Fetching the paper…
Reading the bibliography…
The pixel-wise dense prediction tasks based on weakly supervisions currently use Class Attention Maps (CAM) to generate pseudo masks as ground-truth.
The pascal visual object classes (voc) challenge
Mark Everingham, Luc Van Gool, Christopher KI Williams, John Winn, and Andrew Zisserman · 2010
Earlier work this paper cites.
The caltech-ucsd birds-200-2011 dataset
Catherine Wah, Steve Branson, Peter Welinder, Pietro Perona, and Serge Belongie · 2011
Earlier work this paper cites.
Semantic contours from inverse detectors
Bharath Hariharan, Pablo Arbeláez, Lubomir Bourdev, Subhransu Maji, and Jitendra Malik · 2011
Earlier work this paper cites.
Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2014
Earlier work this paper cites.
Imagenet large scale visual recognition challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, et al · 2015
Earlier work this paper cites.
Boxsup: Exploiting bounding boxes to supervise convolutional networks for semantic segmentation
Jifeng Dai, Kaiming He, and Jian Sun · 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.
Learning deep features for discriminative localization
Bolei Zhou, Aditya Khosla, Agata Lapedriza, Aude Oliva, and Antonio Torralba · 2016
Earlier work this paper cites.
Rethinking the inception architecture for computer vision
Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jon Shlens, and Zbigniew Wojna · 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.
Seed, expand and constrain: Three principles for weakly-supervised image segmentation
Alexander Kolesnikov and Christoph H Lampert · 2016
Earlier work this paper cites.
Grad-cam: Visual explanations from deep networks via gradient-based localization
Ramprasaath R Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, and Dhruv Batra · 2017
Earlier work this paper cites.
Object region mining with adversarial erasing: A simple classification to semantic segmentation approach
Yunchao Wei, Jiashi Feng, Xiaodan Liang, Ming-Ming Cheng, Yao Zhao, and Shuicheng Yan · 2017
Earlier work this paper cites.
Improved regularization of convolutional neural networks with cutout
Terrance DeVries and Graham W Taylor · 2017
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.
Simple does it: Weakly supervised instance and semantic segmentation
Anna Khoreva, Rodrigo Benenson, Jan Hosang, Matthias Hein, and Bernt Schiele · 2017
Cited alongside, same era.
Adversarial complementary learning for weakly supervised object localization
Xiaolin Zhang, Yunchao Wei, Jiashi Feng, Yi Yang, and Thomas S Huang · 2018
Cited alongside, same era.
Grad-cam++: Generalized gradient-based visual explanations for deep convolutional networks
Aditya Chattopadhay, Anirban Sarkar, Prantik Howlader, and Vineeth N Balasubramanian · 2018
Cited alongside, same era.
Self-produced guidance for weakly-supervised object localization
Xiaolin Zhang, Yunchao Wei, Guoliang Kang, Yi Yang, and Thomas Huang · 2018
Cited alongside, same era.
Attention-based dropout layer for weakly supervised object localization
Junsuk Choe and Hyunjung Shim · 2019
Cited alongside, same era.
Rethinking localization map: Towards accurate object perception with self-enhancement maps
Xiaolin Zhang, Yunchao Wei, Yi Yang, and Fei Wu · 2020
Later among the works it cites.
Ss-cam: Smoothed score-cam for sharper visual feature localization
Haofan Wang, Rakshit Naidu, Joy Michael, and Soumya Snigdha Kundu · 2020
Later among the works it cites.
Random erasing data augmentation
Zhun Zhong, Liang Zheng, Guoliang Kang, Shaozi Li, and Yi Yang · 2020
Later among the works it cites.
Axiom-based grad-cam: Towards accurate visualization and explanation of cnns
Ruigang Fu, Qingyong Hu, Xiaohu Dong, Yulan Guo, Yinghui Gao, and Biao Li · 2020
Later among the works it cites.
Causal intervention for weakly-supervised semantic segmentation
Dong Zhang, Hanwang Zhang, Jinhui Tang, Xian-Sheng Hua, and Qianru Sun · 2020
Later among the works it cites.
Inter-image communication for weakly supervised localization
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Daniel Omeiza, Skyler Speakman, Celia Cintas, and Komminist Weldermariam · 2019
Cited alongside, same era.
Ficklenet: Weakly and semi-supervised semantic image segmentation using stochastic inference
Jungbeom Lee, Eunji Kim, Sungmin Lee, Jangho Lee, and Sungroh Yoon · 2019
Cited alongside, same era.
Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, et al · 2019
Cited alongside, same era.
Weakly supervised learning of instance segmentation with inter-pixel relations
Jiwoon Ahn, Sunghyun Cho, and Suha Kwak · 2019
Cited alongside, same era.
Cutmix: Regularization strategy to train strong classifiers with localizable features
Sangdoo Yun, Dongyoon Han, Seong Joon Oh, Sanghyuk Chun, Junsuk Choe, and Youngjoon Yoo · 2019
Cited alongside, same era.
Danet: Divergent activation for weakly supervised object localization
Haolan Xue, Chang Liu, Fang Wan, Jianbin Jiao, Xiangyang Ji, and Qixiang Ye · 2019
Cited alongside, same era.
Integral object mining via online attention accumulation
Peng-Tao Jiang, Qibin Hou, Yang Cao, Ming-Ming Cheng, Yunchao Wei, and Hong-Kai Xiong · 2019
Cited alongside, same era.
Xiaolin Zhang, Yunchao Wei, and Yi Yang · 2020
Later among the works it cites.
Erasing integrated learning: A simple yet effective approach for weakly supervised object localization
Jinjie Mai, Meng Yang, and Wenfeng Luo · 2020
Later among the works it cites.
Cian: Cross-image affinity net for weakly supervised semantic segmentation
Junsong Fan, Zhaoxiang Zhang, Tieniu Tan, Chunfeng Song, and Jun Xiao · 2020
Later among the works it cites.
Self-supervised equivariant attention mechanism for weakly supervised semantic segmentation
Yude Wang, Jie Zhang, Meina Kan, Shiguang Shan, and Xilin Chen · 2020
Later among the works it cites.
Mining cross-image semantics for weakly supervised semantic segmentation
Guolei Sun, Wenguan Wang, Jifeng Dai, and Luc Van Gool · 2020
Later among the works it cites.
Weakly-supervised semantic segmentation via sub-category exploration
Yu-Ting Chang, Qiaosong Wang, Wei-Chih Hung, Robinson Piramuthu, Yi-Hsuan Tsai, and Ming-Hsuan Yang · 2020
Later among the works it cites.
Group-cam: Group score-weighted visual explanations for deep convolutional networks
Qinglong Zhang, Lu Rao, and Yubin Yang · 2021
Closest in time.
Unveiling the potential of structure preserving for weakly supervised object localization
Xingjia Pan, Yingguo Gao, Zhiwen Lin, Fan Tang, Weiming Dong, Haolei Yuan, Feiyue Huang, and Changsheng Xu · 2021
Closest in time.
Online attention accumulation for weakly supervised semantic segmentation
Peng-Tao Jiang, Ling-Hao Han, Qibin Hou, Ming-Ming Cheng, and Yunchao Wei · 2021
Closest in time.