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LiDAR-based world models offer more structured and geometry-aware representations than their image-based counterparts.
The lovász-softmax loss: A tractable surrogate for the optimization of the intersection-over-union measure in neural networks
Maxim Berman, Amal Rannen Triki, and Matthew B Blaschko · 2018
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Neural ordinary differential equations, 2019
Ricky T. Q. Chen, Yulia Rubanova, Jesse Bettencourt, and David Duvenaud · 2019
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4d spatio-temporal convnets: Minkowski convolutional neural networks
Christopher Choy, JunYoung Gwak, and Silvio Savarese · 2019
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Ffjord: Free-form continuous dynamics for scalable reversible generative models
Will Grathwohl, Ricky T. Q. Chen, Jesse Bettencourt, Ilya Sutskever, and David Duvenaud · 2019
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Similarity of neural network representations revisited, 2019
Simon Kornblith, Mohammad Norouzi, Honglak Lee, and Geoffrey Hinton · 2019
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nuscenes: A multimodal dataset for autonomous driving
Holger Caesar, Varun Bankiti, Alex H Lang, Sourabh Vora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Giancarlo Baldan, and Oscar Beijbom · 2020
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Lora: Low-rank adaptation of large language models, 2021
Edward J. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen · 2021
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Nerf: Representing scenes as neural radiance fields for view synthesis
Ben Mildenhall, Pratul P Srinivasan, Matthew Tancik, Jonathan T Barron, Ravi Ramamoorthi, and Ren Ng · 2021
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Score-based generative modeling through stochastic differential equations
Yang Song, Jascha Sohl-Dickstein, Diederik P. Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole · 2021
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Lidar slam with plane adjustment for indoor environment
Lipu Zhou, Daniel Koppel, and Michael Kaess · 2021
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Elucidating the design space of diffusion-based generative models
Tero Karras, Miika Aittala, Timo Aila, and Samuli Laine · 2022
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Kitti-360: A novel dataset and benchmarks for urban scene understanding in 2d and 3d
Yiyi Liao, Jun Xie, and Andreas Geiger · 2022
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Flow straight and fast: Learning to generate and transfer data with rectified flow
Xingchao Liu, Chengyue Gong, and Qiang Liu · 2022
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Detail preserving residual feature pyramid modules for optical flow
Libo Long and Jochen Lang · 2022
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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
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S2net: Stochastic sequential pointcloud forecasting
Xinshuo Weng, Junyu Nan, Kuan-Hui Lee, Rowan McAllister, Adrien Gaidon, Nicholas Rhinehart, and Kris M Kitani · 2022
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Hexplane: A fast representation for dynamic scenes
Ang Cao and Justin Johnson · 2023
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Gaia-1: A generative world model for autonomous driving
Anthony Hu, Lloyd Russell, Hudson Yeo, Zak Murez, George Fedoseev, Alex Kendall, Jamie Shotton, and Gianluca Corrado · 2023
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Point cloud forecasting as a proxy for 4d occupancy forecasting
Tarasha Khurana, Peiyun Hu, David Held, and Deva Ramanan · 2023
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Pcpnet: An efficient and semantic-enhanced transformer network for point cloud prediction
Zhen Luo, Junyi Ma, Zijie Zhou, and Guangming Xiong · 2023
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Scalable diffusion models with transformers
William Peebles and Saining Xie · 2023
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Consistency models
Yang Song, Prafulla Dhariwal, Mark Chen, and Ilya Sutskever · 2023
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Occ3d: A large-scale 3d occupancy prediction benchmark for autonomous driving
Xiaoyu Tian, Tao Jiang, Longfei Yun, Yucheng Mao, Huitong Yang, Yue Wang, Yilun Wang, and Hang Zhao · 2023
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Openoccupancy: A large scale benchmark for surrounding semantic occupancy perception
Xiaofeng Wang, Zheng Zhu, Wenbo Xu, Yunpeng Zhang, Yi Wei, Xu Chi, Yun Ye, Dalong Du, Jiwen Lu, and Xingang Wang · 2023
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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, et al · 2023
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Train till you drop: Towards stable and robust source-free unsupervised 3d domain adaptation
Björn Michele, Alexandre Boulch, Tuan-Hung Vu, Gilles Puy, Renaud Marlet, and Nicolas Courty · 2024
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Fast lidar data generation with rectified flows
Kazuto Nakashima, Xiaowen Liu, Tomoya Miyawaki, Yumi Iwashita, and Ryo Kurazume · 2024
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Scaling diffusion models to real-world 3d lidar scene completion
Lucas Nunes, Rodrigo Marcuzzi, Benedikt Mersch, Jens Behley, and Cyrill Stachniss · 2024
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Towards realistic scene generation with lidar diffusion models
Haoxi Ran, Vitor Guizilini, and Yue Wang · 2024
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Occsora: 4d occupancy generation models as world simulators for autonomous driving
Lening Wang, Wenzhao Zheng, Yilong Ren, Han Jiang, Zhiyong Cui, Haiyang Yu, and Jiwen Lu · 2024
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Yuwen Xiong, Wei-Chiu Ma, Jingkang Wang, and Raquel Urtasun · 2023
Cited alongside, same era.
Copilot4d: Learning unsupervised world models for autonomous driving via discrete diffusion
Lunjun Zhang, Yuwen Xiong, Ze Yang, Sergio Casas, Rui Hu, and Raquel Urtasun · 2023
Cited alongside, same era.
Uno: Unsupervised occupancy fields for perception and forecasting
Ben Agro, Quinlan Sykora, Sergio Casas, Thomas Gilles, and Raquel Urtasun · 2024
Cited alongside, same era.
Amir Bar, Gaoyue Zhou, Danny Tran, Trevor Darrell, and Yann LeCun · 2024
Cited alongside, same era.
Dynamiccity: Large-scale lidar generation from dynamic scenes
Hengwei Bian, Lingdong Kong, Haozhe Xie, Liang Pan, Yu Qiao, and Ziwei Liu · 2024
Cited alongside, same era.
p i 0 pi_{0} : A vision-language-action flow model for general robot control
Kevin Black, Noah Brown, Danny Driess, Adnan Esmail, Michael Equi, Chelsea Finn, Niccolo Fusai, Lachy Groom, Karol Hausman, Brian Ichter, et al · 2024
Cited alongside, same era.
Scaling rectified flow transformers for high-resolution image synthesis
Patrick Esser, Sumith Kulal, Andreas Blattmann, Rahim Entezari, Jonas Müller, Harry Saini, Yam Levi, Dominik Lorenz, Axel Sauer, Frederic Boesel, et al · 2024
Cited alongside, same era.
Later among the works it cites.
Driving into the future: Multiview visual forecasting and planning with world model for autonomous driving
Yuqi Wang, Jiawei He, Lue Fan, Hongxin Li, Yuntao Chen, and Zhaoxiang Zhang · 2024
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Occllama: An occupancy-language-action generative world model for autonomous driving
Julong Wei, Shanshuai Yuan, Pengfei Li, Qingda Hu, Zhongxue Gan, and Wenchao Ding · 2024
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Renderworld: World model with self-supervised 3d label
Ziyang Yan, Wenzhen Dong, Yihua Shao, Yuhang Lu, Liu Haiyang, Jingwen Liu, Haozhe Wang, Zhe Wang, Yan Wang, Fabio Remondino, et al · 2024
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Visual point cloud forecasting enables scalable autonomous driving
Zetong Yang, Li Chen, Yanan Sun, and Hongyang Li · 2024
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Lingfeng Zhang, Yuening Wang, Hongjian Gu, Atia Hamidizadeh, Zhanguang Zhang, Yuecheng Liu, Yutong Wang, David Gamaliel Arcos Bravo, Junyi Dong, Shunbo Zhou, et al · 2024
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Bevworld: A multimodal world model for autonomous driving via unified bev latent space
Yumeng Zhang, Shi Gong, Kaixin Xiong, Xiaoqing Ye, Xiao Tan, Fan Wang, Jizhou Huang, Hua Wu, and Haifeng Wang · 2024
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Occworld: Learning a 3d occupancy world model for autonomous driving
Wenzhao Zheng, Weiliang Chen, Yuanhui Huang, Borui Zhang, Yueqi Duan, and Jiwen Lu · 2024
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Smartpretrain: Model-agnostic and dataset-agnostic representation learning for motion prediction
Yang Zhou, Hao Shao, Letian Wang, Steven L Waslander, Hongsheng Li, and Yu Liu · 2024
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Cosmos world foundation model platform for physical ai
Niket Agarwal, Arslan Ali, Maciej Bala, Yogesh Balaji, Erik Barker, Tiffany Cai, Prithvijit Chattopadhyay, Yongxin Chen, Yin Cui, Yifan Ding, et al · 2025
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Cosmos-transfer1: Conditional world generation with adaptive multimodal control
Hassan Abu Alhaija, Jose Alvarez, Maciej Bala, Tiffany Cai, Tianshi Cao, Liz Cha, Joshua Chen, Mike Chen, Francesco Ferroni, Sanja Fidler, et al · 2025
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Dr-mpc: Deep residual model predictive control for real-world social navigation
James R Han, Hugues Thomas, Jian Zhang, Nicholas Rhinehart, and Timothy D Barfoot · 2025
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Omnieva: Embodied versatile planner via task-adaptive 3d-grounded and embodiment-aware reasoning
Yuecheng Liu, Dafeng Chi, Shiguang Wu, Zhanguang Zhang, Yuzheng Zhuang, Bowen Yang, He Zhu, Lingfeng Zhang, Pengwei Xie, David Gamaliel Arcos Bravo, et al · 2025
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Shape and texture: What influences reliable optical flow estimation?
Libo Long, Xiao Hu, and Jochen Lang · 2025
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Gaia-2: A controllable multi-view generative world model for autonomous driving
Lloyd Russell, Anthony Hu, Lorenzo Bertoni, George Fedoseev, Jamie Shotton, Elahe Arani, and Gianluca Corrado · 2025
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Lingfeng Zhang, Yuecheng Liu, Zhanguang Zhang, Matin Aghaei, Yaochen Hu, Hongjian Gu, Mohammad Ali Alomrani, David Gamaliel Arcos Bravo, Raika Karimi, Atia Hamidizadeh, et al · 2025
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