Fetching the paper…
Reading the bibliography…
Fine-Grained Visual Classification(FGVC) is the task that requires recognizing the objects belonging to multiple subordinate categories of a super-category.
Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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.
3d object representations for fine-grained categorization
Jonathan Krause, Michael Stark, Jia Deng, and Li Fei-Fei · 2013
Earlier work this paper cites.
Fine-grained visual classification of aircraft
Subhransu Maji, Esa Rahtu, Juho Kannala, Matthew Blaschko, and Andrea Vedaldi · 2013
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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.
Building a bird recognition app and large scale dataset with citizen scientists: The fine print in fine-grained dataset collection
Grant Van Horn, Steve Branson, Ryan Farrell, Scott Haber, Jessie Barry, Panos Ipeirotis, Pietro Perona, and Serge Belongie · 2015
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.
Look closer to see better: Recurrent attention convolutional neural network for fine-grained image recognition
Jianlong Fu, Heliang Zheng, and Tao Mei · 2017
Earlier work this paper cites.
Fine-grained image classification via combining vision and language
Xiangteng He and Yuxin Peng · 2017
Earlier work this paper cites.
The inaturalist challenge 2017 dataset
Grant Van Horn, Oisin Mac Aodha, Yang Song, Alexander Shepard, Hartwig Adam, Pietro Perona, and Serge Belongie · 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.
Learning multi-attention convolutional neural network for fine-grained image recognition
Heliang Zheng, Jianlong Fu, Tao Mei, and Jiebo Luo · 2017
Earlier work this paper cites.
Knowledge-embedded representation learning for fine-grained image recognition
Tianshui Chen, Liang Lin, Riquan Chen, Yang Wu, and Xiaonan Luo · 2018
Earlier work this paper cites.
Large scale fine-grained categorization and domain-specific transfer learning
Yin Cui, Yang Song, Chen Sun, Andrew Howard, and Serge Belongie · 2018
Earlier work this paper cites.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
Earlier work this paper cites.
The inaturalist species classification and detection dataset
Grant Van Horn, Oisin Mac Aodha, Yang Song, Yin Cui, Chen Sun, Alex Shepard, Hartwig Adam, Pietro Perona, and Serge Belongie · 2018
Earlier work this paper cites.
Mask-cnn: Localizing parts and selecting descriptors for fine-grained bird species categorization
Xiu-Shen Wei, Chen-Wei Xie, Jianxin Wu, and Chunhua Shen · 2018
Earlier work this paper cites.
Learning to navigate for fine-grained classification
Ze Yang, Tiange Luo, Dong Wang, Zhiqiang Hu, Jun Gao, and Liwei Wang · 2018
Earlier work this paper cites.
Hierarchical bilinear pooling for fine-grained visual recognition
Chaojian Yu, Xinyi Zhao, Qi Zheng, Peng Zhang, and Xinge You · 2018
Cited alongside, same era.
Destruction and construction learning for fine-grained image recognition
Yue Chen, Yalong Bai, Wei Zhang, and Tao Mei · 2019
Cited alongside, same era.
Geo-aware networks for fine-grained recognition
Grace Chu, Brian Potetz, Weijun Wang, Andrew Howard, Yang Song, Fernando Brucher, Thomas Leung, and Hartwig Adam · 2019
Cited alongside, same era.
Selective sparse sampling for fine-grained image recognition
Yao Ding, Yanzhao Zhou, Yi Zhu, Qixiang Ye, and Jianbin Jiao · 2019
Cited alongside, same era.
Weakly supervised complementary parts models for fine-grained image classification from the bottom up
Weifeng Ge, Xiangru Lin, and Yizhou Yu · 2019
Cited alongside, same era.
Gpipe: Efficient training of giant neural networks using pipeline parallelism
Transtrack: Multiple-object tracking with transformer
Peize Sun, Yi Jiang, Rufeng Zhang, Enze Xie, Jinkun Cao, Xinting Hu, Tao Kong, Zehuan Yuan, Changhu Wang, and Ping Luo · 2020
Later among the works it cites.
Learning attentive pairwise interaction for fine-grained classification
Peiqin Zhuang, Yali Wang, and Yu Qiao · 2020
Later among the works it cites.
Context-aware attentional pooling (cap) for fine-grained visual classification
Ardhendu Behera, Zachary Wharton, Pradeep Hewage, and Asish Bera · 2021
Later among the works it cites.
Coatnet: Marrying convolution and attention for all data sizes
Zihang Dai, Hanxiao Liu, Quoc V Le, and Mingxing Tan · 2021
Later among the works it cites.
Convit: Improving vision transformers with soft convolutional inductive biases
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Yanping Huang, Youlong Cheng, Ankur Bapna, Orhan Firat, Dehao Chen, Mia Chen, HyoukJoong Lee, Jiquan Ngiam, Quoc V Le, Yonghui Wu, et al · 2019
Cited alongside, same era.
Cross-x learning for fine-grained visual categorization
Wei Luo, Xitong Yang, Xianjie Mo, Yuheng Lu, Larry S Davis, Jun Li, Jian Yang, and Ser-Nam Lim · 2019
Cited alongside, same era.
Presence-only geographical priors for fine-grained image classification
Oisin Mac Aodha, Elijah Cole, and Pietro Perona · 2019
Cited alongside, same era.
Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu · 2019
Cited alongside, same era.
Efficientnet: Rethinking model scaling for convolutional neural networks
Mingxing Tan and Quoc Le · 2019
Cited alongside, same era.
Fixing the train-test resolution discrepancy
Hugo Touvron, Andrea Vedaldi, Matthijs Douze, and Hervé Jégou · 2019
Cited alongside, same era.
Pytorch image models
Ross Wightman · 2019
Cited alongside, same era.
Stéphane d’Ascoli, Hugo Touvron, Matthew Leavitt, Ari Morcos, Giulio Biroli, and Levent Sagun · 2021
Later among the works it cites.
10,000 species recognition challenge with inaturalist data - fgvc8, 2021
Oisin Mac Aodha Grant Van Horn · 2021
Later among the works it cites.
Transfg: A transformer architecture for fine-grained recognition
Ju He, Jie-Neng Chen, Shuai Liu, Adam Kortylewski, Cheng Yang, Yutong Bai, Changhu Wang, and Alan Yuille · 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.
Trackformer: Multi-object tracking with transformers, 2021
Tim Meinhardt, Alexander Kirillov, Laura Leal-Taixe, and Christoph Feichtenhofer · 2021
Later among the works it cites.
Counterfactual attention learning for fine-grained visual categorization and re-identification
Yongming Rao, Guangyi Chen, Jiwen Lu, and Jie Zhou · 2021
Later among the works it cites.
Imagenet-21k pretraining for the masses
Tal Ridnik, Emanuel Ben-Baruch, Asaf Noy, and Lihi Zelnik-Manor · 2021
Later among the works it cites.
Sparse r-cnn: End-to-end object detection with learnable proposals
Peize Sun, Rufeng Zhang, Yi Jiang, Tao Kong, Chenfeng Xu, Wei Zhan, Masayoshi Tomizuka, Lei Li, Zehuan Yuan, Changhu Wang, et al · 2021
Later among the works it cites.
Efficientnetv2: Smaller models and faster training
Mingxing Tan and Quoc V Le · 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.
Grafit: Learning fine-grained image representations with coarse labels
Hugo Touvron, Alexandre Sablayrolles, Matthijs Douze, Matthieu Cord, and Hervé Jégou · 2021
Later among the works it cites.
Pvtv2: Improved baselines with pyramid vision transformer
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.
End-to-end video instance segmentation with transformers
Yuqing Wang, Zhaoliang Xu, Xinlong Wang, Chunhua Shen, Baoshan Cheng, Hao Shen, and Huaxia Xia · 2021
Later among the works it cites.
Seqformer: a frustratingly simple model for video instance segmentation
Junfeng Wu, Yi Jiang, Wenqing Zhang, Xiang Bai, and Song Bai · 2021
Later among the works it cites.
Rethinking semantic segmentation from a sequence-to-sequence perspective with transformers
Sixiao Zheng, Jiachen Lu, Hengshuang Zhao, Xiatian Zhu, Zekun Luo, Yabiao Wang, Yanwei Fu, Jianfeng Feng, Tao Xiang, Philip HS Torr, et al · 2021
Later among the works it cites.