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Recently 3D object detection from surround-view images has made notable advancements with its low deployment cost.
An image is worth 16x16 words: Transformers for image recognition at scale
Dosovitskiy, A.; Beyer, L.; Kolesnikov, A.; Weissenborn, D.; Zhai, X.; Unterthiner, T.; Dehghani, M.; Minderer, M.; Heigold, G.; Gelly, S.; et al. 2020 · 2010
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Deformable detr: Deformable transformers for end-to-end object detection
Zhu, X.; Su, W.; Lu, L.; Li, B.; Wang, X.; and Dai, J. 2020 · 2010
Earlier work this paper cites.
Microsoft coco: Common objects in context
Lin, T.-Y.; Maire, M.; Belongie, S.; Hays, J.; Perona, P.; Ramanan, D.; Dollár, P.; and Zitnick, C. L. 2014 · 2014
Earlier work this paper cites.
Deep residual learning for image recognition
He, K.; Zhang, X.; Ren, S.; and Sun, J. 2016 · 2016
Earlier work this paper cites.
Feature pyramid networks for object detection
Lin, T.-Y.; Dollár, P.; Girshick, R.; He, K.; Hariharan, B.; and Belongie, S. 2017 · 2017
Earlier work this paper cites.
Decoupled weight decay regularization
Loshchilov, I.; and Hutter, F. 2017 · 2017
Earlier work this paper cites.
Attention is all you need
Vaswani, A.; Shazeer, N.; Parmar, N.; Uszkoreit, J.; Jones, L.; Gomez, A. N.; Kaiser, Ł.; and Polosukhin, I. 2017 · 2017
Earlier work this paper cites.
Squeeze-and-excitation networks
Hu, J.; Shen, L.; and Sun, G. 2018 · 2018
Earlier work this paper cites.
An energy and GPU-computation efficient backbone network for real-time object detection
Lee, Y.; Hwang, J.-w.; Lee, S.; Bae, Y.; and Park, J. 2019 · 2019
Earlier work this paper cites.
Objects365: A large-scale, high-quality dataset for object detection
Shao, S.; Li, Z.; Zhang, T.; Peng, C.; Yu, G.; Zhang, X.; Li, J.; and Sun, J. 2019 · 2019
Earlier work this paper cites.
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
Earlier work this paper cites.
End-to-end object detection with transformers
Carion, N.; Massa, F.; Synnaeve, G.; Usunier, N.; Kirillov, A.; and Zagoruyko, S. 2020 · 2020
Earlier work this paper cites.
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.
Yolox: Exceeding yolo series in 2021
Ge, Z.; Liu, S.; Wang, F.; Li, Z.; and Sun, J. 2021 · 2021
Cited alongside, same era.
Bevdet: High-performance multi-camera 3d object detection in bird-eye-view
Huang, J.; Huang, G.; Zhu, Z.; Ye, Y.; and Du, D. 2021 · 2021
Cited alongside, same era.
Categorical depth distribution network for monocular 3d object detection
Reading, C.; Harakeh, A.; Chae, J.; and Waslander, S. L. 2021 · 2021
Cited alongside, same era.
Fcos3d: Fully convolutional one-stage monocular 3d object detection
Wang, T.; Zhu, X.; Pang, J.; and Lin, D. 2021 · 2021
Cited alongside, same era.
M2BEV: 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
Later among the works it cites.
MonoDETR: depth-guided transformer for monocular 3D object detection
Zhang, R.; Qiu, H.; Wang, T.; Guo, Z.; Xu, X.; Qiao, Y.; Gao, P.; and Li, H. 2022 · 2022
Later among the works it cites.
Temporal Enhanced Training of Multi-view 3D Object Detector via Historical Object Prediction
Zong, Z.; Jiang, D.; Song, G.; Xue, Z.; Su, J.; Li, H.; and Liu, Y. 2023 · 2022
Later among the works it cites.
Voxelnext: Fully sparse voxelnet for 3d object detection and tracking
Chen, Y.; Liu, J.; Zhang, X.; Qi, X.; and Jia, J. 2023 · 2023
Closest in time.
Polarformer: Multi-camera 3d object detection with polar transformer
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Center-based 3d object detection and tracking
Yin, T.; Zhou, X.; and Krahenbuhl, P. 2021 · 2021
Cited alongside, same era.
Fully sparse 3d object detection
Fan, L.; Wang, F.; Wang, N.; and ZHANG, Z.-X. 2022 · 2022
Cited alongside, same era.
Bevdet4d: Exploit temporal cues in multi-camera 3d object detection
Huang, J.; and Huang, G. 2022 · 2022
Cited alongside, same era.
Sparse4d: Multi-view 3d object detection with sparse spatial-temporal fusion
Lin, X.; Lin, T.; Pei, Z.; Huang, L.; and Su, Z. 2022 · 2022
Cited alongside, same era.
Time will tell: New outlooks and a baseline for temporal multi-view 3d object detection
Park, J.; Xu, C.; Yang, S.; Keutzer, K.; Kitani, K.; Tomizuka, M.; and Zhan, W. 2022 · 2022
Cited alongside, same era.
Focal-PETR: Embracing Foreground for Efficient Multi-Camera 3D Object Detection
Wang, S.; Jiang, X.; and Li, Y. 2022 · 2022
Cited alongside, same era.
Detr3d: 3d object detection from multi-view images via 3d-to-2d queries
Wang, Y.; Guizilini, V. C.; Zhang, T.; Wang, Y.; Zhao, H.; and Solomon, J. 2022 · 2022
Cited alongside, same era.
Jiang, Y.; Zhang, L.; Miao, Z.; Zhu, X.; Gao, J.; Hu, W.; and Jiang, Y.-G. 2023 · 2023
Closest in time.
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. 2023 · 2023
Closest in time.
Sparse4D v2: Recurrent Temporal Fusion with Sparse Model
Lin, X.; Lin, T.; Pei, Z.; Huang, L.; and Su, Z. 2023 · 2023
Closest in time.
Towards Better 3D Knowledge Transfer via Masked Image Modeling for Multi-view 3D Understanding
Liu, J.; Wang, T.; Liu, B.; Zhang, Q.; Liu, Y.; and Li, H. 2023 · 2023
Closest in time.
Argoverse 2: Next generation datasets for self-driving perception and forecasting
Wilson, B.; Qi, W.; Agarwal, T.; Lambert, J.; Singh, J.; Khandelwal, S.; Pan, B.; Kumar, R.; Hartnett, A.; Pontes, J. K.; et al. 2023 · 2023
Closest in time.
BEVFormer v2: Adapting Modern Image Backbones to Bird’s-Eye-View Recognition via Perspective Supervision
Yang, C.; Chen, Y.; Tian, H.; Tao, C.; Zhu, X.; Zhang, Z.; Huang, G.; Li, H.; Qiao, Y.; Lu, L.; et al. 2023 · 2023
Closest in time.
A Simple Baseline for Multi-Camera 3D Object Detection
Zhang, Y.; Zheng, W.; Zhu, Z.; Huang, G.; Lu, J.; and Zhou, J. 2023 · 2023
Closest in time.