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Combining CNNs or ViTs, with RNNs for spatiotemporal forecasting, has yielded unparalleled results in predicting temporal and spatial dynamics.
Recognizing human actions: a local svm approach
Christian Schuldt, Ivan Laptev, and Barbara Caputo · 2004
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Image quality assessment: from error visibility to structural similarity
Zhou Wang, Alan C Bovik, Hamid R Sheikh, and Eero P Simoncelli · 2004
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Convolutional lstm network: A machine learning approach for precipitation nowcasting
Xingjian Shi, Zhourong Chen, Hao Wang, Dit-Yan Yeung, Wai-Kin Wong, and Wang-chun Woo · 2015
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Unsupervised learning of video representations using lstms
Nitish Srivastava, Elman Mansimov, and Ruslan Salakhudinov · 2015
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Dynamic filter networks
Xu Jia, Bert De Brabandere, Tinne Tuytelaars, and Luc V Gool · 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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Video pixel networks
Nal Kalchbrenner, Aäron Oord, Karen Simonyan, Ivo Danihelka, Oriol Vinyals, Alex Graves, and Koray Kavukcuoglu · 2017
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Deep predictive coding networks for video prediction and unsupervised learning
William Lotter, Gabriel Kreiman, and David Cox · 2017
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Deep learning for precipitation nowcasting: A benchmark and a new model
Xingjian Shi, Zhihan Gao, Leonard Lausen, Hao Wang, Dit-Yan Yeung, Wai-kin Wong, and Wang-chun Woo · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Predrnn: Recurrent neural networks for predictive learning using spatiotemporal lstms
Yunbo Wang, Mingsheng Long, Jianmin Wang, Zhifeng Gao, and Philip S Yu · 2017
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Deep spatio-temporal residual networks for citywide crowd flows prediction
Junbo Zhang, Yu Zheng, and Dekang Qi · 2017
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Learning spatiotemporal features using 3dcnn and convolutional lstm for gesture recognition
Liang Zhang, Guangming Zhu, Peiyi Shen, Juan Song, Syed Afaq Shah, and Mohammed Bennamoun · 2017
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Long-term on-board prediction of people in traffic scenes under uncertainty
Apratim Bhattacharyya, Mario Fritz, and Bernt Schiele · 2018
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Varnet: Exploring variations for unsupervised video prediction
Beibei Jin, Yu Hu, Yiming Zeng, Qiankun Tang, Shice Liu, and Jing Ye · 2018
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Stochastic adversarial video prediction
Alex X Lee, Richard Zhang, Frederik Ebert, Pieter Abbeel, Chelsea Finn, and Sergey Levine · 2018
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Folded recurrent neural networks for future video prediction
Marc Oliu, Javier Selva, and Sergio Escalera · 2018
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Rgb-d-based human motion recognition with deep learning: A survey
Pichao Wang, Wanqing Li, Philip Ogunbona, Jun Wan, and Sergio Escalera · 2018
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Predrnn++: Towards a resolution of the deep-in-time dilemma in spatiotemporal predictive learning
Yunbo Wang, Zhifeng Gao, Mingsheng Long, Jianmin Wang, and S Yu Philip · 2018
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Eidetic 3d lstm: A model for video prediction and beyond
Yunbo Wang, Lu Jiang, Ming-Hsuan Yang, Li-Jia Li, Mingsheng Long, and Li Fei-Fei · 2018
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Predcnn: Predictive learning with cascade convolutions
Ziru Xu, Yunbo Wang, Mingsheng Long, Jianmin Wang, and M KLiss · 2018
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Disentangling propagation and generation for video prediction
Hang Gao, Huazhe Xu, Qi-Zhi Cai, Ruth Wang, Fisher Yu, and Trevor Darrell · 2019
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Predicting future frames using retrospective cycle gan
Yong-Hoon Kwon and Min-Gyu Park · 2019
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Memory in memory: A predictive neural network for learning higher-order non-stationarity from spatiotemporal dynamics
Yunbo Wang, Jianjin Zhang, Hongyu Zhu, Mingsheng Long, Jianmin Wang, and Philip S Yu · 2019
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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
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Hippo: Recurrent memory with optimal polynomial projections
Albert Gu, Tri Dao, Stefano Ermon, Atri Rudra, and Christopher Ré · 2020
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Disentangling physical dynamics from unknown factors for unsupervised video prediction
Vincent Le Guen and Nicolas Thome · 2020
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Simplified state space layers for sequence modeling
Jimmy TH Smith, Andrew Warrington, and Scott Linderman · 2022
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Simvp: Towards simple yet powerful spatiotemporal predictive learning
Cheng Tan, Zhangyang Gao, Siyuan Li, and Stan Z Li · 2022
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Swin-unet: Unet-like pure transformer for medical image segmentation
Hu Cao, Yueyue Wang, Joy Chen, Dongsheng Jiang, Xiaopeng Zhang, Qi Tian, and Manning Wang · 2023
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Mamba: Linear-time sequence modeling with selective state spaces
Albert Gu and Tri Dao · 2023
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A dynamic multi-scale voxel flow network for video prediction
Xiaotao Hu, Zhewei Huang, Ailin Huang, Jun Xu, and Shuchang Zhou · 2023
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Video representation learning by recognizing temporal transformations
Simon Jenni, Givi Meishvili, and Paolo Favaro · 2020
Cited alongside, same era.
Exploring spatial-temporal multi-frequency analysis for high-fidelity and temporal-consistency video prediction
Beibei Jin, Yu Hu, Qiankun Tang, Jingyu Niu, Zhiping Shi, Yinhe Han, and Xiaowei Li · 2020
Cited alongside, same era.
Glu variants improve transformer
Noam Shazeer · 2020
Cited alongside, same era.
Efficient and information-preserving future frame prediction and beyond
Wei Yu, Yichao Lu, Steve Easterbrook, and Sanja Fidler · 2020
Cited alongside, same era.
Mau: A motion-aware unit for video prediction and beyond
Zheng Chang, Xinfeng Zhang, Shanshe Wang, Siwei Ma, Yan Ye, Xiang Xinguang, and Wen Gao · 2021
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Efficiently modeling long sequences with structured state spaces
Albert Gu, Karan Goel, and Christopher Re · 2021
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Combining recurrent, convolutional, and continuous-time models with linear state space layers
Albert Gu, Isys Johnson, Karan Goel, Khaled Saab, Tri Dao, Atri Rudra, and Christopher Ré · 2021
Cited alongside, same era.
Rong Li, ShiJie Li, Xieyuanli Chen, Teli Ma, Wang Hao, Juergen Gall, and Junwei Liang · 2023
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Long range language modeling via gated state spaces
Harsh Mehta, Ankit Gupta, Ashok Cutkosky, and Behnam Neyshabur · 2023
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Temporal attention unit: Towards efficient spatiotemporal predictive learning
Cheng Tan, Zhangyang Gao, Lirong Wu, Yongjie Xu, Jun Xia, Siyuan Li, and Stan Z Li · 2023
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Swinlstm: Improving spatiotemporal prediction accuracy using swin transformer and lstm
Song Tang, Chuang Li, Pu Zhang, and RongNian Tang · 2023
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Postrainbench: A comprehensive benchmark and a new model for precipitation forecasting
Yujin Tang, Jiaming Zhou, Xiang Pan, Zeying Gong, and Junwei Liang · 2023
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Mmvp: Motion-matrix-based video prediction
Yiqi Zhong, Luming Liang, Ilya Zharkov, and Ulrich Neumann · 2023
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Haifan Gong, Luoyao Kang, Yitao Wang, Xiang Wan, and Haofeng Li · 2024
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Mambair: A simple baseline for image restoration with state-space model
Hang Guo, Jinmin Li, Tao Dai, Zhihao Ouyang, Xudong Ren, and Shu-Tao Xia · 2024
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Tao Guo, Yinuo Wang, and Cai Meng · 2024
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Swin-umamba: Mamba-based unet with imagenet-based pretraining
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Vmamba: Visual state space model
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U-mamba: Enhancing long-range dependency for biomedical image segmentation
Jun Ma, Feifei Li, and Bo Wang · 2024
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Openstl: A comprehensive benchmark of spatio-temporal predictive learning
Cheng Tan, Siyuan Li, Zhangyang Gao, Wenfei Guan, Zedong Wang, Zicheng Liu, Lirong Wu, and Stan Z Li · 2024
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Segmamba: Long-range sequential modeling mamba for 3d medical image segmentation
Zhaohu Xing, Tian Ye, Yijun Yang, Guang Liu, and Lei Zhu · 2024
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Vivim: a video vision mamba for medical video object segmentation
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Vision mamba: Efficient visual representation learning with bidirectional state space model
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