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Recognizing scenes and objects in 3D from a single image is a longstanding goal of computer vision with applications in robotics and AR/VR.
The quickhull algorithm for convex hulls
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Elsayed Hemayed · 2003
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Recovering the spatial layout of cluttered rooms
Varsha Hedau, Derek Hoiem, and David Forsyth · 2009
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Geometric reasoning for single image structure recovery
David C Lee, Martial Hebert, and Takeo Kanade · 2009
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Are we ready for autonomous driving? the KITTI vision benchmark suite
Andreas Geiger, Philip Lenz, and Raquel Urtasun · 2012
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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
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Arun Mallya and Svetlana Lazebnik · 2015
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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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ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, Alexander Berg, and Li Fei-Fei · 2015
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SUN RGB-D: A RGB-D scene understanding benchmark suite
Shuran Song, Samuel Lichtenberg, and Jianxiong Xiao · 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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Delay: Robust spatial layout estimation for cluttered indoor scenes
Saumitro Dasgupta, Kuan Fang, Kevin Chen, and Silvio Savarese · 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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SSD: Single shot multibox detector
Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, and Alexander Berg · 2016
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You only look once: Unified, real-time object detection
Joseph Redmon, Santosh Divvala, Ross Girshick, and Ali Farhadi · 2016
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ScanNet: Richly-annotated 3D reconstructions of indoor scenes
Angela Dai, Angel X. Chang, Manolis Savva, Maciej Halber, Thomas Funkhouser, and Matthias Nießner · 2017
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Mask R-CNN
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick · 2017
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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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Focal loss for dense object detection
Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He, and Piotr Dollár · 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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Deep Ordinal Regression Network for Monocular Depth Estimation
Huan Fu, Mingming Gong, Chaohui Wang, Kayhan Batmanghelich, and Dacheng Tao · 2018
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Cooperative holistic scene understanding: Unifying 3D object, layout, and camera pose estimation
Siyuan Huang, Siyuan Qi, Yinxue Xiao, Yixin Zhu, Ying Nian Wu, and Song-Chun Zhu · 2018
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Joint 3D proposal generation and object detection from view aggregation
Jason Ku, Melissa Mozifian, Jungwook Lee, Ali Harakeh, and Steven Waslander · 2018
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3D-RCNN: Instance-level 3D object reconstruction via render-and-compare
Abhijit Kundu, Yin Li, and James Rehg · 2018
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CornerNet: Detecting objects as paired keypoints
Hei Law and Jia Deng · 2018
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Frustum pointnets for 3D object detection from RGB-D data
Charles Qi, Wei Liu, Chenxia Wu, Hao Su, and Leonidas Guibas · 2018
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Factoring shape, pose, and layout from the 2D image of a 3D scene
Shubham Tulsiani, Saurabh Gupta, David Fouhey, Alexei Efros, and Jitendra Malik · 2018
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Deep layer aggregation
Fisher Yu, Dequan Wang, Evan Shelhamer, and Trevor Darrell · 2018
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Scan2CAD: Learning CAD model alignment in RGB-D scans
Armen Avetisyan, Manuel Dahnert, Angela Dai, Manolis Savva, Angel X Chang, and Matthias Nießner · 2019
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MonoFENet: Monocular 3D object detection with feature enhancement networks
Wentao Bao, Bin Xu, and Zhenzhong Chen · 2019
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M3D-RPN: Monocular 3D region proposal network for object detection
Garrick Brazil and Xiaoming Liu · 2019
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Argoverse: 3D tracking and forecasting with rich maps
Ming-Fang Chang, John Lambert, Patsorn Sangkloy, Jagjeet Singh, Slawomir Bak, Andrew Hartnett, De Wang, Peter Carr, Simon Lucey, Deva Ramanan, et al · 2019
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MMDetection: Open mmlab detection toolbox and benchmark
Kai Chen, Jiaqi Wang, Jiangmiao Pang, Yuhang Cao, Yu Xiong, Xiaoxiao Li, Shuyang Sun, Wansen Feng, Ziwei Liu, Jiarui Xu, Zheng Zhang, Dazhi Cheng, Chenchen Zhu, Tianheng Cheng, Qijie Zhao, Buyu Li, Xin Lu, Rui Zhu, Yue Wu, Jifeng Dai, Jingdong Wang, Jianping Shi, Wanli Ouyang, Chen Change Loy, and Dahua Lin · 2019
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Mesh R-CNN
Georgia Gkioxari, Jitendra Malik, and Justin Johnson · 2019
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LVIS: A dataset for large vocabulary instance segmentation
Agrim Gupta, Piotr Dollar, and Ross Girshick · 2019
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The apolloscape open dataset for autonomous driving and its application
Xinyu Huang, Peng Wang, Xinjing Cheng, Dingfu Zhou, Qichuan Geng, and Ruigang Yang · 2019
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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 Weinberger · 2020
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IAFA: Instance-aware feature aggregation for 3D object detection from a single image
Dingfu Zhou, Xibin Song, Yuchao Dai, Junbo Yin, Feixiang Lu, Miao Liao, Jin Fang, and Liangjun Zhang · 2020
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Objectron: A large scale dataset of object-centric videos in the wild with pose annotations
Adel Ahmadyan, Liangkai Zhang, Artsiom Ablavatski, Jianing Wei, and Matthias Grundmann · 2021
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ARKitScenes - a diverse real-world dataset for 3D indoor scene understanding using mobile RGB-D data
Gilad Baruch, Zhuoyuan Chen, Afshin Dehghan, Tal Dimry, Yuri Feigin, Peter Fu, Thomas Gebauer, Brandon Joffe, Daniel Kurz, Arik Schwartz, and Elad Shulman · 2021
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MonoRUn: Monocular 3D object detection by reconstruction and uncertainty propagation
Hansheng Chen, Yuyao Huang, Wei Tian, Zhong Gao, and Lu Xiong · 2021
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Level 5 perception dataset 2020
R. Kesten, M. Usman, J. Houston, T. Pandya, K. Nadhamuni, A. Ferreira, M. Yuan, B. Low, A. Jain, P. Ondruska, S. Omari, S. Shah, A. Kulkarni, A. Kazakova, C. Tao, L. Platinsky, W. Jiang, and V. Shet · 2019
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3D-RelNet: Joint object and relational network for 3D prediction
Nilesh Kulkarni, Ishan Misra, Shubham Tulsiani, and Abhinav Gupta · 2019
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Accurate monocular 3D object detection via color-embedded 3D reconstruction for autonomous driving
Xinzhu Ma, Zhihui Wang, Haojie Li, Pengbo Zhang, Wanli Ouyang, and Xin Fan · 2019
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Disentangling monocular 3D object detection
Andrea Simonelli, Samuel Rota Bulo, Lorenzo Porzi, Manuel López-Antequera, and Peter Kontschieder · 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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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 Weinberger · 2019
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Detectron2
Yuxin Wu, Alexander Kirillov, Francisco Massa, Wan-Yen Lo, and Ross Girshick · 2019
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Aug3D-RPN: Improving monocular 3D object detection by synthetic images with virtual depth
Chenhang He, Jianqiang Huang, Xian-Sheng Hua, and Lei Zhang · 2021
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GrooMeD-NMS: Grouped mathematically differentiable NMS for monocular 3D object detection
Abhinav Kumar, Garrick Brazil, and Xiaoming Liu · 2021
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Deep line encoding for monocular 3D object detection and depth prediction
Ce Liu, Shuhang Gu, Luc Van Gool, and Radu Timofte · 2021
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Ground-aware monocular 3D object detection for autonomous driving
Yuxuan Liu, Yuan Yixuan, and Ming Liu · 2021
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Autoshape: Real-time shape-aware monocular 3D object detection
Zongdai Liu, Dingfu Zhou, Feixiang Lu, Jin Fang, and Liangjun Zhang · 2021
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Geometry uncertainty projection network for monocular 3D object detection
Yan Lu, Xinzhu Ma, Lei Yang, Tianzhu Zhang, Yating Liu, Qi Chu, Junjie Yan, and Wanli Ouyang · 2021
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Delving into localization errors for monocular 3D object detection
Xinzhu Ma, Yinmin Zhang, Dan Xu, Dongzhan Zhou, Shuai Yi, Haojie Li, and Wanli Ouyang · 2021
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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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Categorical depth distribution network for monocular 3D object detection
Cody Reading, Ali Harakeh, Julia Chae, and Steven Waslander · 2021
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Hypersim: A photorealistic synthetic dataset for holistic indoor scene understanding
Mike Roberts, Jason Ramapuram, Anurag Ranjan, Atulit Kumar, Miguel Bautista, Nathan Paczan, Russ Webb, and Joshua Susskind · 2021
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Depth-conditioned dynamic message propagation for monocular 3D object detection
Li Wang, Liang Du, Xiaoqing Ye, Yanwei Fu, Guodong Guo, Xiangyang Xue, Jianfeng Feng, and Li Zhang · 2021
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Progressive coordinate transforms for monocular 3D object detection
Li Wang, Li Zhang, Yi Zhu, Zhi Zhang, Tong He, Mu Li, and Xiangyang Xue · 2021
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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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Objects are different: Flexible monocular 3D object detection
Yunpeng Zhang, Jiwen Lu, and Jie Zhou · 2021
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Monocular 3D object detection: An extrinsic parameter free approach
Yunsong Zhou, Yuan He, Hongzi Zhu, Cheng Wang, Hongyang Li, and Qinhong Jiang · 2021
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The devil is in the task: Exploiting reciprocal appearance-localization features for monocular 3D object detection
Zhikang Zou, Xiaoqing Ye, Liang Du, Xianhui Cheng, Xiao Tan, Li Zhang, Jianfeng Feng, Xiangyang Xue, and Errui Ding · 2021
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https://www.cvlibs.net/datasets/kitti/eval_object.php?obj_benchmark=3d
KITTI server · 2022
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Pseudo-stereo for monocular 3D object detection in autonomous driving
Yi-Nan Chen, Hang Dai, and Yong Ding · 2022
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Homography loss for monocular 3D object detection
Jiaqi Gu, Bojian Wu, Lubin Fan, Jianqiang Huang, Shen Cao, Zhiyu Xiang, and Xian-Sheng Hua · 2022
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MonoDTR: Monocular 3D object detection with depth-aware transformer
Kuan-Chih Huang, Tsung-Han Wu, Hung-Ting Su, and Winston Hsu · 2022
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Learning open-world object proposals without learning to classify
Dahun Kim, Tsung-Yi Lin, Anelia Angelova, In Kweon, and Weicheng Kuo · 2022
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DEVIANT: Depth EquiVarIAnt NeTwork for monocular 3D object detection
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Learning auxiliary monocular contexts helps monocular 3D object detection
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ImVoxelNet: Image to voxels projection for monocular and multi-view general-purpose 3D object detection
Danila Rukhovich, Anna Vorontsova, and Anton Konushin · 2022
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Probabilistic and geometric depth: Detecting objects in perspective
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