Fetching the paper…
Reading the bibliography…
Scene flow estimation is the task of describing the 3D motion field between temporally successive point clouds.
Object modelling by registration of multiple range images
Yang Chen and Gérard Medioni · 1992
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
Earlier work this paper cites.
Rigid scene flow for 3d lidar scans
Ayush Dewan, Tim Caselitz, Gian Diego Tipaldi, and Wolfram Burgard · 2016
Earlier work this paper cites.
A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation
N. Mayer, E. Ilg, P. Häusser, P. Fischer, D. Cremers, A. Dosovitskiy, and T. Brox · 2016
Earlier work this paper cites.
Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, and Ilya Sutskever · 2018
Earlier work this paper cites.
Pointflownet: Learning representations for rigid motion estimation from point clouds
Aseem Behl, Despoina Paschalidou, Simon Donné, and Andreas Geiger · 2019
Earlier work this paper cites.
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
Earlier work this paper cites.
PointPillars: Fast Encoders for Object Detection From Point Clouds
Alex Lang, Sourabh Vora, Holger Caesar, Lubing Zhou, Jiong Yang, and Oscar Beijbom · 2019
Earlier work this paper cites.
FlowNet3D: Learning Scene Flow in 3D Point Clouds
Xingyu Liu, Charles R Qi, and Leonidas J Guibas · 2019
Earlier work this paper cites.
Velodyne Lidar, 11 2019
Velodyne Lidar Alpha Prime · 2019
Earlier work this paper cites.
Language Models are Few-Shot Learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel Ziegler, Jeffrey Wu, Clemens Winter, Chris Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei · 2020
Earlier work this paper cites.
Smooth shells: Multi-scale shape registration with functional maps
Marvin Eisenberger, Zorah Lahner, and Daniel Cremers · 2020
Earlier work this paper cites.
Towards streaming perception
Mengtian Li, Yu-Xiong Wang, and Deva Ramanan · 2020
Earlier work this paper cites.
Just Go With the Flow: Self-Supervised Scene Flow Estimation
Himangi Mittal, Brian Okorn, and David Held · 2020
Earlier work this paper cites.
Scene flow from point clouds with or without learning
Jhony Kaesemodel Pontes, James Hays, and Simon Lucey · 2020
Earlier work this paper cites.
Flot: Scene flow on point clouds guided by optimal transport
Gilles Puy, Alexandre Boulch, and Renaud Marlet · 2020
Earlier work this paper cites.
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, Vijay Vasudevan, Wei Han, Jiquan Ngiam, Hang Zhao, Aleksei Timofeev, Scott Ettinger, Maxim Krivokon, Amy Gao, Aditya Joshi, Yu Zhang, Jonathon Shlens, Zhifeng Chen, and Dragomir Anguelov · 2020
Cited alongside, same era.
Self-supervised learning of non-rigid residual flow and ego-motion
Ivan Tishchenko, Sandro Lombardi, Martin R Oswald, and Marc Pollefeys · 2020
Cited alongside, same era.
Pointpwc-net: Cost volume on point clouds for (self-) supervised scene flow estimation
Wenxuan Wu, Zhi Yuan Wang, Zhuwen Li, Wei Liu, and Li Fuxin · 2020
Cited alongside, same era.
FlowMOT: 3D Multi-Object Tracking by Scene Flow Association
Guangyao Zhai, Xin Kong, Jinhao Cui, Yong Liu, and Zhen Yang · 2020
Cited alongside, same era.
SLIM: Self-supervised LiDAR scene flow and motion segmentation
Stefan Andreas Baur, David Josef Emmerichs, Frank Moosmann, Peter Pinggera, Björn Ommer, and Andreas Geiger · 2021
Deformation and Correspondence Aware Unsupervised Synthetic-to-Real Scene Flow Estimation for Point Clouds
Zhao Jin, Yinjie Lei, Naveed Akhtar, Haifeng Li, and Munawar Hayat · 2022
Later among the works it cites.
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
Later among the works it cites.
Application of Laser Systems for Detection and Ranging in the Modern Road Transportation and Maritime Sector
Nikola Lopac, Irena Jurdana, Adrian Brnelić, and Tomislav Krljan · 2022
Later among the works it cites.
VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training
Yecheng Jason Ma, Shagun Sodhani, Dinesh Jayaraman, Osbert Bastani, Vikash Kumar, and Amy Zhang · 2022
Later among the works it cites.
Motion Inspired Unsupervised Perception and Prediction in Autonomous Driving
Mahyar Najibi, Jingwei Ji, Yin Zhou, Charles R. Qi, Xinchen Yan, Scott Ettinger, and Dragomir Anguelov · 2022
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
On the opportunities and risks of foundation models
Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S. Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, Erik Brynjolfsson, S. Buch, Dallas Card, Rodrigo Castellon, Niladri S. Chatterji, Annie S. Chen, Kathleen A. Creel, Jared Davis, Dora Demszky, Chris Donahue, Moussa Doumbouya, Esin Durmus, Stefano Ermon, John Etchemendy, Kawin Ethayarajh, Li Fei-Fei, Chelsea Finn, Trevor Gale, Lauren E. Gillespie, Karan Goel, Noah D. Goodman, Shelby Grossman, Neel Guha, Tatsunori Hashimoto, Peter Henderson, John Hewitt, Daniel E. Ho, Jenny Hong, Kyle Hsu, Jing Huang, Thomas F. Icard, Saahil Jain, Dan Jurafsky, Pratyusha Kalluri, Siddharth Karamcheti, Geoff Keeling, Fereshte Khani, O. Khattab, Pang Wei Koh, Mark S. Krass, Ranjay Krishna, Rohith Kuditipudi, Ananya Kumar, Faisal Ladhak, Mina Lee, Tony Lee, Jure Leskovec, Isabelle Levent, Xiang Lisa Li, Xuechen Li, Tengyu Ma, Ali Malik, Christopher D. Manning, Suvir P. Mirchandani, Eric Mitchell, Zanele Munyikwa, Suraj Nair, Avanika Narayan, Deepak Narayanan, Benjamin Newman, Allen Nie, Juan Carlos Niebles, Hamed Nilforoshan, J. F. Nyarko, Giray Ogut, Laurel Orr, Isabel Papadimitriou, Joon Sung Park, Chris Piech, Eva Portelance, Christopher Potts, Aditi Raghunathan, Robert Reich, Hongyu Ren, Frieda Rong, Yusuf H. Roohani, Camilo Ruiz, Jack Ryan, Christopher R’e, Dorsa Sadigh, Shiori Sagawa, Keshav Santhanam, Andy Shih, Krishna Parasuram Srinivasan, Alex Tamkin, Rohan Taori, Armin W. Thomas, Florian Tramèr, Rose E. Wang, William Wang, Bohan Wu, Jiajun Wu, Yuhuai Wu, Sang Michael Xie, Michihiro Yasunaga, Jiaxuan You, Matei A. Zaharia, Michael Zhang, Tianyi Zhang, Xikun Zhang, Yuhui Zhang, Lucia Zheng, Kaitlyn Zhou, and Percy Liang · 2021
Cited alongside, same era.
Weakly supervised learning of rigid 3d scene flow
Zan Gojcic, Or Litany, Andreas Wieser, Leonidas J Guibas, and Tolga Birdal · 2021
Cited alongside, same era.
Scalable Scene Flow From Point Clouds in the Real World
Philipp Jund, Chris Sweeney, Nichola Abdo, Zhifeng Chen, and Jonathon Shlens · 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.
Inverting the pose forecasting pipeline with spf2: Sequential pointcloud forecasting for sequential pose forecasting
Xinshuo Weng, Jianren Wang, Sergey Levine, Kris Kitani, and Nicholas Rhinehart · 2021
Cited alongside, same era.
Argoverse 2: Next Generation Datasets for Self-driving Perception and Forecasting
Benjamin Wilson, William Qi, Tanmay Agarwal, John Lambert, Jagjeet Singh, Siddhesh Khandelwal, Bowen Pan, Ratnesh Kumar, Andrew Hartnett, Jhony Kaesemodel Pontes, Deva Ramanan, Peter Carr, and James Hays · 2021
Cited alongside, same era.
RMS-FlowNet: Efficient and Robust Multi-Scale Scene Flow Estimation for Large-Scale Point Clouds
Ramy Battrawy, René Schuster, Mohammad-Ali Nikouei Mahani, and Didier Stricker · 2022
Cited alongside, same era.
Later among the works it cites.
R3M: A Universal Visual Representation for Robot Manipulation
Aravind Rajeswaran, Vikash Kumar, Chelsea Finn, and Abhinav Gupta · 2022
Later among the works it cites.
Sparse PointPillars: Maintaining and Exploiting Input Sparsity to Improve Runtime on Embedded Systems
Kyle Vedder and Eric Eaton · 2022
Later among the works it cites.
PointMotionNet: Point-Wise Motion Learning for Large-Scale LiDAR Point Clouds Sequences
Jun Wang, Xiaolong Li, Alan Sullivan, Lynn Abbott, and Siheng Chen · 2022
Later among the works it cites.
Re-Evaluating LiDAR Scene Flow for Autonomous Driving
Nathaniel Chodosh, Deva Ramanan, and Simon Lucey · 2023
Closest in time.
Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alexander C. Berg, Wan-Yen Lo, Piotr Dollár, and Ross Girshick · 2023
Closest in time.
LIV: Language-Image Representations and Rewards for Robotic Control
Yecheng Jason Ma, William Liang, Vaidehi Som, Vikash Kumar, Amy Zhang, Osbert Bastani, and Dinesh Jayaraman · 2023
Closest in time.
Gpt-4 technical report, 2023
OpenAI · 2023
Closest in time.
An empirical analysis of range for 3d object detection
Neehar Peri, Mengtian Li, Benjamin Wilson, Yu-Xiong Wang, James Hays, and Deva Ramanan · 2023
Closest in time.
Voyager: An Open-Ended Embodied Agent with Large Language Models
Guanzhi Wang, Yuqi Xie, Yunfan Jiang, Ajay Mandlekar, Chaowei Xiao, Yuke Zhu, Linxi Fan, and Anima Anandkumar · 2023
Closest in time.
Adcnet: Learning from raw radar data via distillation, 2023
Bo Yang, Ishan Khatri, Michael Happold, and Chulong Chen · 2023
Closest in time.
PointOdyssey: A Large-Scale Synthetic Dataset for Long-Term Point Tracking
Yang Zheng, Adam W. Harley, Bokui Shen, Gordon Wetzstein, and Leonidas J. Guibas · 2023
Closest in time.