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Environment prediction frameworks are critical for the safe navigation of autonomous vehicles (AVs) in dynamic settings.
Using occupancy grids for mobile robot perception and navigation
Alberto Elfes · 1989
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Autoencoders, minimum description length and Helmholtz free energy
Geoffrey E Hinton and Richard Zemel · 1993
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Merging occupancy grid maps from multiple robots
Andreas Birk and Stefano Carpin · 2006
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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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Auto-encoding variational Bayes
Diederik P Kingma and Max Welling · 2014
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Autoencoding beyond pixels using a learned similarity metric
Anders Boesen Lindbo Larsen, Søren Kaae Sønderby, Hugo Larochelle, and Ole Winther · 2016
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Image-to-image translation with conditional adversarial networks
Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, and Alexei A Efros · 2017
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Deep predictive coding networks for video prediction and unsupervised learning
William Lotter, Gabriel Kreiman, and David Cox · 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, Lukasz Kaiser, and Illia Polosukhin · 2017
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Stochastic variational video prediction
Mohammad Babaeizadeh, Chelsea Finn, Dumitru Erhan, Roy H. Campbell, and Sergey Levine · 2018
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Deep tracking in the wild: End-to-end tracking using recurrent neural networks
Julie Dequaire, Peter Ondrúška, Dushyant Rao, Dominic Wang, and Ingmar Posner · 2018
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Recurrent world models facilitate policy evolution
David Ha and Jürgen Schmidhuber · 2018
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The unreasonable effectiveness of deep features as a perceptual metric
Richard Zhang, Phillip Isola, Alexei A Efros, Eli Shechtman, and Oliver Wang · 2018
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Dream to control: Learning behaviors by latent imagination
Danijar Hafner, Timothy Lillicrap, Jimmy Ba, and Mohammad Norouzi · 2019
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Dynamic environment prediction in urban scenes using recurrent representation learning
Masha Itkina, Katherine Driggs-Campbell, and Mykel J Kochenderfer · 2019
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2019
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Multi-step prediction of occupancy grid maps with recurrent neural networks
Nima Mohajerin and Mohsen Rohani · 2019
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Long-term occupancy grid prediction using recurrent neural networks
Marcel Schreiber, Stefan Hoermann, and Klaus Dietmayer · 2019
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Eidetic 3d lstm: A model for video prediction and beyond
Yunbo Wang, Lu Jiang, Ming-Hsuan Yang, Li-Jia Li, Mingsheng Long, and Li Fei-Fei · 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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MultiPath: Multiple probabilistic anchor trajectory hypotheses for behavior prediction
Yuning Chai, Benjamin Sapp, Mayank Bansal, and Dragomir Anguelov · 2020
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Analyzing and improving the image quality of stylegan
Tero Karras, Samuli Laine, Miika Aittala, Janne Hellsten, Jaakko Lehtinen, and Timo Aila · 2020
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Attention augmented ConvLSTM for environment prediction
How do we fail? stress testing perception in autonomous vehicles
Harrison Delecki, Masha Itkina, Bernard Lange, Ransalu Senanayake, and Mykel J Kochenderfer · 2022
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Simvp: Simpler yet better video prediction
Zhangyang Gao, Cheng Tan, Lirong Wu, and Stan Z Li · 2022
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Video diffusion models
Jonathan Ho, Tim Salimans, Alexey A. Gritsenko, William Chan, Mohammad Norouzi, and David J. Fleet · 2022
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Multi-agent variational occlusion inference using people as sensors
Masha Itkina, Ye-Ji Mun, Katherine Driggs-Campbell, and Mykel J. Kochenderfer · 2022
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Occupancy flow fields for motion forecasting in autonomous driving
Reza Mahjourian, Jinkyu Kim, Yuning Chai, Mingxing Tan, Ben Sapp, and Dragomir Anguelov · 2022
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Dynamics-aware spatiotemporal occupancy prediction in urban environments
Maneekwan Toyungyernsub, Esen Yel, Jiachen Li, and Mykel J Kochenderfer · 2022
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Bernard Lange, Masha Itkina, and Mykel J Kochenderfer · 2020
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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
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Shared cross-modal trajectory prediction for autonomous driving
Chiho Choi, Joon Hee Choi, Jiachen Li, and Srikanth Malla · 2021
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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 · 2021
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Large scale interactive motion forecasting for autonomous driving: The waymo open motion dataset
Scott Ettinger, Shuyang Cheng, Benjamin Caine, Chenxi Liu, Hang Zhao, Sabeek Pradhan, Yuning Chai, Ben Sapp, Charles R Qi, Yin Zhou, et al · 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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Offboard 3d object detection from point cloud sequences
Charles R Qi, Yin Zhou, Mahyar Najibi, Pei Sun, Khoa Vo, Boyang Deng, and Dragomir Anguelov · 2021
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Diffusers: State-of-the-art diffusion models
Patrick von Platen, Suraj Patil, Anton Lozhkov, Pedro Cuenca, Nathan Lambert, Kashif Rasul, Mishig Davaadorj, Dhruv Nair, Sayak Paul, William Berman, Yiyi Xu, Steven Liu, and Thomas Wolf · 2022
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Predrnn: A recurrent neural network for spatiotemporal predictive learning
Yunbo Wang, Haixu Wu, Jianjin Zhang, Zhifeng Gao, Jianmin Wang, S Yu Philip, and Mingsheng Long · 2022
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Survey on lidar perception in adverse weather conditions
Mariella Dreissig, Dominik Scheuble, Florian Piewak, and Joschka Boedecker · 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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Wayformer: Motion forecasting via simple & efficient attention networks
Nigamaa Nayakanti, Rami Al-Rfou, Aurick Zhou, Kratarth Goel, Khaled S. Refaat, and Benjamin Sapp · 2023
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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, Yue Wang, Yilun Wang, and Hang Zhao · 2023
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Scene informer: Anchor-based occlusion inference and trajectory prediction in partially observable environments
Bernard Lange, Jiachen Li, and Mykel J Kochenderfer · 2024
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Dinov2: Learning robust visual features without supervision
Maxime Oquab, Timothée Darcet, Théo Moutakanni, Huy V. Vo, Marc Szafraniec, Vasil Khalidov, Pierre Fernandez, Daniel HAZIZA, Francisco Massa, Alaaeldin El-Nouby, Mido Assran, Nicolas Ballas, Wojciech Galuba, Russell Howes, Po-Yao Huang, Shang-Wen Li, Ishan Misra, Michael Rabbat, Vasu Sharma, Gabriel Synnaeve, Hu Xu, Herve Jegou, Julien Mairal, Patrick Labatut, Armand Joulin, and Piotr Bojanowski · 2024
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Predicting future spatiotemporal occupancy grids with semantics for autonomous driving
Maneekwan Toyungyernsub, Esen Yel, Jiachen Li, and Mykel J Kochenderfer · 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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