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Although DETR-based 3D detectors can simplify the detection pipeline and achieve direct sparse predictions, their performance still lags behind dense detectors with post-processing for 3D object detection from point clouds.
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Submanifold sparse convolutional networks
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Tsung-Yi Lin, Piotr Dollár, Ross Girshick, Kaiming He, Bharath Hariharan, and Serge Belongie · 2017
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Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He, and Piotr Dollár · 2017
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Han Hu, Jiayuan Gu, Zheng Zhang, Jifeng Dai, and Yichen Wei · 2018
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Voxelnet: End-to-end learning for point cloud based 3d object detection
Yin Zhou and Oncel Tuzel · 2018
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Decoupled weight decay regularization
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Shaoshuai Shi, Xiaogang Wang, and Hongsheng Li · 2019
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Nicolas Carion, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, and Sergey Zagoruyko · 2020
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Mathilde Caron, Ishan Misra, Julien Mairal, Priya Goyal, Piotr Bojanowski, and Armand Joulin · 2020
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Scalability in perception for autonomous driving: Waymo open dataset
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Pointaugmenting: Cross-modal augmentation for 3d object detection
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End-to-end object detection with fully convolutional network
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G-detkd: Towards general distillation framework for object detectors via contrastive and semantic-guided feature imitation
Lewei Yao, Renjie Pi, Hang Xu, Wei Zhang, Zhenguo Li, and Tong Zhang · 2021
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Embracing single stride 3d object detector with sparse transformer
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Bridging the gap between anchor-based and anchor-free detection via adaptive training sample selection
Shifeng Zhang, Cheng Chi, Yongqiang Yao, Zhen Lei, and Stan Z Li · 2020
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Eqco: Equivalent rules for self-supervised contrastive learning
Benjin Zhu, Junqiang Huang, Zeming Li, Xiangyu Zhang, and Jian Sun · 2020
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Autoassign: Differentiable label assignment for dense object detection
Benjin Zhu, Jianfeng Wang, Zhengkai Jiang, Fuhang Zong, Songtao Liu, Zeming Li, and Jian Sun · 2020
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Deformable detr: Deformable transformers for end-to-end object detection
Xizhou Zhu, Weijie Su, Lewei Lu, Bin Li, Xiaogang Wang, and Jifeng Dai · 2020
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Ota: Optimal transport assignment for object detection
Zheng Ge, Songtao Liu, Zeming Li, Osamu Yoshie, and Jian Sun · 2021
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Contrastive object detection using knowledge graph embeddings
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Lue Fan, Ziqi Pang, Tianyuan Zhang, Yu-Xiong Wang, Hang Zhao, Feng Wang, Naiyan Wang, and Zhaoxiang Zhang · 2022
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Fully sparse 3d object detection
Lue Fan, Feng Wang, Naiyan Wang, and Zhaoxiang Zhang · 2022
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Yihan Hu, Zhuangzhuang Ding, Runzhou Ge, Wenxin Shao, Li Huang, Kun Li, and Qiang Liu · 2022
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Detrs with hybrid matching
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Feng Li, Hao Zhang, Shilong Liu, Jian Guo, Lionel M Ni, and Lei Zhang · 2022
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Zixiang Zhou, Xiangchen Zhao, Yu Wang, Panqu Wang, and Hassan Foroosh · 2022
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