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Mamba has shown great potential for computer vision due to its linear complexity in modeling the global context with respect to the input length.
Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Long Short-Term Memory , pages 37–45
Alex Graves · 2012
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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
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Very deep convolutional networks for large-scale image recognition, 2015
Karen Simonyan and Andrew Zisserman · 2015
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Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding, 2016
Song Han, Huizi Mao, and William J. Dally · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Understanding the effective receptive field in deep convolutional neural networks
Wenjie Luo, Yujia Li, Raquel Urtasun, and Richard Zemel · 2016
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Mask r-cnn
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick · 2017
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Mobilenets: Efficient convolutional neural networks for mobile vision applications, 2017
Andrew G. Howard, Menglong Zhu, Bo Chen, Dmitry Kalenichenko, Weijun Wang, Tobias Weyand, Marco Andreetto, and Hartwig Adam · 2017
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Scene parsing through ade20k dataset
Bolei Zhou, Hang Zhao, Xavier Puig, Sanja Fidler, Adela Barriuso, and Antonio Torralba · 2017
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Shufflenet v2: Practical guidelines for efficient cnn architecture design
Ningning Ma, Xiangyu Zhang, Hai-Tao Zheng, and Jian Sun · 2018
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Mobilenetv2: Inverted residuals and linear bottlenecks
Mark Sandler, Andrew Howard, Menglong Zhu, Andrey Zhmoginov, and Liang-Chieh Chen · 2018
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Shufflenet: An extremely efficient convolutional neural network for mobile devices
Xiangyu Zhang, Xinyu Zhou, Mengxiao Lin, and Jian Sun · 2018
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Searching for mobilenetv3
Andrew Howard, Mark Sandler, Grace Chu, Liang-Chieh Chen, Bo Chen, Mingxing Tan, Weijun Wang, Yukun Zhu, Ruoming Pang, Vijay Vasudevan, Quoc V. Le, and Hartwig Adam · 2019
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Panoptic feature pyramid networks
Alexander Kirillov, Ross Girshick, Kaiming He, and Piotr Dollár · 2019
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Espnetv2: A light-weight, power efficient, and general purpose convolutional neural network
Sachin Mehta, Mohammad Rastegari, Linda Shapiro, and Hannaneh Hajishirzi · 2019
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On network design spaces for visual recognition
Ilija Radosavovic, Justin Johnson, Saining Xie, Wan-Yen Lo, and Piotr Dollar · 2019
Cited alongside, same era.
An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2020
Cited alongside, same era.
Hippo: Recurrent memory with optimal polynomial projections
Albert Gu, Tri Dao, Stefano Ermon, Atri Rudra, and Christopher Ré · 2020
Cited alongside, same era.
Ghostnet: More features from cheap operations
Kai Han, Yunhe Wang, Qi Tian, Jianyuan Guo, Chunjing Xu, and Chang Xu · 2020
Cited alongside, same era.
Scaling up your kernels to 31x31: Revisiting large kernel design in cnns
Xiaohan Ding, Xiangyu Zhang, Jungong Han, and Guiguang Ding · 2022
Cited alongside, same era.
Mamba: Linear-time sequence modeling with selective state spaces
Albert Gu and Tri Dao · 2023
Later among the works it cites.
Rethinking vision transformers for mobilenet size and speed
Yanyu Li, Ju Hu, Yang Wen, Georgios Evangelidis, Kamyar Salahi, Yanzhi Wang, Sergey Tulyakov, and Jian Ren · 2023
Later among the works it cites.
Swiftformer: Efficient additive attention for transformer-based real-time mobile vision applications
Abdelrahman Shaker, Muhammad Maaz, Hanoona Rasheed, Salman Khan, Ming-Hsuan Yang, and Fahad Shahbaz Khan · 2023
Later among the works it cites.
Can biases in imagenet models explain generalization?
Paul Gavrikov and Janis Keuper · 2024
Closest in time.
Mobilemamba: Lightweight multi-receptive visual mamba network, 2024
Haoyang He, Jiangning Zhang, Yuxuan Cai, Hongxu Chen, Xiaobin Hu, Zhenye Gan, Yabiao Wang, Chengjie Wang, Yunsheng Wu, and Lei Xie · 2024
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Daniel Y Fu, Tri Dao, Khaled K Saab, Armin W Thomas, Atri Rudra, and Christopher Ré · 2022
Cited alongside, same era.
Imagenet-trained cnns are biased towards texture; increasing shape bias improves accuracy and robustness, 2022
Robert Geirhos, Patricia Rubisch, Claudio Michaelis, Matthias Bethge, Felix A. Wichmann, and Wieland Brendel · 2022
Cited alongside, same era.
On the parameterization and initialization of diagonal state space models
Albert Gu, Karan Goel, Ankit Gupta, and Christopher Ré · 2022
Cited alongside, same era.
Diagonal state spaces are as effective as structured state spaces
Ankit Gupta, Albert Gu, and Jonathan Berant · 2022
Cited alongside, same era.
Liquid structural state-space models
Ramin Hasani, Mathias Lechner, Tsun-Hsuan Wang, Makram Chahine, Alexander Amini, and Daniela Rus · 2022
Cited alongside, same era.
Efficientformer: Vision transformers at mobilenet speed
Yanyu Li, Geng Yuan, Yang Wen, Ju Hu, Georgios Evangelidis, Sergey Tulyakov, Yanzhi Wang, and Jian Ren · 2022
Cited alongside, same era.
Mega: moving average equipped gated attention
Xuezhe Ma, Chunting Zhou, Xiang Kong, Junxian He, Liangke Gui, Graham Neubig, Jonathan May, and Luke Zettlemoyer · 2022
Cited alongside, same era.
Localmamba: Visual state space model with windowed selective scan, 2024
Tao Huang, Xiaohuan Pei, Shan You, Fei Wang, Chen Qian, and Chang Xu · 2024
Closest in time.
Fouriermamba: Fourier learning integration with state space models for image deraining, 2024
Dong Li, Yidi Liu, Xueyang Fu, Senyan Xu, and Zheng-Jun Zha · 2024
Closest in time.
Vmamba: Visual state space model
Yue Liu, Yunjie Tian, Yuzhong Zhao, Hongtian Yu, Lingxi Xie, Yaowei Wang, Qixiang Ye, and Yunfan Liu · 2024
Closest in time.
Efficientvmamba: Atrous selective scan for light weight visual mamba, 2024
Xiaohuan Pei, Tao Huang, and Chang Xu · 2024
Closest in time.
Vl-mamba: Exploring state space models for multimodal learning, 2024
Yanyuan Qiao, Zheng Yu, Longteng Guo, Sihan Chen, Zijia Zhao, Mingzhen Sun, Qi Wu, and Jing Liu · 2024
Closest in time.
Multi-scale vmamba: Hierarchy in hierarchy visual state space model
Yuheng Shi, Minjing Dong, and Chang Xu · 2024
Closest in time.
Repvit: Revisiting mobile cnn from vit perspective
Ao Wang, Hui Chen, Zijia Lin, Jungong Han, and Guiguang Ding · 2024
Closest in time.
Quadmamba: Learning quadtree-based selective scan for visual state space model, 2024
Fei Xie, Weijia Zhang, Zhongdao Wang, and Chao Ma · 2024
Closest in time.
Inceptionnext: When inception meets convnext
Weihao Yu, Pan Zhou, Shuicheng Yan, and Xinchao Wang · 2024
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Samba: Semantic segmentation of remotely sensed images with state space model, 2024
Qinfeng Zhu, Yuanzhi Cai, Yuan Fang, Yihan Yang, Cheng Chen, Lei Fan, and Anh Nguyen · 2024
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Agent attention: On the integration of softmax and linear attention
Dongchen Han, Tianzhu Ye, Yizeng Han, Zhuofan Xia, Siyuan Pan, Pengfei Wan, Shiji Song, and Gao Huang · 2025
Closest in time.