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Understanding dynamic 3D environment is crucial for robotic agents and many other applications.
Three-dimensional scene flow
Sundar Vedula, Simon Baker, Peter Rander, Robert Collins, and Takeo Kanade · 1999
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A spatio-temporal descriptor based on 3d-gradients
Alexander Kläser, Marcin Marszałek, and Cordelia Schmid · 2008
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Action recognition based on a bag of 3d points
Wanqing Li, Zhengyou Zhang, and Zicheng Liu · 2010
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Stop: Space-time occupancy patterns for 3d action recognition from depth map sequences
Antonio W Vieira, Erickson R Nascimento, Gabriel L Oliveira, Zicheng Liu, and Mario FM Campos · 2012
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Mining actionlet ensemble for action recognition with depth cameras
Jiang Wang, Zicheng Liu, Ying Wu, and Junsong Yuan · 2012
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Vision meets robotics: The kitti dataset
Andreas Geiger, Philip Lenz, Christoph Stiller, and Raquel Urtasun · 2013
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Large-scale video classification with convolutional neural networks
Andrej Karpathy, George Toderici, Sanketh Shetty, Thomas Leung, Rahul Sukthankar, and Li Fei-Fei · 2014
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Two-stream convolutional networks for action recognition in videos
Karen Simonyan and Andrew Zisserman · 2014
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ShapeNet: An Information-Rich 3D Model Repository
Angel X. Chang, Thomas Funkhouser, Leonidas Guibas, Pat Hanrahan, Qixing Huang, Zimo Li, Silvio Savarese, Manolis Savva, Shuran Song, Hao Su, Jianxiong Xiao, Li Yi, and Fisher Yu · 2015
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Long-term recurrent convolutional networks for visual recognition and description
Jeffrey Donahue, Lisa Anne Hendricks, Sergio Guadarrama, Marcus Rohrbach, Subhashini Venugopalan, Kate Saenko, and Trevor Darrell · 2015
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Flownet: Learning optical flow with convolutional networks
Alexey Dosovitskiy, Philipp Fischery, Eddy Ilg, Caner Hazirbas, Vladimir Golkov, Patrick van der Smagt, Daniel Cremers, and Thomas Brox · 2015
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Voxnet: A 3d convolutional neural network for real-time object recognition
Daniel Maturana and Sebastian Scherer · 2015
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Object scene flow for autonomous vehicles
Moritz Menze and Andreas Geiger · 2015
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Object scene flow for autonomous vehicles
Moritz Menze and Andreas Geiger · 2015
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Learning spatiotemporal features with 3d convolutional networks
Du Tran, Lubomir Bourdev, Rob Fergus, Lorenzo Torresani, and Manohar Paluri · 2015
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3d shapenets: A deep representation for volumetric shapes
Zhirong Wu, Shuran Song, Aditya Khosla, Fisher Yu, Linguang Zhang, Xiaoou Tang, and Jianxiong Xiao · 2015
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Beyond short snippets: Deep networks for video classification
Joe Yue-Hei Ng, Matthew Hausknecht, Sudheendra Vijayanarasimhan, Oriol Vinyals, Rajat Monga, and George Toderici · 2015
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Convolutional two-stream network fusion for video action recognition
Andrew Zisserman Christoph Feichtenhofer, Axel Pinz · 2016
Cited alongside, same era.
A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation
Frustum pointnets for 3d object detection from rgb-d data
Charles R. Qi, Wei Liu, Chenxia Wu, Hao Su, and Leonidas J. Guibas · 2018
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SPLATNet: Sparse lattice networks for point cloud processing
Hang Su, Varun Jampani, Deqing Sun, Subhransu Maji, Evangelos Kalogerakis, Ming-Hsuan Yang, and Jan Kautz · 2018
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Appearance-and-relation networks for video classification
Limin Wang, Wei Li, Wen Li, and Luc Van Gool · 2018
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Non-local neural networks
Xiaolong Wang, Ross Girshick, Abhinav Gupta, and Kaiming He · 2018
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Dynamic graph cnn for learning on point clouds
Yue Wang, Yongbin Sun, Ziwei Liu, Sanjay E. Sarma, Michael M. Bronstein, and Justin M. Solomon · 2018
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Second: Sparsely embedded convolutional detection
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N. Mayer, E. Ilg, P. Häusser, P. Fischer, D. Cremers, A. Dosovitskiy, and T. Brox · 2016
Cited alongside, same era.
The synthia dataset: A large collection of synthetic images for semantic segmentation of urban scenes
German Ros, Laura Sellart, Joanna Materzynska, David Vazquez, and Antonio M. Lopez · 2016
Cited alongside, same era.
http://www.cvlibs.net/datasets/kitti/eval_object.php?obj_benchmark=3d
Kitti 3d object detection benchmark leader board · 2017
Cited alongside, same era.
Quo vadis, action recognition? a new model and the kinetics dataset
Joao Carreira and Andrew Zisserman · 2017
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Deep learning advances in computer vision with 3d data: A survey
Anastasia Ioannidou, Elisavet Chatzilari, Spiros Nikolopoulos, and Ioannis Kompatsiaris · 2017
Cited alongside, same era.
Pointnet: Deep learning on point sets for 3d classification and segmentation
Charles R. Qi, H. Su, Kaichun Mo, and L. J. Guibas · 2017
Cited alongside, same era.
Pointnet++: Deep hierarchical feature learning on point sets in a metric space
Charles R. Qi, Li Yi, Hao Su, and Leonidas J Guibas · 2017
Cited alongside, same era.
Yan Yan, Yuxing Mao, and Bo Li · 2018
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Voxelnet: End-to-end learning for point cloud based 3d object detection
Yin Zhou and Oncel Tuzel · 2018
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Eco: Efficient convolutional network for online video understanding
Mohammadreza Zolfaghari, Kamaljeet Singh, and Thomas Brox · 2018
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4D Spatio-Temporal ConvNets: Minkowski Convolutional Neural Networks
Christopher Choy, JunYoung Gwak, and Silvio Savarese · 2019
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Learning video representations from correspondence proposals
Xingyu Liu, Joon-Young Lee, and Hailin Jin · 2019
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Flownet3d: Learning scene flow in 3d point clouds
Xingyu Liu, Charles. R. Qi, and Leonidas J. Guibas · 2019
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Pointrcnn: 3d object proposal generation and detection from point cloud
Shaoshuai Shi, Xiaogang Wang, and Hongsheng Li · 2019
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