial Entropy Minimization for Domain Adaptation in Semantic Segmentation
Tuan-Hung Vu, Himalaya Jain, Maxime Bucher, Matthieu Cord, and Patrick Pérez · 2019
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Biyi Fang, Xiao Zeng, and Mi Zhang · 2018
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Multi-Scale Dense Networks for Resource Efficient Image Classification
Gao Huang, Danlu Chen, Tianhong Li, Felix Wu, Laurens van der Maaten, and Kilian Weinberger · 2018
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ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation
Sachin Mehta, Mohammad Rastegari, Anat Caspi, Linda Shapiro, and Hannaneh Hajishirzi · 2018
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MobileNetV2: Inverted Residuals and Linear Bottlenecks
Mark Sandler, Andrew Howard, Menglong Zhu, Andrey Zhmoginov, and Liang-Chieh Chen · 2018
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A Comparative Study of Real-Time Semantic Segmentation for Autonomous Driving
Mennatullah Siam, Mostafa Gamal, Moemen Abdel-Razek, Senthil Yogamani, Martin Jagersand, and Hong Zhang · 2018
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Convolutional Networks with Adaptive Inference Graphs
Andreas Veit and Serge Belongie · 2018
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SkipNet: Learning Dynamic Routing in Convolutional Networks
Xin Wang, Fisher Yu, Zi-Yi Dou, Trevor Darrell, and Joseph E Gonzalez · 2018
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Huikai Wu, Junge Zhang, Kaiqi Huang, Kongming Liang, and Yu Yizhou · 2019
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Demystifying Learning Rate Policies for High Accuracy Training of Deep Neural Networks
Yanzhao Wu, Ling Liu, Juhyun Bae, Ka-Ho Chow, Arun Iyengar, Calton Pu, Wenqi Wei, Lei Yu, and Qi Zhang · 2019
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Balanced Sparsity for Efficient DNN Inference on GPU
Zhuliang Yao, Shijie Cao, Wencong Xiao, Chen Zhang, and Lanshun Nie · 2019
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Be your Own Teacher: Improve the Performance of Convolutional Neural Networks via Self Distillation
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SCAN: A Scalable Neural Networks Framework Towards Compact and Efficient Models
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Edge Intelligence: Paving the Last Mile of Artificial Intelligence with Edge Computing
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Resource Efficient Domain Adaptation
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SPINN: Synergistic Progressive Inference of Neural Networks over Device and Cloud
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HAPI: Hardware-Aware Progressive Inference
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Learning Dynamic Routing for Semantic Segmentation
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Dynamic Network Pruning with Interpretable Layerwise Channel Selection
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DeeBERT: Dynamic Early Exiting for Accelerating BERT Inference
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Early Exit Or Not: Resource-Efficient Blind Quality Enhancement for Compressed Images
Qunliang Xing, Mai Xu, Tianyi Li, and Zhenyu Guan · 2020
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Heimdall: Mobile GPU Coordination Platform for Augmented Reality Applications
Juheon Yi and Youngki Lee · 2020
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S2DNAS: Transforming Static CNN Model for Dynamic Inference via Neural Architecture Search
Zhihang Yuan, Bingzhe Wu, Zheng Liang, Shiwan Zhao, Weichen Bi, and Guangyu Sun · 2020
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Fast Bi-layer Neural Synthesis of One-Shot Realistic Head Avatars
E. Zakharov, Aleksei Ivakhnenko, Aliaksandra Shysheya, and V. Lempitsky · 2020
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Towards Cardiac Intervention Assistance: Hardware-aware Neural Architecture Exploration for Real-Time 3D Cardiac Cine MRI Segmentation
Dewen Zeng, Weiwen Jiang, Tianchen Wang, Xiaowei Xu, Haiyun Yuan, Meiping Huang, Jian Zhuang, Jingtong Hu, and Yiyu Shi · 2020
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Adaptive Inference through Early-Exit Networks: Design, Challenges and Directions
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