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Recent advance in 2D CNNs has revealed that large kernels are important.
Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Microsoft COCO: common objects in context
Tsung-Yi Lin, Michael Maire, Serge J. Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C. Lawrence Zitnick · 2014
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Deep convolutional neural network for image deconvolution
Li Xu, Jimmy S. J. Ren, Ce Liu, and Jiaya Jia · 2014
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Lei Jimmy Ba, Jamie Ryan Kiros, and Geoffrey E. Hinton · 2016
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Gaussian error linear units (gelus)
Dan Hendrycks and Kevin Gimpel · 2016
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Multi-scale context aggregation by dilated convolutions
Fisher Yu and Vladlen Koltun · 2016
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Rethinking atrous convolution for semantic image segmentation
Liang-Chieh Chen, George Papandreou, Florian Schroff, and Hartwig Adam · 2017
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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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Deformable convolutional networks
Jifeng Dai, Haozhi Qi, Yuwen Xiong, Yi Li, Guodong Zhang, Han Hu, and Yichen Wei · 2017
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Mobilenets: Efficient convolutional neural networks for mobile vision applications
Andrew G. Howard, Menglong Zhu, Bo Chen, Dmitry Kalenichenko, Weijun Wang, Tobias Weyand, Marco Andreetto, and Hartwig Adam · 2017
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Active convolution: Learning the shape of convolution for image classification
Yunho Jeon and Junmo Kim · 2017
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Large kernel matters - improve semantic segmentation by global convolutional network
Chao Peng, Xiangyu Zhang, Gang Yu, Guiming Luo, and Jian Sun · 2017
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Pointnet: Deep learning on point sets for 3d classification and segmentation
Charles Ruizhongtai Qi, Hao Su, Kaichun Mo, and Leonidas J. Guibas · 2017
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Pointnet++: Deep hierarchical feature learning on point sets in a metric space
Charles Ruizhongtai Qi, Li Yi, Hao Su, and Leonidas J. Guibas · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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3d semantic segmentation with submanifold sparse convolutional networks
Benjamin Graham, Martin Engelcke, and Laurens van der Maaten · 2018
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3d semantic segmentation with submanifold sparse convolutional networks
Benjamin Graham, Martin Engelcke, and Laurens van der Maaten · 2018
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Pointcnn: Convolution on x-transformed points
Yangyan Li, Rui Bu, Mingchao Sun, Wei Wu, Xinhan Di, and Baoquan Chen · 2018
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Self-attention with relative position representations
Peter Shaw, Jakob Uszkoreit, and Ashish Vaswani · 2018
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SECOND: sparsely embedded convolutional detection
Yan Yan, Yuxing Mao, and Bo Li · 2018
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Efficient semantic scene completion network with spatial group convolution
Jiahui Zhang, Hao Zhao, Anbang Yao, Yurong Chen, Li Zhang, and Hongen Liao · 2018
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Attention augmented convolutional networks
Irwan Bello, Barret Zoph, Ashish Vaswani, Jonathon Shlens, and Quoc V Le · 2019
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4d spatio-temporal convnets: Minkowski convolutional neural networks
Christopher B. Choy, JunYoung Gwak, and Silvio Savarese · 2019
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Pointpillars: Fast encoders for object detection from point clouds
Alex H. Lang, Sourabh Vora, Holger Caesar, Lubing Zhou, Jiong Yang, and Oscar Beijbom · 2019
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Kpconv: Flexible and deformable convolution for point clouds
Hugues Thomas, Charles R. Qi, Jean-Emmanuel Deschaud, Beatriz Marcotegui, François Goulette, and Leonidas J. Guibas · 2019
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Pointconv: Deep convolutional networks on 3d point clouds
Wenxuan Wu, Zhongang Qi, and Fuxin Li · 2019
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Xlnet: Generalized autoregressive pretraining for language understanding
Zhilin Yang, Zihang Dai, Yiming Yang, Jaime Carbonell, Russ R Salakhutdinov, and Quoc V Le · 2019
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Class-balanced grouping and sampling for point cloud 3d object detection
Benjin Zhu, Zhengkai Jiang, Xiangxin Zhou, Zeming Li, and Gang Yu · 2019
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Deformable convnets V2: more deformable, better results
Xizhou Zhu, Han Hu, Stephen Lin, and Jifeng Dai · 2019
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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
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Every view counts: Cross-view consistency in 3d object detection with hybrid-cylindrical-spherical voxelization
Qi Chen, Lin Sun, Ernest Cheung, and Alan L. Yuille · 2020
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Object as hotspots: An anchor-free 3d object detection approach via firing of hotspots
Qi Chen, Lin Sun, Zhixin Wang, Kui Jia, and Alan L. Yuille · 2020
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Pyramid R-CNN: towards better performance and adaptability for 3d object detection
Jiageng Mao, Minzhe Niu, Haoyue Bai, Xiaodan Liang, Hang Xu, and Chunjing Xu · 2021
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Voxel transformer for 3d object detection
Jiageng Mao, Yujing Xue, Minzhe Niu, Haoyue Bai, Jiashi Feng, Xiaodan Liang, Hang Xu, and Chunjing Xu · 2021
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Chunghyun Park, Yoonwoo Jeong, Minsu Cho, and Jaesik Park · 2021
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Do vision transformers see like convolutional neural networks?
Maithra Raghu, Thomas Unterthiner, Simon Kornblith, Chiyuan Zhang, and Alexey Dosovitskiy · 2021
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Global filter networks for image classification
Yongming Rao, Wenliang Zhao, Zheng Zhu, Jiwen Lu, and Jie Zhou · 2021
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Randla-net: Efficient semantic segmentation of large-scale point clouds
Qingyong Hu, Bo Yang, Linhai Xie, Stefano Rosa, Yulan Guo, Zhihua Wang, Niki Trigoni, and Andrew Markham · 2020
Cited alongside, same era.
Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, Peter J Liu, et al · 2020
Cited alongside, same era.
PV-RCNN: point-voxel feature set abstraction for 3d object detection
Shaoshuai Shi, Chaoxu Guo, Li Jiang, Zhe Wang, Jianping Shi, Xiaogang Wang, and Hongsheng Li · 2020
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Scalability in perception for autonomous driving: Waymo open dataset
Pei Sun, Henrik Kretzschmar, Xerxes Dotiwalla, Aurelien Chouard, Vijaysai Patnaik, Paul Tsui, James Guo, Yin Zhou, Yuning Chai, Benjamin Caine, Vijay Vasudevan, Wei Han, Jiquan Ngiam, Hang Zhao, Aleksei Timofeev, Scott Ettinger, Maxim Krivokon, Amy Gao, Aditya Joshi, Yu Zhang, Jonathon Shlens, Zhifeng Chen, and Dragomir Anguelov · 2020
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Searching efficient 3d architectures with sparse point-voxel convolution
Haotian Tang, Zhijian Liu, Shengyu Zhao, Yujun Lin, Ji Lin, Hanrui Wang, and Song Han · 2020
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Infofocus: 3d object detection for autonomous driving with dynamic information modeling
Jun Wang, Shiyi Lan, Mingfei Gao, and Larry S. Davis · 2020
Cited alongside, same era.
Pointasnl: Robust point clouds processing using nonlocal neural networks with adaptive sampling
Xu Yan, Chaoda Zheng, Zhen Li, Sheng Wang, and Shuguang Cui · 2020
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David W. Romero, Anna Kuzina, Erik J. Bekkers, Jakub M. Tomczak, and Mark Hoogendoorn · 2021
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From points to parts: 3d object detection from point cloud with part-aware and part-aggregation network
Shaoshuai Shi, Zhe Wang, Jianping Shi, Xiaogang Wang, and Hongsheng Li · 2021
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RSN: range sparse net for efficient, accurate lidar 3d object detection
Pei Sun, Weiyue Wang, Yuning Chai, Gamaleldin Elsayed, Alex Bewley, Xiao Zhang, Cristian Sminchisescu, and Dragomir Anguelov · 2021
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Rethinking and improving relative position encoding for vision transformer
Kan Wu, Houwen Peng, Minghao Chen, Jianlong Fu, and Hongyang Chao · 2021
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Focal self-attention for local-global interactions in vision transformers
Jianwei Yang, Chunyuan Li, Pengchuan Zhang, Xiyang Dai, Bin Xiao, Lu Yuan, and Jianfeng Gao · 2021
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Center-based 3d object detection and tracking
Tianwei Yin, Xingyi Zhou, and Philipp Krähenbühl · 2021
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Point transformer
Hengshuang Zhao, Li Jiang, Jiaya Jia, Philip H. S. Torr, and Vladlen Koltun · 2021
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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
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Focal sparse convolutional networks for 3d object detection
Yukang Chen, Yanwei Li, Xiangyu Zhang, Jian Sun, and Jiaya Jia · 2022
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Twist: Two-way inter-label self-training for semi-supervised 3d instance segmentation
Ruihang Chu, Xiaoqing Ye, Zhengzhe Liu, Xiao Tan, Xiaojuan Qi, Chi-Wing Fu, and Jiaya Jia · 2022
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VISTA: boosting 3d object detection via dual cross-view spatial attention
Shengheng Deng, Zhihao Liang, Lin Sun, and Kui Jia · 2022
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Scaling up your kernels to 31x31: Revisiting large kernel design in cnns
Xiaohan Ding, Xiangyu Zhang, Yizhuang Zhou, Jungong Han, Guiguang Ding, and Jian Sun · 2022
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Embracing single stride 3d object detector with sparse transformer
Lue Fan, Ziqi Pang, Tianyuan Zhang, Yu-Xiong Wang, Hang Zhao, Feng Wang, Naiyan Wang, and Zhaoxiang Zhang · 2022
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M3DETR: multi-representation, multi-scale, mutual-relation 3d object detection with transformers
Tianrui Guan, Jun Wang, Shiyi Lan, Rohan Chandra, Zuxuan Wu, Larry Davis, and Dinesh Manocha · 2022
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Stratified transformer for 3d point cloud segmentation
Xin Lai, Jianhui Liu, Li Jiang, Liwei Wang, Hengshuang Zhao, Shu Liu, Xiaojuan Qi, and Jiaya Jia · 2022
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Unifying voxel-based representation with transformer for 3d object detection
Yanwei Li, Yilun Chen, Xiaojuan Qi, Zeming Li, Jian Sun, and Jiaya Jia · 2022
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Zhuang Liu, Hanzi Mao, Chao-Yuan Wu, Christoph Feichtenhofer, Trevor Darrell, and Saining Xie · 2022
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Swformer: Sparse window transformer for 3d object detection in point clouds
Pei Sun, Mingxing Tan, Weiyue Wang, Chenxi Liu, Fei Xia, Zhaoqi Leng, and Dragomir Anguelov · 2022
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Asher Trockman and J. Zico Kolter · 2022
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Fast-parc: Position aware global kernel for convnets and vits
Tao Yang, Haokui Zhang, Wenze Hu, Changwen Chen, and Xiaoyu Wang · 2022
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Spherical transformer for lidar-based 3d recognition
Xin Lai, Yukang Chen, Fanbin Lu, Jianhui Liu, and Jiaya Jia · 2023
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