Fetching the paper…
Reading the bibliography…
In contrast to extensive studies on general vision, pre-training for scalable visual autonomous driving remains seldom explored.
ImageNet: A Large-Scale Hierarchical Image Database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
Earlier work this paper cites.
Vision meets robotics: The KITTI dataset
Andreas Geiger, Philip Lenz, Christoph Stiller, and Raquel Urtasun · 2013
Earlier work this paper cites.
Microsoft COCO: Common Objects in Context
Tsung-Yi Lin, Michael Maire, Serge J. Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C. Lawrence Zitnick · 2014
Earlier work this paper cites.
Adam: A Method for Stochastic Optimization
Diederik P. Kingma and Jimmy Ba · 2015
Earlier work this paper cites.
Deep Residual Learning for Image Recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
Deformable Convolutional Networks
Jifeng Dai, Haozhi Qi, Yuwen Xiong, Yi Li, Guodong Zhang, Han Hu, and Yichen Wei · 2017
Earlier work this paper cites.
Feature Pyramid Networks for Object Detection
Tsung-Yi Lin, Piotr Dollár, Ross B. Girshick, Kaiming He, Bharath Hariharan, and Serge J. Belongie · 2017
Earlier work this paper cites.
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
Earlier work this paper cites.
Unsupervised Feature Learning via Non-Parametric Instance Discrimination
Zhirong Wu, Yuanjun Xiong, Stella X Yu, and Dahua Lin · 2018
Earlier work this paper cites.
SemanticKITTI: A Dataset for Semantic Scene Understanding of LiDAR Sequences
J. Behley, M. Garbade, A. Milioto, J. Quenzel, S. Behnke, C. Stachniss, and J. Gall · 2019
Earlier work this paper cites.
Decoupled Weight Decay Regularization
Ilya Loshchilov and Frank Hutter · 2019
Earlier work this paper cites.
LaserNet: An Efficient Probabilistic 3D Object Detector for Autonomous Driving
Gregory P. Meyer, Ankit Laddha, Eric Kee, Carlos Vallespi-Gonzalez, and Carl K. Wellington · 2019
Earlier work this paper cites.
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
Earlier work this paper cites.
Improved Baselines with Momentum Contrastive Learning
Xinlei Chen, Haoqi Fan, Ross Girshick, and Kaiming He · 2020
Earlier work this paper cites.
MMDetection3D: OpenMMLab next-generation platform for general 3D object detection
MMDetection3D Contributors · 2020
Earlier work this paper cites.
Momentum Contrast for Unsupervised Visual Representation Learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick · 2020
Earlier work this paper cites.
Supervised Contrastive Learning
Prannay Khosla, Piotr Teterwak, Chen Wang, Aaron Sarna, Yonglong Tian, Phillip Isola, Aaron Maschinot, Ce Liu, and Dilip Krishnan · 2020
Earlier work this paper cites.
PnPNet: End-to-End Perception and Prediction With Tracking in the Loop
Ming Liang, Bin Yang, Wenyuan Zeng, Yun Chen, Rui Hu, Sergio Casas, and Raquel Urtasun · 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
Earlier work this paper cites.
Contrastive Multiview Coding
Yonglong Tian, Dilip Krishnan, and Phillip Isola · 2020
Earlier work this paper cites.
Xinshuo Weng, Jianren Wang, Sergey Levine, Kris Kitani, and Nicholas Rhinehart · 2020
Cited alongside, same era.
PointContrast: Unsupervised Pre-training for 3D Point Cloud Understanding
Saining Xie, Jiatao Gu, Demi Guo, Charles R Qi, Leonidas Guibas, and Or Litany · 2020
Cited alongside, same era.
Deformable DETR: Deformable Transformers for End-to-End Object Detection
Xizhou Zhu, Weijie Su, Lewei Lu, Bin Li, Xiaogang Wang, and Jifeng Dai · 2020
Cited alongside, same era.
Range Conditioned Dilated Convolutions for Scale Invariant 3D Object Detection
Alex Bewley, Pei Sun, Thomas Mensink, Dragomir Anguelov, and Cristian Sminchisescu · 2021
Cited alongside, same era.
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, Jakob Uszkoreit, and Neil Houlsby · 2021
S2Net: Stochastic Sequential Pointcloud Forecasting
Xinshuo Weng, Junyu Nan, Kuan-Hui Lee, Rowan McAllister, Adrien Gaidon, Nicholas Rhinehart, and Kris M Kitani · 2022
Later among the works it cites.
Trajectory-guided Control Prediction for End-to-end Autonomous Driving: A Simple yet Strong Baseline
Penghao Wu, Xiaosong Jia, Li Chen, Junchi Yan, Hongyang Li, and Yu Qiao · 2022
Later among the works it cites.
SimMIM: A Simple Framework for Masked Image Modeling
Zhenda Xie, Zheng Zhang, Yue Cao, Yutong Lin, Jianmin Bao, Zhuliang Yao, Qi Dai, and Han Hu · 2022
Later among the works it cites.
A Cookbook of Self-supervised Learning
Randall Balestriero, Mark Ibrahim, Vlad Sobal, Ari Morcos, Shashank Shekhar, Tom Goldstein, Florian Bordes, Adrien Bardes, Gregoire Mialon, Yuandong Tian, Avi Schwarzschild, Andrew Gordon Wilson, Jonas Geiping, Quentin Garrido, Pierre Fernandez, Amir Bar, Hamed Pirsiavash, Yann LeCun, and Micah Goldblum · 2023
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
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 Qi, Yin Zhou, Zoey Yang, Aurélien Chouard, Pei Sun, Jiquan Ngiam, Vijay Vasudevan, Alexander McCauley, Jonathon Shlens, and Dragomir Anguelov · 2021
Cited alongside, same era.
Exploring Data-Efficient 3D Scene Understanding with Contrastive Scene Contexts
Ji Hou, Benjamin Graham, Matthias Nießner, and Saining Xie · 2021
Cited alongside, same era.
BEVDet: High-performance Multi-camera 3D Object Detection in Bird-Eye-View
Junjie Huang, Guan Huang, Zheng Zhu, Ye Yun, and Dalong Du · 2021
Cited alongside, same era.
Self-supervised Point Cloud Prediction Using 3D Spatio-temporal Convolutional Networks
B. Mersch, X. Chen, J. Behley, and C. Stachniss · 2021
Cited alongside, same era.
SimpleTrack: Understanding and Rethinking 3D Multi-object Tracking
Ziqi Pang, Zhichao Li, and Naiyan Wang · 2021
Cited alongside, same era.
Is Pseudo-Lidar Needed for Monocular 3D Object Detection?
Dennis Park, Rares Ambrus, Vitor Guizilini, Jie Li, and Adrien Gaidon · 2021
Cited alongside, same era.
Categorical Depth DistributionNetwork for Monocular 3D Object Detection
Cody Reading, Ali Harakeh, Julia Chae, and Steven L. Waslander · 2021
Cited alongside, same era.
Li Chen, Penghao Wu, Kashyap Chitta, Bernhard Jaeger, Andreas Geiger, and Hongyang Li · 2023
Closest in time.
OpenScene: The Largest Up-to-Date 3D Occupancy Prediction Benchmark in Autonomous Driving, 2023
OpenScene Contributors · 2023
Closest in time.
ViP3D: End-to-end visual trajectory prediction via 3d agent queries
Junru Gu, Chenxu Hu, Tianyuan Zhang, Xuanyao Chen, Yilun Wang, Yue Wang, and Hang Zhao · 2023
Closest in time.
A Survey on Self-supervised Learning: Algorithms, Applications, and Future Trends
Jie Gui, Tuo Chen, Jing Zhang, Qiong Cao, Zhenan Sun, Hao Luo, and Dacheng Tao · 2023
Closest in time.
Tri-Perspective View for Vision-Based 3D Semantic Occupancy Prediction
Yuanhui Huang, Wenzhao Zheng, Yunpeng Zhang, Jie Zhou, and Jiwen Lu · 2023
Closest in time.
Point Cloud Forecasting as a Proxy for 4D Occupancy Forecasting
Tarasha Khurana, Peiyun Hu, David Held, and Deva Ramanan · 2023
Closest in time.
Occupancy-MAE: Self-Supervised Pre-Training Large-Scale LiDAR Point Clouds With Masked Occupancy Autoencoders
Chen Min, Liang Xiao, Dawei Zhao, Yiming Nie, and Bin Dai · 2023
Closest in time.
To Compress or Not to Compress–Self-Supervised Learning and Information Theory: A Review
Ravid Shwartz-Ziv and Yann LeCun · 2023
Closest in time.
DriveLM: Driving with Graph Visual Question Answering
Chonghao Sima, Katrin Renz, Kashyap Chitta, Li Chen, Hanxue Zhang, Chengen Xie, Ping Luo, Andreas Geiger, and Hongyang Li · 2023
Closest in time.
Scene as Occupancy
Wenwen Tong, Chonghao Sima, Tai Wang, Li Chen, Silei Wu, Hanming Deng, Yi Gu, Lewei Lu, Ping Luo, Dahua Lin, and Hongyang Li · 2023
Closest in time.
SurroundOcc: Multi-Camera 3D Occupancy Prediction for Autonomous Driving
Yi Wei, Linqing Zhao, Wenzhao Zheng, Zheng Zhu, Jie Zhou, and Jiwen Lu · 2023
Closest in time.
Policy Pre-training for Autonomous Driving via Self-supervised Geometric Modeling
Penghao Wu, Li Chen, Hongyang Li, Xiaosong Jia, Junchi Yan, and Yu Qiao · 2023
Closest in time.
SPOT: Scalable 3D Pre-training via Occupancy Prediction for Autonomous Driving
Xiangchao Yan, Runjian Chen, Bo Zhang, Jiakang Yuan, Xinyu Cai, Botian Shi, Wenqi Shao, Junchi Yan, Ping Luo, and Yu Qiao · 2023
Closest in time.
Distilling Focal Knowledge From Imperfect Expert for 3D Object Detection
Jia Zeng, Li Chen, Hanming Deng, Lewei Lu, Junchi Yan, Yu Qiao, and Hongyang Li · 2023
Closest in time.
Learning unsupervised world models for autonomous driving via discrete diffusion
Lunjun Zhang, Yuwen Xiong, Ze Yang, Sergio Casas, Rui Hu, and Raquel Urtasun · 2023
Closest in time.