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Generative models have significantly improved the generation and prediction quality on either camera images or LiDAR point clouds for autonomous driving.
Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2013
Earlier work this paper cites.
Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 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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Neural discrete representation learning
Aaron Van Den Oord, Oriol Vinyals, et al · 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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Towards accurate generative models of video: A new metric & challenges
Thomas Unterthiner, Sjoerd van Steenkiste, Karol Kurach, Raphael Marinier, Marcin Michalski, and Sylvain Gelly · 2018
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Deep generative modeling of lidar data
Lucas Caccia, Herke Van Hoof, Aaron Courville, and Joelle Pineau · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019
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Lidar sensor modeling and data augmentation with gans for autonomous driving
Ahmad El Sallab, Ibrahim Sobh, Mohamed Zahran, and Nader Essam · 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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Classifier-free diffusion guidance
Jonathan Ho and Tim Salimans · 2021
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Drivegan: Towards a controllable high-quality neural simulation
Seung Wook Kim, Jonah Philion, Antonio Torralba, and Sanja Fidler · 2021
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Swin transformer: Hierarchical vision transformer using shifted windows
Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, and Baining Guo · 2021
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High-resolution image synthesis with latent diffusion models, 2021
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2021
Earlier work this paper cites.
Score-based generative modeling through stochastic differential equations
Yang Song, Jascha Sohl-Dickstein, Diederik P Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole · 2021
Earlier work this paper cites.
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.
Maskgit: Masked generative image transformer
Huiwen Chang, Han Zhang, Lu Jiang, Ce Liu, and William T Freeman · 2022
Cited alongside, same era.
Elucidating the design space of diffusion-based generative models
Tero Karras, Miika Aittala, Timo Aila, and Samuli Laine · 2022
Cited alongside, same era.
Bevfusion: A simple and robust lidar-camera fusion framework
Tingting Liang, Hongwei Xie, Kaicheng Yu, Zhongyu Xia, Zhiwei Lin, Yongtao Wang, Tao Tang, Bing Wang, and Zhi Tang · 2022
Cited alongside, same era.
Llama: Open and efficient foundation language models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, et al · 2023
Later among the works it cites.
Drivedreamer: Towards real-world-driven world models for autonomous driving
Xiaofeng Wang, Zheng Zhu, Guan Huang, Xinze Chen, and Jiwen Lu · 2023
Later among the works it cites.
Learning compact representations for lidar completion and generation
Yuwen Xiong, Wei-Chiu Ma, Jingkang Wang, and Raquel Urtasun · 2023
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Kairui Yang, Enhui Ma, Jibin Peng, Qing Guo, Di Lin, and Kaicheng Yu · 2023
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Learning unsupervised world models for autonomous driving via discrete diffusion
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Self-supervised point cloud prediction using 3d spatio-temporal convolutional networks
Benedikt Mersch, Xieyuanli Chen, Jens Behley, and Cyrill Stachniss · 2022
Cited alongside, same era.
Photorealistic text-to-image diffusion models with deep language understanding
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily L Denton, Kamyar Ghasemipour, Raphael Gontijo Lopes, Burcu Karagol Ayan, Tim Salimans, et al · 2022
Cited alongside, same era.
S2net: Stochastic sequential pointcloud forecasting
Xinshuo Weng, Junyu Nan, Kuan-Hui Lee, Rowan McAllister, Adrien Gaidon, Nicholas Rhinehart, and Kris M Kitani · 2022
Cited alongside, same era.
Learning to generate realistic lidar point clouds
Vlas Zyrianov, Xiyue Zhu, and Shenlong Wang · 2022
Cited alongside, same era.
Align your latents: High-resolution video synthesis with latent diffusion models
Andreas Blattmann, Robin Rombach, Huan Ling, Tim Dockhorn, Seung Wook Kim, Sanja Fidler, and Karsten Kreis · 2023
Cited alongside, same era.
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
Cited alongside, same era.
Adriver-i: A general world model for autonomous driving
Fan Jia, Weixin Mao, Yingfei Liu, Yucheng Zhao, Yuqing Wen, Chi Zhang, Xiangyu Zhang, and Tiancai Wang · 2023
Cited alongside, same era.
Lunjun Zhang, Yuwen Xiong, Ze Yang, Sergio Casas, Rui Hu, and Raquel Urtasun · 2023
Later among the works it cites.
Magicdrive: Street view generation with diverse 3d geometry control
Ruiyuan Gao, Kai Chen, Enze Xie, HONG Lanqing, Zhenguo Li, Dit-Yan Yeung, and Qiang Xu · 2024
Closest in time.
Rangeldm: Fast realistic lidar point cloud generation
Qianjiang Hu, Zhimin Zhang, and Wei Hu · 2024
Closest in time.
Subjectdrive: Scaling generative data in autonomous driving via subject control
Binyuan Huang, Yuqing Wen, Yucheng Zhao, Yaosi Hu, Yingfei Liu, Fan Jia, Weixin Mao, Tiancai Wang, Chi Zhang, Chang Wen Chen, et al · 2024
Closest in time.
Zhimin Li, Jianwei Zhang, Qin Lin, Jiangfeng Xiong, Yanxin Long, Xinchi Deng, Yingfang Zhang, Xingchao Liu, Minbin Huang, Zedong Xiao, et al · 2024
Closest in time.
Fit: Flexible vision transformer for diffusion model
Zeyu Lu, Zidong Wang, Di Huang, Chengyue Wu, Xihui Liu, Wanli Ouyang, and Lei Bai · 2024
Closest in time.
Sit: Exploring flow and diffusion-based generative models with scalable interpolant transformers
Nanye Ma, Mark Goldstein, Michael S Albergo, Nicholas M Boffi, Eric Vanden-Eijnden, and Saining Xie · 2024
Closest in time.
Street-view image generation from a bird’s-eye view layout
Alexander Swerdlow, Runsheng Xu, and Bolei Zhou · 2024
Closest in time.
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
Closest in time.
Generalized Predictive Model for Autonomous Driving
Jiazhi Yang, Shenyuan Gao, Yihang Qiu, Li Chen, Tianyu Li, Bo Dai, Kashyap Chitta, Penghao Wu, Jia Zeng, Ping Luo, Jun Zhang, Andreas Geiger, Yu Qiao, and Hongyang Li · 2024
Closest in time.
Bevworld: A multimodal world model for autonomous driving via unified bev latent space
Zhang Yumeng, Gong Shi, Xiong Kaixin, Ye Xiaoqing, Tan Xiao, Wang Fan, Huang Jizhou, Wu Hua, and Wang Haifeng · 2024
Closest in time.
Drivedreamer-2: Llm-enhanced world models for diverse driving video generation
Guosheng Zhao, Xiaofeng Wang, Zheng Zhu, Xinze Chen, Guan Huang, Xiaoyi Bao, and Xingang Wang · 2024
Closest in time.