Fetching the paper…
Reading the bibliography…
In this paper, we study Multiscale Vision Transformers (MViTv2) as a unified architecture for image and video classification, as well as object detection.
Handwritten digit recognition with a back-propagation network
Yann LeCun, Bernhard Boser, John Denker, Donnie Henderson, Richard Howard, Wayne Hubbard, and Lawrence Jackel · 1989
Earlier work this paper cites.
Backpropagation applied to handwritten zip code recognition
Yann LeCun, Bernhard Boser, John S Denker, Donnie Henderson, Richard E Howard, Wayne Hubbard, and Lawrence D Jackel · 1989
Earlier work this paper cites.
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.
ImageNet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
Earlier work this paper cites.
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
Earlier work this paper cites.
Two-stream convolutional networks for action recognition in videos
Karen Simonyan and Andrew Zisserman · 2014
Earlier work this paper cites.
Fast R-CNN
Ross Girshick · 2015
Earlier work this paper cites.
Delving deep into rectifiers: Surpassing human-level performance on imagenet classification
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 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.
Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2015
Earlier work this paper cites.
Going deeper with convolutions
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2015
Earlier work this paper cites.
Rethinking the inception architecture for computer vision
Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jonathon Shlens, and Zbigniew Wojna · 2015
Earlier work this paper cites.
Spatiotemporal residual networks for video action recognition
Christoph Feichtenhofer, Axel Pinz, and Richard Wildes · 2016
Earlier work this paper cites.
Convolutional two-stream network fusion for video action recognition
Christoph Feichtenhofer, Axel Pinz, and Andrew Zisserman · 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.
Identity mappings in deep residual networks
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
Deep networks with stochastic depth
Gao Huang, Yu Sun, Zhuang Liu, Daniel Sedra, and Kilian Q Weinberger · 2016
Earlier work this paper cites.
SGDR: Stochastic gradient descent with warm restarts
Ilya Loshchilov and Frank Hutter · 2016
Earlier work this paper cites.
You only look once: Unified, real-time object detection
Joseph Redmon, Santosh Divvala, Ross Girshick, and Ali Farhadi · 2016
Earlier work this paper cites.
Soft-nms–improving object detection with one line of code
Navaneeth Bodla, Bharat Singh, Rama Chellappa, and Larry S Davis · 2017
Earlier work this paper cites.
Quo vadis, action recognition? a new model and the kinetics dataset
Joao Carreira and Andrew Zisserman · 2017
Earlier work this paper cites.
Accurate, large minibatch SGD: training ImageNet in 1 hour
Priya Goyal, Piotr Dollár, Ross Girshick, Pieter Noordhuis, Lukasz Wesolowski, Aapo Kyrola, Andrew Tulloch, Yangqing Jia, and Kaiming He · 2017
Earlier work this paper cites.
The “Something Something” video database for learning and evaluating visual common sense
Raghav Goyal, Samira Ebrahimi Kahou, Vincent Michalski, Joanna Materzynska, Susanne Westphal, Heuna Kim, Valentin Haenel, Ingo Fruend, Peter Yianilos, Moritz Mueller-Freitag, et al · 2017
Earlier work this paper cites.
Mask R-CNN
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick · 2017
Earlier work this paper cites.
The kinetics human action video dataset
Will Kay, Joao Carreira, Karen Simonyan, Brian Zhang, Chloe Hillier, Sudheendra Vijayanarasimhan, Fabio Viola, Tim Green, Trevor Back, Paul Natsev, et al · 2017
Earlier work this paper cites.
Feature pyramid networks for object detection
Tsung-Yi Lin, Piotr Dollár, Ross Girshick, Kaiming He, Bharath Hariharan, and Serge Belongie · 2017
Earlier work this paper cites.
Learning spatio-temporal representation with pseudo-3d residual networks
Zhaofan Qiu, Ting Yao, and Tao Mei · 2017
Earlier work this paper cites.
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
Earlier work this paper cites.
Aggregated residual transformations for deep neural networks
Saining Xie, Ross Girshick, Piotr Dollár, Zhuowen Tu, and Kaiming He · 2017
Earlier work this paper cites.
Rethinking spatiotemporal feature learning for video understanding
Saining Xie, Chen Sun, Jonathan Huang, Zhuowen Tu, and Kevin Murphy · 2017
Earlier work this paper cites.
Cascade r-cnn: Delving into high quality object detection
Zhaowei Cai and Nuno Vasconcelos · 2018
Earlier work this paper cites.
AVA: A video dataset of spatio-temporally localized atomic visual actions
Chunhui Gu, Chen Sun, David A. Ross, Carl Vondrick, Caroline Pantofaru, Yeqing Li, Sudheendra Vijayanarasimhan, George Toderici, Susanna Ricco, Rahul Sukthankar, Cordelia Schmid, and Jitendra Malik · 2018
Cited alongside, same era.
How to start training: The effect of initialization and architecture
Boris Hanin and David Rolnick · 2018
Cited alongside, same era.
VideoLSTM convolves, attends and flows for action recognition
Zhenyang Li, Kirill Gavrilyuk, Efstratios Gavves, Mihir Jain, and Cees GM Snoek · 2018
Cited alongside, same era.
Fixing weight decay regularization in adam
Ilya Loshchilov and Frank Hutter · 2018
Cited alongside, same era.
Self-attention with relative position representations
Peter Shaw, Jakob Uszkoreit, and Ashish Vaswani · 2018
Cited alongside, same era.
Random erasing data augmentation
Zhun Zhong, Liang Zheng, Guoliang Kang, Shaozi Li, and Yi Yang · 2020
Later among the works it cites.
Vivit: A video vision transformer
Anurag Arnab, Mostafa Dehghani, Georg Heigold, Chen Sun, Mario Lučić, and Cordelia Schmid · 2021
Closest in time.
Is space-time attention all you need for video understanding?
Gedas Bertasius, Heng Wang, and Lorenzo Torresani · 2021
Closest in time.
High-performance large-scale image recognition without normalization
Andrew Brock, Soham De, Samuel L Smith, and Karen Simonyan · 2021
Closest in time.
Crossvit: Cross-attention multi-scale vision transformer for image classification
Chun-Fu Chen, Quanfu Fan, and Rameswar Panda · 2021
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Mixup: Beyond empirical risk minimization
Hongyi Zhang, Moustapha Cisse, Yann N Dauphin, and David Lopez-Paz · 2018
Cited alongside, same era.
Temporal relational reasoning in videos
Bolei Zhou, Alex Andonian, Aude Oliva, and Antonio Torralba · 2018
Cited alongside, same era.
A short note on the kinetics-700 human action dataset
João Carreira, Eric Noland, Chloe Hillier, and Andrew Zisserman · 2019
Cited alongside, same era.
Drop an octave: Reducing spatial redundancy in convolutional neural networks with octave convolution
Yunpeng Chen, Haoqi Fang, Bing Xu, Zhicheng Yan, Yannis Kalantidis, Marcus Rohrbach, Shuicheng Yan, and Jiashi Feng · 2019
Cited alongside, same era.
SlowFast networks for video recognition
Christoph Feichtenhofer, Haoqi Fan, Jitendra Malik, and Kaiming He · 2019
Cited alongside, same era.
Nas-fpn: Learning scalable feature pyramid architecture for object detection
Golnaz Ghiasi, Tsung-Yi Lin, and Quoc V Le · 2019
Cited alongside, same era.
Video action transformer network
Rohit Girdhar, Joao Carreira, Carl Doersch, and Andrew Zisserman · 2019
Cited alongside, same era.
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
Closest in time.
Coatnet: Marrying convolution and attention for all data sizes
Zihang Dai, Hanxiao Liu, Quoc V Le, and Mingxing Tan · 2021
Closest in time.
Fast and accurate model scaling
Piotr Dollár, Mannat Singh, and Ross Girshick · 2021
Closest in time.
Cswin transformer: A general vision transformer backbone with cross-shaped windows
Xiaoyi Dong, Jianmin Bao, Dongdong Chen, Weiming Zhang, Nenghai Yu, Lu Yuan, Dong Chen, and Baining Guo · 2021
Closest in time.
Xcit: Cross-covariance image transformers
Alaaeldin El-Nouby, Hugo Touvron, Mathilde Caron, Piotr Bojanowski, Matthijs Douze, Armand Joulin, Ivan Laptev, Natalia Neverova, Gabriel Synnaeve, Jakob Verbeek, et al · 2021
Closest in time.
PyTorchVideo: A deep learning library for video understanding
Haoqi Fan, Tullie Murrell, Heng Wang, Kalyan Vasudev Alwala, Yanghao Li, Yilei Li, Bo Xiong, Nikhila Ravi, Meng Li, Haichuan Yang, Jitendra Malik, Ross Girshick, Matt Feiszli, Aaron Adcock, Wan-Yen Lo, and Christoph Feichtenhofer · 2021
Closest in time.
Multiscale vision transformers
Haoqi Fan, Bo Xiong, Karttikeya Mangalam, Yanghao Li, Zhicheng Yan, Jitendra Malik, and Christoph Feichtenhofer · 2021
Closest in time.
Simple copy-paste is a strong data augmentation method for instance segmentation
Golnaz Ghiasi, Yin Cui, Aravind Srinivas, Rui Qian, Tsung-Yi Lin, Ekin D Cubuk, Quoc V Le, and Barret Zoph · 2021
Closest in time.
Transformer in transformer
Kai Han, An Xiao, Enhua Wu, Jianyuan Guo, Chunjing Xu, and Yunhe Wang · 2021
Closest in time.
Token labeling: Training a 85.5% top-1 accuracy vision transformer with 56m parameters on imagenet
Zihang Jiang, Qibin Hou, Li Yuan, Daquan Zhou, Xiaojie Jin, Anran Wang, and Jiashi Feng · 2021
Closest in time.
MoViNets: Mobile video networks for efficient video recognition
Dan Kondratyuk, Liangzhe Yuan, Yandong Li, Li Zhang, Mingxing Tan, Matthew Brown, and Boqing Gong · 2021
Closest in time.
Benchmarking detection transfer learning with vision transformers
Yanghao Li, Saining Xie, Xinlei Chen, Piotr Dollar, Kaiming He, and Ross Girshick · 2021
Closest in time.
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
Closest in time.
Ze Liu, Jia Ning, Yue Cao, Yixuan Wei, Zheng Zhang, Stephen Lin, and Han Hu · 2021
Closest in time.
Daniel Neimark, Omri Bar, Maya Zohar, and Dotan Asselmann · 2021
Closest in time.
Actor-context-actor relation network for spatio-temporal action localization
Junting Pan, Siyu Chen, Mike Zheng Shou, Yu Liu, Jing Shao, and Hongsheng Li · 2021
Closest in time.
Segmenter: Transformer for semantic segmentation
Robin Strudel, Ricardo Garcia, Ivan Laptev, and Cordelia Schmid · 2021
Closest in time.
Going deeper with image transformers
Hugo Touvron, Matthieu Cord, Alexandre Sablayrolles, Gabriel Synnaeve, and Hervé Jégou · 2021
Closest in time.
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
Closest in time.
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
Closest in time.
Towards long-form video understanding
Chao-Yuan Wu and Philipp Krahenbuhl · 2021
Closest in time.
Cvt: Introducing convolutions to vision transformers
Haiping Wu, Bin Xiao, Noel Codella, Mengchen Liu, Xiyang Dai, Lu Yuan, and Lei Zhang · 2021
Closest in time.
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 E.H. Tay, Jiashi Feng, and Shuicheng Yan · 2021
Closest in time.
Volo: Vision outlooker for visual recognition, 2021
Li Yuan, Qibin Hou, Zihang Jiang, Jiashi Feng, and Shuicheng Yan · 2021
Closest in time.
Multi-scale vision longformer: A new vision transformer for high-resolution image encoding
Pengchuan Zhang, Xiyang Dai, Jianwei Yang, Bin Xiao, Lu Yuan, Lei Zhang, and Jianfeng Gao · 2021
Closest in time.
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
Closest in time.