Fetching the paper…
Reading the bibliography…
After the great success of Vision Transformer variants (ViTs) in computer vision, it has also demonstrated great potential in domain adaptive semantic segmentation.
Improving predictive inference under covariate shift by weighting the log-likelihood function
Hidetoshi Shimodaira · 2000
Earlier work this paper cites.
Co-training for domain adaptation
Minmin Chen, Kilian Q Weinberger, and John Blitzer · 2011
Earlier work this paper cites.
Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks
Dong-Hyun Lee et al · 2013
Earlier work this paper cites.
Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
Earlier work this paper cites.
The pascal visual object classes challenge: A retrospective
Mark Everingham, SM Ali Eslami, Luc Van Gool, Christopher KI Williams, John Winn, and Andrew Zisserman · 2015
Earlier work this paper cites.
Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, Jeff Dean, et al · 2015
Earlier work this paper cites.
Fully convolutional networks for semantic segmentation
Jonathan Long, Evan Shelhamer, and Trevor Darrell · 2015
Earlier work this paper cites.
Faster r-cnn: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2015
Earlier work this paper cites.
The cityscapes dataset for semantic urban scene understanding
Marius Cordts, Mohamed Omran, Sebastian Ramos, Timo Rehfeld, Markus Enzweiler, Rodrigo Benenson, Uwe Franke, Stefan Roth, and Bernt Schiele · 2016
Earlier work this paper cites.
Domain-adversarial training of neural networks
Yaroslav Ganin, Evgeniya Ustinova, Hana Ajakan, Pascal Germain, Hugo Larochelle, François Laviolette, Mario Marchand, and Victor Lempitsky · 2016
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
Fcns in the wild: Pixel-level adversarial and constraint-based adaptation, 2016
Judy Hoffman, Dequan Wang, Fisher Yu, and Trevor Darrell · 2016
Earlier work this paper cites.
Playing for data: Ground truth from computer games
Stephan R Richter, Vibhav Vineet, Stefan Roth, and Vladlen Koltun · 2016
Earlier work this paper cites.
The synthia dataset: A large collection of synthetic images for semantic segmentation of urban scenes
German Ros, Laura Sellart, Joanna Materzynska, David Vazquez, and Antonio M Lopez · 2016
Earlier work this paper cites.
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
Earlier work this paper cites.
No more discrimination: Cross city adaptation of road scene segmenters
Yi-Hsin Chen, Wei-Yu Chen, Yu-Ting Chen, Bo-Cheng Tsai, Yu-Chiang Frank Wang, and Min Sun · 2017
Earlier work this paper cites.
Adversarial discriminative domain adaptation
Eric Tzeng, Judy Hoffman, Kate Saenko, and Trevor Darrell · 2017
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
Earlier work this paper cites.
Pyramid scene parsing network
Hengshuang Zhao, Jianping Shi, Xiaojuan Qi, Xiaogang Wang, and Jiaya Jia · 2017
Cited alongside, same era.
Cycada: Cycle-consistent adversarial domain adaptation
Judy Hoffman, Eric Tzeng, Taesung Park, Jun-Yan Zhu, Phillip Isola, Kate Saenko, Alexei Efros, and Trevor Darrell · 2018
Cited alongside, same era.
Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2018
Cited alongside, same era.
Umap: Uniform manifold approximation and projection for dimension reduction
Leland McInnes, John Healy, and James Melville · 2018
Cited alongside, same era.
Learning to adapt structured output space for semantic segmentation
Yi-Hsuan Tsai, Wei-Chih Hung, Samuel Schulter, Kihyuk Sohn, Ming-Hsuan Yang, and Manmohan Chandraker · 2018
Cited alongside, same era.
Unified perceptual parsing for scene understanding
Fda: Fourier domain adaptation for semantic segmentation
Yanchao Yang and Stefano Soatto · 2020
Later among the works it cites.
Self-supervised augmentation consistency for adapting semantic segmentation
Nikita Araslanov and Stefan Roth · 2021
Later among the works it cites.
Twins: Revisiting the design of spatial attention in vision transformers
Xiangxiang Chu, Zhi Tian, Yuqing Wang, Bo Zhang, Haibing Ren, Xiaolin Wei, Huaxia Xia, and Chunhua Shen · 2021
Later among the works it cites.
Sotr: Segmenting objects with transformers
Ruohao Guo, Dantong Niu, Liao Qu, and Zhenbo Li · 2021
Later among the works it cites.
Metacorrection: Domain-aware meta loss correction for unsupervised domain adaptation in semantic segmentation
Xiaoqing Guo, Chen Yang, Baopu Li, and Yixuan Yuan · 2021
Later among the works it cites.
Demystifying local vision transformer: Sparse connectivity, weight sharing, and dynamic weight
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Tete Xiao, Yingcheng Liu, Bolei Zhou, Yuning Jiang, and Jian Sun · 2018
Cited alongside, same era.
Progressive feature alignment for unsupervised domain adaptation
Chaoqi Chen, Weiping Xie, Wenbing Huang, Yu Rong, Xinghao Ding, Yue Huang, Tingyang Xu, and Junzhou Huang · 2019
Cited alongside, same era.
Self-ensembling with gan-based data augmentation for domain adaptation in semantic segmentation
Jaehoon Choi, Taekyung Kim, and Changick Kim · 2019
Cited alongside, same era.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin Ming-Wei Chang Kenton and Lee Kristina Toutanova · 2019
Cited alongside, same era.
Bidirectional learning for domain adaptation of semantic segmentation
Yunsheng Li, Lu Yuan, and Nuno Vasconcelos · 2019
Cited alongside, same era.
Taking a closer look at domain shift: Category-level adversaries for semantics consistent domain adaptation
Yawei Luo, Liang Zheng, Tao Guan, Junqing Yu, and Yi Yang · 2019
Cited alongside, same era.
Not all areas are equal: Transfer learning for semantic segmentation via hierarchical region selection
Ruoqi Sun, Xinge Zhu, Chongruo Wu, Chen Huang, Jianping Shi, and Lizhuang Ma · 2019
Cited alongside, same era.
Qi Han, Zejia Fan, Qi Dai, Lei Sun, Ming-Ming Cheng, Jiaying Liu, and Jingdong Wang · 2021
Later among the works it cites.
Dynamic neural networks: A survey
Yizeng Han, Gao Huang, Shiji Song, Le Yang, Honghui Wang, and Yulin Wang · 2021
Later among the works it cites.
Dynamic transfer for multi-source domain adaptation
Yunsheng Li, Lu Yuan, Yinpeng Chen, Pei Wang, and Nuno Vasconcelos · 2021
Later among the works it cites.
Swin transformer: Hierarchical vision transformer using shifted windows
Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, and Baining Guo · 2021
Later among the works it cites.
Coarse-to-fine domain adaptive semantic segmentation with photometric alignment and category-center regularization
Haoyu Ma, Xiangru Lin, Zifeng Wu, and Yizhou Yu · 2021
Later among the works it cites.
Better supervisory signals by observing learning paths
Yi Ren, Shangmin Guo, and Danica J Sutherland · 2021
Later among the works it cites.
Training data-efficient image transformers & distillation through attention
Hugo Touvron, Matthieu Cord, Matthijs Douze, Francisco Massa, Alexandre Sablayrolles, and Hervé Jégou · 2021
Later among the works it cites.
Scaling local self-attention for parameter efficient visual backbones, 2021
Ashish Vaswani, Prajit Ramachandran, Aravind Srinivas, Niki Parmar, Blake Hechtman, and Jonathon Shlens · 2021
Later among the works it cites.
Pyramid vision transformer: A versatile backbone for dense prediction without convolutions
Wenhai Wang, Enze Xie, Xiang Li, Deng-Ping Fan, Kaitao Song, Ding Liang, Tong Lu, Ping Luo, and Ling Shao · 2021
Later among the works it cites.
Segformer: Simple and efficient design for semantic segmentation with transformers
Enze Xie, Wenhai Wang, Zhiding Yu, Anima Anandkumar, Jose M Alvarez, and Ping Luo · 2021
Later among the works it cites.
Tokens-to-token vit: Training vision transformers from scratch on imagenet
Li Yuan, Yunpeng Chen, Tao Wang, Weihao Yu, Yujun Shi, Zi-Hang Jiang, Francis EH Tay, Jiashi Feng, and Shuicheng Yan · 2021
Later among the works it cites.
Prototypical pseudo label denoising and target structure learning for domain adaptive semantic segmentation
Pan Zhang, Bo Zhang, Ting Zhang, Dong Chen, Yong Wang, and Fang Wen · 2021
Later among the works it cites.
Rectifying pseudo label learning via uncertainty estimation for domain adaptive semantic segmentation
Zhedong Zheng and Yi Yang · 2021
Later among the works it cites.