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Bounded by the inherent ambiguity of depth perception, contemporary camera-based 3D object detection methods fall into the performance bottleneck.
Fast-mvsnet: Sparse-to-dense multi-view stereo with learned propagation and gauss-newton refinement
Yu, Z.; and Gao, S. 2020 · 1958
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Deep ordinal regression network for monocular depth estimation
Fu, H.; Gong, M.; Wang, C.; Batmanghelich, K.; and Tao, D. 2018 · 2011
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Predicting depth, surface normals and semantic labels with a common multi-scale convolutional architecture
Eigen, D.; and Fergus, R. 2015 · 2015
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Decoupled weight decay regularization
Loshchilov, I.; and Hutter, F. 2017 · 2017
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Second: Sparsely embedded convolutional detection
Yan, Y.; Mao, Y.; and Li, B. 2018 · 2018
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Mvsnet: Depth inference for unstructured multi-view stereo
Yao, Y.; Luo, Z.; Li, S.; Fang, T.; and Quan, L. 2018 · 2018
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M3d-rpn: Monocular 3d region proposal network for object detection
Brazil, G.; and Liu, X. 2019 · 2019
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Point-based multi-view stereo network
Chen, R.; Han, S.; Xu, J.; and Su, H. 2019 · 2019
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Pointpillars: Fast encoders for object detection from point clouds
Lang, A. H.; Vora, S.; Caesar, H.; Zhou, L.; Yang, J.; and Beijbom, O. 2019 · 2019
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Fcos: Fully convolutional one-stage object detection
Tian, Z.; Shen, C.; Chen, H.; and He, T. 2019 · 2019
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Mvscrf: Learning multi-view stereo with conditional random fields
Xue, Y.; Chen, J.; Wan, W.; Huang, Y.; Yu, C.; Li, T.; and Bao, J. 2019 · 2019
Cited alongside, same era.
Recurrent mvsnet for high-resolution multi-view stereo depth inference
Yao, Y.; Luo, Z.; Li, S.; Shen, T.; Fang, T.; and Quan, L. 2019 · 2019
Cited alongside, same era.
nuscenes: A multimodal dataset for autonomous driving
Caesar, H.; Bankiti, V.; Lang, A. H.; Vora, S.; Liong, V. E.; Xu, Q.; Krishnan, A.; Pan, Y.; Baldan, G.; and Beijbom, O. 2020 · 2020
Cited alongside, same era.
Monocular 3d object detection with decoupled structured polygon estimation and height-guided depth estimation
Cai, Y.; Li, B.; Jiao, Z.; Li, H.; Zeng, X.; and Wang, X. 2020 · 2020
Cited alongside, same era.
End-to-end object detection with transformers
Carion, N.; Massa, F.; Synnaeve, G.; Usunier, N.; Kirillov, A.; and Zagoruyko, S. 2020 · 2020
Cited alongside, same era.
Bevdet: High-performance multi-camera 3d object detection in bird-eye-view
Huang, J.; Huang, G.; Zhu, Z.; and Du, D. 2021 · 2021
Later among the works it cites.
Aa-rmvsnet: Adaptive aggregation recurrent multi-view stereo network
Wei, Z.; Zhu, Q.; Min, C.; Chen, Y.; and Wang, G. 2021 · 2021
Later among the works it cites.
Center-based 3d object detection and tracking
Yin, T.; Zhou, X.; and Krahenbuhl, P. 2021 · 2021
Later among the works it cites.
Deep Learning for Multi-View Stereo via Plane Sweep: A Survey
Zhu, Q.; Min, C.; Wei, Z.; Chen, Y.; and Wang, G. 2021 · 2021
Later among the works it cites.
Multi-View Depth Estimation by Fusing Single-View Depth Probability with Multi-View Geometry
Bae, G.; Budvytis, I.; and Cipolla, R. 2022 · 2022
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Ding, M.; Huo, Y.; Yi, H.; Wang, Z.; Shi, J.; Lu, Z.; and Luo, P. 2020 · 2020
Cited alongside, same era.
Cascade cost volume for high-resolution multi-view stereo and stereo matching
Gu, X.; Fan, Z.; Zhu, S.; Dai, Z.; Tan, F.; and Tan, P. 2020 · 2020
Cited alongside, same era.
Lift, splat, shoot: Encoding images from arbitrary camera rigs by implicitly unprojecting to 3d
Philion, J.; and Fidler, S. 2020 · 2020
Cited alongside, same era.
Adabins: Depth estimation using adaptive bins
Bhat, S. F.; Alhashim, I.; and Wonka, P. 2021 · 2021
Cited alongside, same era.
Depth map prediction from a single image using a multi-scale deep network
Eigen, D.; Puhrsch, C.; and Fergus, R. 2014a
Cited in the paper.
Depth map prediction from a single image using a multi-scale deep network
Eigen, D.; Puhrsch, C.; and Fergus, R. 2014b
Cited in the paper.
BEVDepth: Acquisition of Reliable Depth for Multi-view 3D Object Detection
Li, Y.; Ge, Z.; Yu, G.; Yang, J.; Wang, Z.; Shi, Y.; Sun, J.; and Li, Z. 2022a
Cited in the paper.
Huang, J.; and Huang, G. 2022 · 2022
Closest in time.
Monocular 3D Object Detection with Depth from Motion
Wang, T.; Pang, J.; and Lin, D. 2022 · 2022
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Bidirectional Hybrid LSTM Based Recurrent Neural Network for Multi-view Stereo
Wei, Z.; Zhu, Q.; Min, C.; Chen, Y.; and Wang, G. 2022 · 2022
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Mˆ 2BEV: Multi-Camera Joint 3D Detection and Segmentation with Unified Birds-Eye View Representation
Xie, E.; Yu, Z.; Zhou, D.; Philion, J.; Anandkumar, A.; Fidler, S.; Luo, P.; and Alvarez, J. M. 2022 · 2022
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