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Recent progress in 3D object detection from single images leverages monocular depth estimation as a way to produce 3D pointclouds, turning cameras into pseudo-lidar sensors.
Are we ready for autonomous driving? the kitti vision benchmark suite
Andreas Geiger, Philip Lenz, and Raquel Urtasun · 2012
Earlier work this paper cites.
Depth map prediction from a single image using a multi-scale deep network
David Eigen, Christian Puhrsch, and Rob Fergus · 2014
Earlier work this paper cites.
Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
Earlier work this paper cites.
3d object proposals for accurate object class detection
Xiaozhi Chen, Kaustav Kundu, Yukun Zhu, Andrew G Berneshawi, Huimin Ma, Sanja Fidler, and Raquel Urtasun · 2015
Earlier work this paper cites.
Depth and surface normal estimation from monocular images using regression on deep features and hierarchical crfs
Bo Li, Chunhua Shen, Yuchao Dai, Anton Van, and Mingyi He · 2015
Earlier work this paper cites.
Faster r-cnn: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2015
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
Deeper depth prediction with fully convolutional residual networks
Iro Laina, Christian Rupprecht, Vasileios Belagiannis, Federico Tombari, and Nassir Navab · 2016
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You only look once: Unified, real-time object detection
Joseph Redmon, Santosh Divvala, Ross Girshick, and Ali Farhadi · 2016
Earlier work this paper cites.
Unitbox: An advanced object detection network
Jiahui Yu, Yuning Jiang, Zhangyang Wang, Zhimin Cao, and Thomas Huang · 2016
Earlier work this paper cites.
Deep manta: A coarse-to-fine many-task network for joint 2d and 3d vehicle analysis from monocular image
Florian Chabot, Mohamed Chaouch, Jaonary Rabarisoa, Celine Teuliere, and Thierry Chateau · 2017
Earlier work this paper cites.
Multi-view 3d object detection network for autonomous driving
Xiaozhi Chen, Huimin Ma, Ji Wan, Bo Li, and Tian Xia · 2017
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Ssd-6d: Making rgb-based 3d detection and 6d pose estimation great again
Wadim Kehl, Fabian Manhardt, Federico Tombari, Slobodan Ilic, and Nassir Navab · 2017
Earlier work this paper cites.
Feature pyramid networks for object detection
Tsung-Yi Lin, Piotr Dollár, Ross Girshick, Kaiming He, Bharath Hariharan, and Serge Belongie · 2017
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2017
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3d bounding box estimation using deep learning and geometry
Arsalan Mousavian, Dragomir Anguelov, John Flynn, and Jana Kosecka · 2017
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Automatic differentiation in pytorch
Adam Paszke, Sam Gross, Soumith Chintala, Gregory Chanan, Edward Yang, Zachary DeVito, Zeming Lin, Alban Desmaison, Luca Antiga, and Adam Lerer · 2017
Earlier work this paper cites.
Demon: Depth and motion network for learning monocular stereo
Benjamin Ummenhofer, Huizhong Zhou, Jonas Uhrig, Nikolaus Mayer, Eddy Ilg, Alexey Dosovitskiy, and Thomas Brox · 2017
Earlier work this paper cites.
Sfm-net: Learning of structure and motion from video
Sudheendra Vijayanarasimhan, Susanna Ricco, Cordelia Schmid, Rahul Sukthankar, and Katerina Fragkiadaki · 2017
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Unsupervised learning of depth and ego-motion from video
Tinghui Zhou, Matthew Brown, Noah Snavely, and David G Lowe · 2017
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The earth ain’t flat: Monocular reconstruction of vehicles on steep and graded roads from a moving camera
Junaid Ahmed Ansari, Sarthak Sharma, Anshuman Majumdar, J. Krishna Murthy, and K. Madhava Krishna · 2018
Earlier work this paper cites.
Deep ordinal regression network for monocular depth estimation
Huan Fu, Mingming Gong, Chaohui Wang, Kayhan Batmanghelich, and Dacheng Tao · 2018
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Digging into self-supervised monocular depth estimation
Clément Godard, Oisin Mac Aodha, and Gabriel Brostow · 2018
Earlier work this paper cites.
Squeeze-and-excitation networks
Jie Hu, Li Shen, and Gang Sun · 2018
Earlier work this paper cites.
3d-rcnn: Instance-level 3d object reconstruction via render-and-compare
Abhijit Kundu, Yin Li, and James M. Rehg · 2018
Earlier work this paper cites.
Single-image depth estimation based on fourier domain analysis
Jae-Han Lee, Minhyeok Heo, Kyung-Rae Kim, and Chang-Su Kim · 2018
Earlier work this paper cites.
Superdepth: Self-supervised, super-resolved monocular depth estimation
Sudeep Pillai, Rares Ambrus, and Adrien Gaidon · 2018
Cited alongside, same era.
Frustum pointnets for 3d object detection from rgb-d data
Charles R Qi, Wei Liu, Chenxia Wu, Hao Su, and Leonidas J Guibas · 2018
Cited alongside, same era.
Geonet: Geometric neural network for joint depth and surface normal estimation
Xiaojuan Qi, Renjie Liao, Zhengzhe Liu, Raquel Urtasun, and Jiaya Jia · 2018
Cited alongside, same era.
Orthographic feature transform for monocular 3d object detection
Thomas Roddick, Alex Kendall, and Roberto Cipolla · 2018
Cited alongside, same era.
Pixor: Real-time 3d object detection from point clouds
Bin Yang, Wenjie Luo, and Raquel Urtasun · 2018
Cited alongside, same era.
Disentangling monocular 3d object detection
Andrea Simonelli, Samuel Rota Bulo, Lorenzo Porzi, Manuel López-Antequera, and Peter Kontschieder · 2019
Later among the works it cites.
Learning 2d to 3d lifting for object detection in 3d for autonomous vehicles
Siddharth Srivastava, Frédéric Jurie, and Gaurav Sharma · 2019
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Fcos: Fully convolutional one-stage object detection
Zhi Tian, Chunhua Shen, Hao Chen, and Tong He · 2019
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Refinedmpl: Refined monocular pseudolidar for 3d object detection in autonomous driving
Jean Marie Uwabeza Vianney, Shubhra Aich, and Bingbing Liu · 2019
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Pseudo-lidar from visual depth estimation: Bridging the gap in 3d object detection for autonomous driving
Yan Wang, Wei-Lun Chao, Divyansh Garg, Bharath Hariharan, Mark Campbell, and Kilian Q. Weinberger · 2019
Later among the works it cites.
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Deep layer aggregation
Fisher Yu, Dequan Wang, Evan Shelhamer, and Trevor Darrell · 2018
Cited alongside, same era.
Stereo magnification: Learning view synthesis using multiplane images
Tinghui Zhou, Richard Tucker, John Flynn, Graham Fyffe, and Noah Snavely · 2018
Cited alongside, same era.
Monocular 3d object detection via geometric reasoning on keypoints
Ivan Barabanau, Alexey Artemov, Evgeny Burnaev, and Vyacheslav Murashkin · 2019
Cited alongside, same era.
M3d-rpn: Monocular 3d region proposal network for object detection
Garrick Brazil and Xiaoming Liu · 2019
Cited alongside, same era.
3d bounding box estimation for autonomous vehicles by cascaded geometric constraints and depurated 2d detections using 3d results, 2019
Jiaojiao Fang, Lingtao Zhou, and Guizhong Liu · 2019
Cited alongside, same era.
Robust semi-supervised monocular depth estimation with reprojected distances
Vitor Guizilini, Jie Li, Rares Ambrus, Sudeep Pillai, and Adrien Gaidon · 2019
Cited alongside, same era.
Mono3d++: Monocular 3d vehicle detection with two-scale 3d hypotheses and task priors
Tong He and Stefano Soatto · 2019
Cited alongside, same era.
Monocular 3d object detection with pseudo-lidar point cloud
Xinshuo Weng and Kris Kitani · 2019
Later among the works it cites.
Pseudo-lidar++: Accurate depth for 3d object detection in autonomous driving
Yurong You, Yan Wang, Wei-Lun Chao, Divyansh Garg, Geoff Pleiss, Bharath Hariharan, Mark Campbell, and Kilian Q Weinberger · 2019
Later among the works it cites.
Xingyi Zhou, Dequan Wang, and Philipp Krähenbühl · 2019
Later among the works it cites.
Kinematic 3d object detection in monocular video
Garrick Brazil, Gerard Pons-Moll, Xiaoming Liu, and Bernt Schiele · 2020
Later among the works it 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
Later among the works it cites.
Monopair: Monocular 3d object detection using pairwise spatial relationships
Yongjian Chen, Lei Tai, Kai Sun, and Mingyang Li · 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
Later among the works it cites.
3d packing for self-supervised monocular depth estimation
Vitor Guizilini, Rares Ambrus, Sudeep Pillai, Allan Raventos, and Adrien Gaidon · 2020
Later among the works it cites.
3d packing for self-supervised monocular depth estimation
Vitor Guizilini, Rares Ambrus, Sudeep Pillai, Allan Raventos, and Adrien Gaidon · 2020
Later among the works it cites.
Semantically-guided representation learning for self-supervised monocular depth
Vitor Guizilini, Rui Hou, Jie Li, Rares Ambrus, and Adrien Gaidon · 2020
Later among the works it cites.
Self-supervised monocular depth estimation: Solving the dynamic object problem by semantic guidance
Marvin Klingner, Jan-Aike Termöhlen, Jonas Mikolajczyk, and Tim Fingscheidt · 2020
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Centermask: Real-time anchor-free instance segmentation
Youngwan Lee and Jongyoul Park · 2020
Later among the works it cites.
Smoke: single-stage monocular 3d object detection via keypoint estimation
Zechen Liu, Zizhang Wu, and Roland Tóth · 2020
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Rethinking pseudo-lidar representation
Xinzhu Ma, Shinan Liu, Zhiyi Xia, Hongwen Zhang, Xingyu Zeng, and Wanli Ouyang · 2020
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End-to-end pseudo-lidar for image-based 3d object detection
Rui Qian, Divyansh Garg, Yan Wang, Yurong You, Serge Belongie, Bharath Hariharan, Mark Campbell, Kilian Q Weinberger, and Wei-Lun Chao · 2020
Later among the works it cites.
Disentangling monocular 3d object detection: From single to multi-class recognition
Andrea Simonelli, Samuel Rota Bulo, Lorenzo Porzi, Manuel Lopez Antequera, and Peter Kontschieder · 2020
Later among the works it cites.
Demystifying pseudo-lidar for monocular 3d object detection
Andrea Simonelli, Samuel Rota Bulò, Lorenzo Porzi, Peter Kontschieder, and Elisa Ricci · 2020
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Task-aware monocular depth estimation for 3d object detection
Xinlong Wang, Wei Yin, Tao Kong, Yuning Jiang, Lei Li, and Chunhua Shen · 2020
Later among the works it cites.
Train in germany, test in the usa: Making 3d object detectors generalize
Yan Wang, Xiangyu Chen, Yurong You, Li Erran Li, Bharath Hariharan, Mark Campbell, Kilian Q Weinberger, and Wei-Lun Chao · 2020
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Fcos3d: Fully convolutional one-stage monocular 3d object detection
Tai Wang, Xinge Zhu, Jiangmiao Pang, and Dahua Lin · 2021
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