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We tackle the task of scene flow estimation from point clouds.
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, et al · 2015
Earlier work this paper cites.
Flownet: Learning optical flow with convolutional networks
Alexey Dosovitskiy, Philipp Fischer, Eddy Ilg, Philip Hausser, Caner Hazirbas, Vladimir Golkov, Patrick Van Der Smagt, Daniel Cremers, and Thomas Brox · 2015
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Object scene flow for autonomous vehicles
Moritz Menze and Andreas Geiger · 2015
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3d scene flow estimation with a piecewise rigid scene model
Christoph Vogel, Konrad Schindler, and Stefan Roth · 2015
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A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation
Nikolaus Mayer, Eddy Ilg, Philip Hausser, Philipp Fischer, Daniel Cremers, Alexey Dosovitskiy, and Thomas Brox · 2016
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Bounding boxes, segmentations and object coordinates: How important is recognition for 3d scene flow estimation in autonomous driving scenarios?
Aseem Behl, Omid Hosseini Jafari, Siva Karthik Mustikovela, Hassan Abu Alhaija, Carsten Rother, and Andreas Geiger · 2017
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Flownet 2.0: Evolution of optical flow estimation with deep networks
Eddy Ilg, Nikolaus Mayer, Tonmoy Saikia, Margret Keuper, Alexey Dosovitskiy, and Thomas Brox · 2017
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Pointnet: Deep learning on point sets for 3d classification and segmentation
Charles R Qi, Hao Su, Kaichun Mo, and Leonidas J Guibas · 2017
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Cascaded scene flow prediction using semantic segmentation
Zhile Ren, Deqing Sun, Jan Kautz, and Erik Sudderth · 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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Ppf-foldnet: Unsupervised learning of rotation invariant 3d local descriptors
Haowen Deng, Tolga Birdal, and Slobodan Ilic · 2018
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Ppfnet: Global context aware local features for robust 3d point matching
Haowen Deng, Tolga Birdal, and Slobodan Ilic · 2018
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Pwc-net: Cnns for optical flow using pyramid, warping, and cost volume
Deqing Sun, Xiaodong Yang, Ming-Yu Liu, and Jan Kautz · 2018
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The perfect match: 3d point cloud matching with smoothed densities
Zan Gojcic, Caifa Zhou, Jan D Wegner, and Andreas Wieser · 2019
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Hplflownet: Hierarchical permutohedral lattice flownet for scene flow estimation on large-scale point clouds
Xiuye Gu, Yijie Wang, Chongruo Wu, Yong Jae Lee, and Panqu Wang · 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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Deep rigid instance scene flow
Wei-Chiu Ma, Shenlong Wang, Rui Hu, Yuwen Xiong, and Raquel Urtasun · 2019
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Bert4rec: Sequential recommendation with bidirectional encoder representations from transformer
Fei Sun, Jun Liu, Jian Wu, Changhua Pei, Xiao Lin, Wenwu Ou, and Peng Jiang · 2019
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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 · 2019
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Wenxuan Wu, Zhiyuan Wang, Zhuwen Li, Wei Liu, and Li Fuxin · 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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Scene flow from point clouds with or without learning
Jhony Kaesemodel Pontes, James Hays, and Simon Lucey · 2020
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Flot: Scene flow on point clouds guided by optimal transport
Gilles Puy, Alexandre Boulch, and Renaud Marlet · 2020
Cited alongside, same era.
Superglue: Learning feature matching with graph neural networks
Paul-Edouard Sarlin, Daniel DeTone, Tomasz Malisiewicz, and Andrew Rabinovich · 2020
Cited alongside, same era.
Scalability in perception for autonomous driving: Waymo open dataset
Pei Sun, Henrik Kretzschmar, Xerxes Dotiwalla, Aurelien Chouard, Vijaysai Patnaik, Paul Tsui, James Guo, Yin Zhou, Yuning Chai, Benjamin Caine, et al · 2020
Cited alongside, same era.
Raft: Recurrent all-pairs field transforms for optical flow
Zachary Teed and Jia Deng · 2020
Cited alongside, same era.
Flownet3d++: Geometric losses for deep scene flow estimation
Zirui Wang, Shuda Li, Henry Howard-Jenkins, Victor Prisacariu, and Min Chen · 2020
Cited alongside, same era.
Transformers: State-of-the-art natural language processing
Fh-net: A fast hierarchical network for scene flow estimation on real-world point clouds
Lihe Ding, Shaocong Dong, Tingfa Xu, Xinli Xu, Jie Wang, and Jianan Li · 2022
Later among the works it cites.
Rcp: Recurrent closest point for scene flow estimation on 3d point clouds
Xiaodong Gu, Chengzhou Tang, Weihao Yuan, Zuozhuo Dai, Siyu Zhu, and Ping Tan · 2022
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Sctn: Sparse convolution-transformer network for scene flow estimation
Bing Li, Cheng Zheng, Silvio Giancola, and Bernard Ghanem · 2022
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Rigidflow: Self-supervised scene flow learning on point clouds by local rigidity prior
Ruibo Li, Chi Zhang, Guosheng Lin, Zhe Wang, and Chunhua Shen · 2022
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Camliflow: bidirectional camera-lidar fusion for joint optical flow and scene flow estimation
Haisong Liu, Tao Lu, Yihui Xu, Jia Liu, Wenjie Li, and Lijun Chen · 2022
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Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi Louf, Morgan Funtowicz, et al · 2020
Cited alongside, same era.
Pointasnl: Robust point clouds processing using nonlocal neural networks with adaptive sampling
Xu Yan, Chaoda Zheng, Zhen Li, Sheng Wang, and Shuguang Cui · 2020
Cited alongside, same era.
Pct: Point cloud transformer
Meng-Hao Guo, Jun-Xiong Cai, Zheng-Ning Liu, Tai-Jiang Mu, Ralph R Martin, and Shi-Min Hu · 2021
Cited alongside, same era.
Flowstep3d: Model unrolling for self-supervised scene flow estimation
Yair Kittenplon, Yonina C Eldar, and Dan Raviv · 2021
Cited alongside, same era.
Hcrf-flow: Scene flow from point clouds with continuous high-order crfs and position-aware flow embedding
Ruibo Li, Guosheng Lin, Tong He, Fayao Liu, and Chunhua Shen · 2021
Cited alongside, same era.
Neural scene flow prior
Xueqian Li, Jhony Kaesemodel Pontes, and Simon Lucey · 2021
Cited alongside, same era.
Tera: Self-supervised learning of transformer encoder representation for speech
Andy T Liu, Shang-Wen Li, and Hung-yi Lee · 2021
Cited alongside, same era.
Transformers in 3d point clouds: A survey
Dening Lu, Qian Xie, Mingqiang Wei, Linlin Xu, and Jonathan Li · 2022
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Geometric transformer for fast and robust point cloud registration
Zheng Qin, Hao Yu, Changjian Wang, Yulan Guo, Yuxing Peng, and Kai Xu · 2022
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Sf2se3: Clustering scene flow into se (3)-motions via proposal and selection
Leonhard Sommer, Philipp Schröppel, and Thomas Brox · 2022
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What matters for 3d scene flow network
Guangming Wang, Yunzhe Hu, Zhe Liu, Yiyang Zhou, Masayoshi Tomizuka, Wei Zhan, and Hesheng Wang · 2022
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Gmflow: Learning optical flow via global matching
Haofei Xu, Jing Zhang, Jianfei Cai, Hamid Rezatofighi, and Dacheng Tao · 2022
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Point-bert: Pre-training 3d point cloud transformers with masked point modeling
Xumin Yu, Lulu Tang, Yongming Rao, Tiejun Huang, Jie Zhou, and Jiwen Lu · 2022
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Global matching with overlapping attention for optical flow estimation
Shiyu Zhao, Long Zhao, Zhixing Zhang, Enyu Zhou, and Dimitris Metaxas · 2022
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Re-evaluating lidar scene flow for autonomous driving
Nathaniel Chodosh, Deva Ramanan, and Simon Lucey · 2023
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Dkm: Dense kernelized feature matching for geometry estimation
Johan Edstedt, Ioannis Athanasiadis, Mårten Wadenbäck, and Michael Felsberg · 2023
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Pt-flownet: Scene flow estimation on point clouds with point transformer
Jingyun Fu, Zhiyu Xiang, Chengyu Qiao, and Tingming Bai · 2023
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Scoop: Self-supervised correspondence and optimization-based scene flow
Itai Lang, Dror Aiger, Forrester Cole, Shai Avidan, and Michael Rubinstein · 2023
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Deep learning for scene flow estimation on point clouds: A survey and prospective trends
Zhiqi Li, Nan Xiang, Honghua Chen, Jianjun Zhang, and Xiaosong Yang · 2023
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Learning optical flow and scene flow with bidirectional camera-lidar fusion
Haisong Liu, Tao Lu, Yihui Xu, Jia Liu, and Limin Wang · 2023
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Toolflownet: Robotic manipulation with tools via predicting tool flow from point clouds
Daniel Seita, Yufei Wang, Sarthak J Shetty, Edward Yao Li, Zackory Erickson, and David Held · 2023
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Rotation-invariant transformer for point cloud matching
Hao Yu, Zheng Qin, Ji Hou, Mahdi Saleh, Dongsheng Li, Benjamin Busam, and Slobodan Ilic · 2023
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Peal: Prior-embedded explicit attention learning for low-overlap point cloud registration
Junle Yu, Luwei Ren, Yu Zhang, Wenhui Zhou, Lili Lin, and Guojun Dai · 2023
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