Fetching the paper…
Reading the bibliography…
Humans can naturally understand an image in depth with the aid of rich knowledge accumulated from daily lives or professions.
Beyond categories: The visual memex model for reasoning about object relationships
Tomasz Malisiewicz and Alyosha Efros · 2009
Earlier work this paper cites.
Random walk inference and learning in a large scale knowledge base
Ni Lao, Tom Mitchell, and William W Cohen · 2011
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.
Bird species categorization using pose normalized deep convolutional nets
Steve Branson, Grant Van Horn, Serge Belongie, and Pietro Perona · 2014
Earlier work this paper cites.
Recurrent models of visual attention
Volodymyr Mnih, Nicolas Heess, Alex Graves, et al · 2014
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.
Part-based r-cnns for fine-grained category detection
Ning Zhang, Jeff Donahue, Ross Girshick, and Trevor Darrell · 2014
Earlier work this paper cites.
Reasoning about object affordances in a knowledge base representation
Yuke Zhu, Alireza Fathi, and Li Fei-Fei · 2014
Earlier work this paper cites.
Convolutional networks on graphs for learning molecular fingerprints
David K Duvenaud, Dougal Maclaurin, Jorge Iparraguirre, Rafael Bombarell, Timothy Hirzel, Alán Aspuru-Guzik, and Ryan P Adams · 2015
Earlier work this paper cites.
Spatial transformer networks
Max Jaderberg, Karen Simonyan, Andrew Zisserman, et al · 2015
Earlier work this paper cites.
Fine-grained recognition without part annotations
Jonathan Krause, Hailin Jin, Jianchao Yang, and Li Fei-Fei · 2015
Earlier work this paper cites.
Gated graph sequence neural networks
Yujia Li, Daniel Tarlow, Marc Brockschmidt, and Richard Zemel · 2015
Earlier work this paper cites.
Deep lac: Deep localization, alignment and classification for fine-grained recognition
Di Lin, Xiaoyong Shen, Cewu Lu, and Jiaya Jia · 2015
Earlier work this paper cites.
Bilinear cnn models for fine-grained visual recognition
Tsung-Yu Lin, Aruni RoyChowdhury, and Subhransu Maji · 2015
Earlier work this paper cites.
Multiple granularity descriptors for fine-grained categorization
Dequan Wang, Zhiqiang Shen, Jie Shao, Wei Zhang, Xiangyang Xue, and Zheng Zhang · 2015
Cited alongside, same era.
The application of two-level attention models in deep convolutional neural network for fine-grained image classification
Tianjun Xiao, Yichong Xu, Kuiyuan Yang, Jiaxing Zhang, Yuxin Peng, and Zheng Zhang · 2015
Cited alongside, same era.
Disc: Deep image saliency computing via progressive representation learning
Tianshui Chen, Liang Lin, Lingbo Liu, Xiaonan Luo, and Xuelong Li · 2016
Cited alongside, same era.
Compact bilinear pooling
Yang Gao, Oscar Beijbom, Ning Zhang, and Trevor Darrell · 2016
Cited alongside, same era.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Cited alongside, same era.
Part-stacked cnn for fine-grained visual categorization
Weakly supervised learning of part selection model with spatial constraints for fine-grained image classification
Xiangteng He and Yuxin Peng · 2017
Later among the works it cites.
Low-rank bilinear pooling for fine-grained classification
Shu Kong and Charless Fowlkes · 2017
Later among the works it cites.
Situation recognition with graph neural networks
Ruiyu Li, Makarand Tapaswi, Renjie Liao, Jiaya Jia, Raquel Urtasun, and Sanja Fidler · 2017
Later among the works it cites.
Knowledge-guided recurrent neural network learning for task-oriented action prediction
Liang Lin, Lili Huang, Tianshui Chen, Yukang Gan, and Hui Cheng · 2017
Later among the works it cites.
Localizing by describing: Attribute-guided attention localization for fine-grained recognition
Xiao Liu, Jiang Wang, Shilei Wen, Errui Ding, and Yuanqing Lin · 2017
Later among the works it cites.
The more you know: Using knowledge graphs for image classification
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Shaoli Huang, Zhe Xu, Dacheng Tao, and Ya Zhang · 2016
Cited alongside, same era.
Semantic object parsing with graph lstm
Xiaodan Liang, Xiaohui Shen, Jiashi Feng, Liang Lin, and Shuicheng Yan · 2016
Cited alongside, same era.
Xiao Liu, Tian Xia, Jiang Wang, and Yuanqing Lin · 2016
Cited alongside, same era.
Learning convolutional neural networks for graphs
Mathias Niepert, Mohamed Ahmed, and Konstantin Kutzkov · 2016
Cited alongside, same era.
Spda-cnn: Unifying semantic part detection and abstraction for fine-grained recognition
Han Zhang, Tao Xu, Mohamed Elhoseiny, Xiaolei Huang, Shaoting Zhang, Ahmed Elgammal, and Dimitris Metaxas · 2016
Cited alongside, same era.
Picking deep filter responses for fine-grained image recognition
Xiaopeng Zhang, Hongkai Xiong, Wengang Zhou, Weiyao Lin, and Qi Tian · 2016
Cited alongside, same era.
Learning deep features for discriminative localization
Bolei Zhou, Aditya Khosla, Agata Lapedriza, Aude Oliva, and Antonio Torralba · 2016
Cited alongside, same era.
Kenneth Marino, Ruslan Salakhutdinov, and Abhinav Gupta · 2017
Later among the works it cites.
3d graph neural networks for rgbd semantic segmentation
Xiaojuan Qi, Renjie Liao, Jiaya Jia, Sanja Fidler, and Raquel Urtasun · 2017
Later among the works it cites.
Multi-label image recognition by recurrently discovering attentional regions
Zhouxia Wang, Tianshui Chen, Guanbin Li, Ruijia Xu, and Liang Lin · 2017
Later among the works it cites.
Diversified visual attention networks for fine-grained object classification
Bo Zhao, Xiao Wu, Jiashi Feng, Qiang Peng, and Shuicheng Yan · 2017
Later among the works it cites.
Learning multi-attention convolutional neural network for fine-grained image recognition
Heliang Zheng, Jianlong Fu, Tao Mei, and Jiebo Luo · 2017
Later among the works it cites.
Recurrent attentional reinforcement learning for multi-label image recognition
Tianshui Chen, Zhouxia Wang, Guanbin Li, and Liang Lin · 2018
Closest in time.
Crowd counting using deep recurrent spatial-aware network
Lingbo Liu, Hongjun Wang, Guanbin Li, Wanli Ouyang, and Liang Lin · 2018
Closest in time.
Object-part attention model for fine-grained image classification
Yuxin Peng, Xiangteng He, and Junjie Zhao · 2018
Closest in time.