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3D object detection from multiple image views is a fundamental and challenging task for visual scene understanding.
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FitNets: Hints for thin deep nets
Adriana Romero, Nicolas Ballas, Samira Ebrahimi Kahou, Antoine Chassang, Carlo Gatta, and Yoshua Bengio · 2014
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Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, Jeff Dean, et al · 2015
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Monocular 3d object detection for autonomous driving
Xiaozhi Chen, Kaustav Kundu, Ziyu Zhang, Huimin Ma, Sanja Fidler, and Raquel Urtasun · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Fast and robust detection of fallen people from a mobile robot
Morris Antonello, Marco Carraro, Marco Pierobon, and Emanuele Menegatti · 2017
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Learning efficient object detection models with knowledge distillation
Guobin Chen, Wongun Choi, Xiang Yu, Tony Han, and Manmohan Chandraker · 2017
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SECOND: Sparsely embedded convolutional detection
Yan Yan, Yuxing Mao, and Bo Li · 2018
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PointPillars: Fast encoders for object detection from point clouds
Alex H Lang, Sourabh Vora, Holger Caesar, Lubing Zhou, Jiong Yang, and Oscar Beijbom · 2019
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Xingyi Zhou, Dequan Wang, and Philipp Krähenbühl · 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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End-to-end object detection with transformers
Nicolas Carion, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, and Sergey Zagoruyko · 2020
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MMDetection3D: OpenMMLab next-generation platform for general 3D object detection
MMDetection3D Contributors · 2020
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Learning depth-guided convolutions for monocular 3d object detection
Mingyu Ding, Yuqi Huo, Hongwei Yi, Zhe Wang, Jianping Shi, Zhiwu Lu, and Ping Luo · 2020
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Momentum contrast for unsupervised visual representation learning
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CenterMask: Real-time anchor-free instance segmentation
Youngwan Lee and Jongyoul Park · 2020
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Lift, splat, shoot: Encoding images from arbitrary camera rigs by implicitly unprojecting to 3d
Is pseudo-lidar needed for monocular 3d object detection?
Dennis Park, Rares Ambrus, Vitor Guizilini, Jie Li, and Adrien Gaidon · 2021
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Lidar point cloud guided monocular 3d object detection
Liang Peng, Fei Liu, Zhengxu Yu, Senbo Yan, Dan Deng, Zheng Yang, Haifeng Liu, and Deng Cai · 2021
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Object dgcnn: 3d object detection using dynamic graphs
Yue Wang and Justin M Solomon · 2021
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Center-based 3d object detection and tracking
Tianwei Yin, Xingyi Zhou, and Philipp Krahenbuhl · 2021
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Objects are different: Flexible monocular 3d object detection
Yunpeng Zhang, Jiwen Lu, and Jie Zhou · 2021
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BEVDet4D: Exploit temporal cues in multi-camera 3d object detection
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Jonah Philion and Sanja Fidler · 2020
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PV-RCNN: Point-voxel feature set abstraction for 3d object detection
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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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Improve object detection with feature-based knowledge distillation: Towards accurate and efficient detectors
Linfeng Zhang and Kaisheng Ma · 2020
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MonoDistill: Learning spatial features for monocular 3d object detection
Zhiyu Chong, Xinzhu Ma, Hong Zhang, Yuxin Yue, Haojie Li, Zhihui Wang, and Wanli Ouyang · 2021
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General instance distillation for object detection
Xing Dai, Zeren Jiang, Zhao Wu, Yiping Bao, Zhicheng Wang, Si Liu, and Erjin Zhou · 2021
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BEVDet: High-performance multi-camera 3d object detection in bird-eye-view
Junjie Huang, Guan Huang, Zheng Zhu, and Dalong Du · 2021
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Junjie Huang and Guan Huang · 2022
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LET-3D-AP: Longitudinal error tolerant 3d average precision for camera-only 3d detection
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M2BEV: Multi-camera joint 3d detection and segmentation with unified birds-eye view representation
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BEVerse: Unified perception and prediction in birds-eye-view for vision-centric autonomous driving
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Localization distillation for dense object detection
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