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Sensor fusion is an essential topic in many perception systems, such as autonomous driving and robotics.
“Multi-view 3d object detection network for autonomous driving,”
Xiaozhi Chen, Huimin Ma, Ji Wan, Bo Li, and Tian Xia, · 1915
Earlier work this paper cites.
“Unsupervised learning of spoken language with visual context,”
David Harwath, Antonio Torralba, and James Glass, · 2016
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
Earlier work this paper cites.
“Deep continuous fusion for multi-sensor 3d object detection,”
Ming Liang, Bin Yang, Shenlong Wang, and Raquel Urtasun, · 2018
Earlier work this paper cites.
“Voxelnet: End-to-end learning for point cloud based 3d object detection,”
Yin Zhou and Oncel Tuzel, · 2018
Earlier work this paper cites.
“Pointpillars: Fast encoders for object detection from point clouds,”
Alex H Lang, Sourabh Vora, Holger Caesar, Lubing Zhou, Jiong Yang, and Oscar Beijbom, · 2019
Earlier work this paper cites.
“Clocs: Camera-lidar object candidates fusion for 3d object detection,”
Su Pang, Daniel Morris, and Hayder Radha, · 2020
Earlier work this paper cites.
“Pointpainting: Sequential fusion for 3d object detection,”
Sourabh Vora, Alex H Lang, Bassam Helou, and Oscar Beijbom, · 2020
Earlier work this paper cites.
“End-to-end object detection with transformers,”
Nicolas Carion, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, and Sergey Zagoruyko, · 2020
Earlier work this paper cites.
“Lift, splat, shoot: Encoding images from arbitrary camera rigs by implicitly unprojecting to 3d,”
Jonah Philion and Sanja Fidler, · 2020
Earlier work this paper cites.
“Deformable detr: Deformable transformers for end-to-end object detection,”
Xizhou Zhu, Weijie Su, Lewei Lu, Bin Li, Xiaogang Wang, and Jifeng Dai, · 2020
Cited alongside, same era.
“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
Cited alongside, same era.
“Center-based 3d object detection and tracking,”
Tianwei Yin, Xingyi Zhou, and Philipp Krahenbuhl, · 2021
Cited alongside, same era.
“4d-net for learned multi-modal alignment,”
AJ Piergiovanni, Vincent Casser, Michael S Ryoo, and Anelia Angelova, · 2021
Cited alongside, same era.
“Efficient detr: improving end-to-end object detector with dense prior,”
Zhuyu Yao, Jiangbo Ai, Boxun Li, and Chi Zhang, · 2021
Cited alongside, same era.
“Unifying voxel-based representation with transformer for 3d object detection,”
Yanwei Li, Yilun Chen, Xiaojuan Qi, Zeming Li, Jian Sun, and Jiaya Jia, · 2022
Later among the works it cites.
“Futr3d: A unified sensor fusion framework for 3d detection,”
Xuanyao Chen, Tianyuan Zhang, Yue Wang, Yilun Wang, and Hang Zhao, · 2022
Later among the works it cites.
“Lift: Learning 4d lidar image fusion transformer for 3d object detection,”
Yihan Zeng, Da Zhang, Chunwei Wang, Zhenwei Miao, Ting Liu, Xin Zhan, Dayang Hao, and Chao Ma, · 2022
Later among the works it cites.
“Deepinteraction: 3d object detection via modality interaction,”
Zeyu Yang, Jiaqi Chen, Zhenwei Miao, Wei Li, Xiatian Zhu, and Li Zhang, · 2022
Later among the works it cites.
“Autoalign: Pixel-instance feature aggregation for multi-modal 3d object detection,”
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“Detr3d: 3d object detection from multi-view images via 3d-to-2d queries,”
Yue Wang, Vitor Campagnolo Guizilini, Tianyuan Zhang, Yilun Wang, Hang Zhao, and Justin Solomon, · 2022
Cited alongside, same era.
“Bevformer: Learning bird’s-eye-view representation from multi-camera images via spatiotemporal transformers,”
Zhiqi Li, Wenhai Wang, Hongyang Li, Enze Xie, Chonghao Sima, Tong Lu, Yu Qiao, and Jifeng Dai, · 2022
Cited alongside, same era.
“Bevfusion: Multi-task multi-sensor fusion with unified bird’s-eye view representation,”
Zhijian Liu, Haotian Tang, Alexander Amini, Xinyu Yang, Huizi Mao, Daniela Rus, and Song Han, · 2022
Cited alongside, same era.
“Transfuser: Imitation with transformer-based sensor fusion for autonomous driving,”
Kashyap Chitta, Aditya Prakash, Bernhard Jaeger, Zehao Yu, Katrin Renz, and Andreas Geiger, · 2022
Cited alongside, same era.
“Transfusion: Robust lidar-camera fusion for 3d object detection with transformers,”
Xuyang Bai, Zeyu Hu, Xinge Zhu, Qingqiu Huang, Yilun Chen, Hongbo Fu, and Chiew-Lan Tai, · 2022
Cited alongside, same era.
Zehui Chen, Zhenyu Li, Shiquan Zhang, Liangji Fang, Qinghong Jiang, Feng Zhao, Bolei Zhou, and Hang Zhao, · 2022
Later among the works it cites.
“3m3d: Multi-view, multi-path, multi-representation for 3d object detection,”
Jongwoo Park, Apoorv Singh, and Varun Bankiti, · 2023
Closest in time.
“Surround-view vision-based 3d detection for autonomous driving: A survey,”
Apoorv Singh and Varun Bankiti, · 2023
Closest in time.
“Vision-radar fusion for robotics bev detections: A survey,”
Apoorv Singh, · 2023
Closest in time.
“Cross modal transformer via coordinates encoding for 3d object dectection,”
Junjie Yan, Yingfei Liu, Jianjian Sun, Fan Jia, Shuailin Li, Tiancai Wang, and Xiangyu Zhang, · 2023
Closest in time.