Fetching the paper…
Reading the bibliography…
We introduce PointConvFormer, a novel building block for point cloud based deep network architectures.
Rademacher and gaussian complexities: Risk bounds and structural results
Peter L Bartlett and Shahar Mendelson · 2002
Earlier work this paper cites.
A variational method for scene flow estimation from stereo sequences
Frédéric Huguet and Frédéric Devernay · 2007
Earlier work this paper cites.
Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
Earlier work this paper cites.
Are we ready for Autonomous Driving? The KITTI Vision Benchmark Suite
A. Geiger, P. Lenz, and R. Urtasun · 2012
Earlier work this paper cites.
Voxnet: A 3d convolutional neural network for real-time object recognition
Daniel Maturana and Sebastian Scherer · 2015
Earlier work this paper cites.
Object scene flow for autonomous vehicles
Moritz Menze and Andreas Geiger · 2015
Earlier work this paper cites.
Joint 3d estimation of vehicles and scene flow
Moritz Menze, Christian Heipke, and Andreas Geiger · 2015
Earlier work this paper cites.
Multi-view convolutional neural networks for 3d shape recognition
Hang Su, Subhransu Maji, Evangelos Kalogerakis, and Erik Learned-Miller · 2015
Earlier work this paper cites.
3d scene flow estimation with a piecewise rigid scene model
Christoph Vogel, Konrad Schindler, and Stefan Roth · 2015
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
Learning sparse high dimensional filters: Image filtering, dense crfs and bilateral neural networks
Varun Jampani, Martin Kiefel, and Peter V Gehler · 2016
Earlier work this paper cites.
Dynamic filter networks
Xu Jia, Bert De Brabandere, Tinne Tuytelaars, and Luc V Gool · 2016
Earlier work this paper cites.
Vehicle detection from 3d lidar using fully convolutional network
Bo Li, Tianlei Zhang, and Tian Xia · 2016
Earlier work this paper cites.
A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation
Nikolaus Mayer, Eddy Ilg, Philip Hausser, Philipp Fischer, Daniel Cremers, Alexey Dosovitskiy, and Thomas Brox · 2016
Earlier work this paper cites.
A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation
Nikolaus Mayer, Eddy Ilg, Philip Hausser, Philipp Fischer, Daniel Cremers, Alexey Dosovitskiy, and Thomas Brox · 2016
Earlier work this paper cites.
Unstructured point cloud semantic labeling using deep segmentation networks
Alexandre Boulch, Bertrand Le Saux, Nicolas Audebert, et al · 2017
Earlier work this paper cites.
Multi-view 3d object detection network for autonomous driving
Xiaozhi Chen, Huimin Ma, Ji Wan, Bo Li, and Tian Xia · 2017
Earlier work this paper cites.
Scannet: Richly-annotated 3d reconstructions of indoor scenes
Angela Dai, Angel X. Chang, Manolis Savva, Maciej Halber, Thomas Funkhouser, and Matthias Nießner · 2017
Earlier work this paper cites.
Deformable convolutional networks
Jifeng Dai, Haozhi Qi, Yuwen Xiong, Yi Li, Guodong Zhang, Han Hu, and Yichen Wei · 2017
Earlier work this paper cites.
Filter shaping for convolutional neural networks
Xingyi Li, Fuxin Li, Xiaoli Fern, and Raviv Raich · 2017
Earlier work this paper cites.
Pointnet: Deep learning on point sets for 3d classification and segmentation
Charles R Qi, Hao Su, Kaichun Mo, and Leonidas J Guibas · 2017
Earlier work this paper cites.
Pointnet++: Deep hierarchical feature learning on point sets in a metric space
Charles Ruizhongtai Qi, Li Yi, Hao Su, and Leonidas J Guibas · 2017
Earlier work this paper cites.
Dynamic edge-conditioned filters in convolutional neural networks on graphs
Martin Simonovsky and Nikos Komodakis · 2017
Earlier work this paper cites.
Semantic scene completion from a single depth image
Shuran Song, Fisher Yu, Andy Zeng, Angel X Chang, Manolis Savva, and Thomas Funkhouser · 2017
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
Earlier work this paper cites.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
Earlier work this paper cites.
Learning so (3) equivariant representations with spherical cnns
Carlos Esteves, Christine Allen-Blanchette, Ameesh Makadia, and Kostas Daniilidis · 2018
Earlier work this paper cites.
3d semantic segmentation with submanifold sparse convolutional networks
Benjamin Graham, Martin Engelcke, and Laurens van der Maaten · 2018
Earlier work this paper cites.
Rotationnet: Joint object categorization and pose estimation using multiviews from unsupervised viewpoints
Asako Kanezaki, Yasuyuki Matsushita, and Yoshifumi Nishida · 2018
Earlier work this paper cites.
Pointcnn: Convolution on x-transformed points
Yangyan Li, Rui Bu, Mingchao Sun, Wei Wu, Xinhan Di, and Baoquan Chen · 2018
Earlier work this paper cites.
Object scene flow
Moritz Menze, Christian Heipke, and Andreas Geiger · 2018
Earlier work this paper cites.
Self-attention with relative position representations
Peter Shaw, Jakob Uszkoreit, and Ashish Vaswani · 2018
Earlier work this paper cites.
Splatnet: Sparse lattice networks for point cloud processing
Hang Su, Varun Jampani, Deqing Sun, Subhransu Maji, Evangelos Kalogerakis, Ming-Hsuan Yang, and Jan Kautz · 2018
Earlier work this paper cites.
Local spectral graph convolution for point set feature learning
Chu Wang, Babak Samari, and Kaleem Siddiqi · 2018
Earlier work this paper cites.
Deep parametric continuous convolutional neural networks
Shenlong Wang, Simon Suo, Wei-Chiu Ma, Andrei Pokrovsky, and Raquel Urtasun · 2018
Cited alongside, same era.
Non-local neural networks
Xiaolong Wang, Ross Girshick, Abhinav Gupta, and Kaiming He · 2018
Cited alongside, same era.
Cbam: Convolutional block attention module
Sanghyun Woo, Jongchan Park, Joon-Young Lee, and In So Kweon · 2018
Cited alongside, same era.
Attentional shapecontextnet for point cloud recognition
Saining Xie, Sainan Liu, Zeyu Chen, and Zhuowen Tu · 2018
Cited alongside, same era.
Spidercnn: Deep learning on point sets with parameterized convolutional filters
Yifan Xu, Tianqi Fan, Mingye Xu, Long Zeng, and Yu Qiao · 2018
Cited alongside, same era.
Semantickitti: A dataset for semantic scene understanding of lidar sequences
Jens Behley, Martin Garbade, Andres Milioto, Jan Quenzel, Sven Behnke, Cyrill Stachniss, and Jurgen Gall · 2019
An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2020
Later among the works it cites.
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
Later among the works it cites.
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
Later among the works it cites.
Kprnet: Improving projection-based lidar semantic segmentation
Deyvid Kochanov, Fatemeh Karimi Nejadasl, and Olaf Booij · 2020
Later among the works it cites.
Virtual multi-view fusion for 3d semantic segmentation
Abhijit Kundu, Xiaoqi Yin, Alireza Fathi, David Ross, Brian Brewington, Thomas Funkhouser, and Caroline Pantofaru · 2020
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
SemanticKITTI: A Dataset for Semantic Scene Understanding of LiDAR Sequences
J. Behley, M. Garbade, A. Milioto, J. Quenzel, S. Behnke, C. Stachniss, and J. Gall · 2019
Cited alongside, same era.
A unified point-based framework for 3d segmentation
Hung-Yueh Chiang, Yen-Liang Lin, Yueh-Cheng Liu, and Winston H Hsu · 2019
Cited alongside, same era.
4d spatio-temporal convnets: Minkowski convolutional neural networks
Christopher Choy, JunYoung Gwak, and Silvio Savarese · 2019
Cited alongside, same era.
Transformer-xl: Attentive language models beyond a fixed-length context
Zihang Dai, Zhilin Yang, Yiming Yang, Jaime G Carbonell, Quoc Le, and Ruslan Salakhutdinov · 2019
Cited alongside, same era.
Hplflownet: Hierarchical permutohedral lattice flownet for scene flow estimation on large-scale point clouds
Xiuye Gu, Yijie Wang, Chongruo Wu, Yong Jae Lee, and Panqu Wang · 2019
Cited alongside, same era.
Local relation networks for image recognition
Han Hu, Zheng Zhang, Zhenda Xie, and Stephen Lin · 2019
Cited alongside, same era.
Later among the works it cites.
Weightnet: Revisiting the design space of weight networks
Ningning Ma, Xiangyu Zhang, Jiawei Huang, and Jian Sun · 2020
Later among the works it cites.
Flot: Scene flow on point clouds guided by optimal transport
Gilles Puy, Alexandre Boulch, and Renaud Marlet · 2020
Later among the works it cites.
Spatially-adaptive filter units for compact and efficient deep neural networks
Domen Tabernik, Matej Kristan, and Aleš Leonardis · 2020
Later among the works it cites.
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
Later among the works it cites.
Conditional convolutions for instance segmentation
Zhi Tian, Chunhua Shen, and Hao Chen · 2020
Later among the works it cites.
Solov2: Dynamic and fast instance segmentation
Xinlong Wang, Rufeng Zhang, Tao Kong, Lei Li, and Chunhua Shen · 2020
Later among the works it cites.
Pointpwc-net: Cost volume on point clouds for (self-) supervised scene flow estimation
Wenxuan Wu, Zhi Yuan Wang, Zhuwen Li, Wei Liu, and Li Fuxin · 2020
Later among the works it cites.
Squeezesegv3: Spatially-adaptive convolution for efficient point-cloud segmentation
Chenfeng Xu, Bichen Wu, Zining Wang, Wei Zhan, Peter Vajda, Kurt Keutzer, and Masayoshi Tomizuka · 2020
Later among the works it cites.
Pointasnl: Robust point clouds processing using nonlocal neural networks with adaptive sampling
Xu Yan, Chaoda Zheng, Zhen Li, Sheng Wang, and Shuguang Cui · 2020
Later among the works it cites.
Deep fusionnet for point cloud semantic segmentation
Feihu Zhang, Jin Fang, Benjamin Wah, and Philip Torr · 2020
Later among the works it cites.
Dynet: Dynamic convolution for accelerating convolutional neural networks
Yikang Zhang, Jian Zhang, Qiang Wang, and Zhao Zhong · 2020
Later among the works it cites.
Exploring self-attention for image recognition
Hengshuang Zhao, Jiaya Jia, and Vladlen Koltun · 2020
Later among the works it cites.
2-s3net: Attentive feature fusion with adaptive feature selection for sparse semantic segmentation network
Ran Cheng, Ryan Razani, Ehsan Taghavi, Enxu Li, and Bingbing Liu · 2021
Later among the works it cites.
Conditional positional encodings for vision transformers
Xiangxiang Chu, Zhi Tian, Bo Zhang, Xinlong Wang, Xiaolin Wei, Huaxia Xia, and Chunhua Shen · 2021
Later among the works it cites.
Kcnet: Kernel-based canonicalization network for entities in recruitment domain
Nidhi Goyal, Niharika Sachdeva, Anmol Goel, Jushaan Singh Kalra, and Ponnurangam Kumaraguru · 2021
Later among the works it cites.
Bidirectional projection network for cross dimension scene understanding
Wenbo Hu, Hengshuang Zhao, Li Jiang, Jiaya Jia, and Tien-Tsin Wong · 2021
Later among the works it cites.
Vmnet: Voxel-mesh network for geodesic-aware 3d semantic segmentation
Zeyu Hu, Xuyang Bai, Jiaxiang Shang, Runze Zhang, Jiayu Dong, Xin Wang, Guangyuan Sun, Hongbo Fu, and Chiew-Lan Tai · 2021
Later among the works it cites.
Hcrf-flow: Scene flow from point clouds with continuous high-order crfs and position-aware flow embedding
Ruibo Li, Guosheng Lin, Tong He, Fayao Liu, and Chunhua Shen · 2021
Later among the works it cites.
The devils in the point clouds: Studying the robustness of point cloud convolutions
Xingyi Li, Wenxuan Wu, Xiaoli Z Fern, and Li Fuxin · 2021
Later among the works it cites.
Mix3d: Out-of-context data augmentation for 3d scenes
Alexey Nekrasov, Jonas Schult, Or Litany, Bastian Leibe, and Francis Engelmann · 2021
Later among the works it cites.
Chunghyun Park, Yoonwoo Jeong, Minsu Cho, and Jaesik Park · 2021
Later among the works it cites.
Pv-raft: Point-voxel correlation fields for scene flow estimation of point clouds
Yi Wei, Ziyi Wang, Yongming Rao, Jiwen Lu, and Jie Zhou · 2021
Later among the works it cites.
Point transformer
Hengshuang Zhao, Li Jiang, Jiaya Jia, Philip HS Torr, and Vladlen Koltun · 2021
Later among the works it cites.
Decoupled dynamic filter networks
Jingkai Zhou, Varun Jampani, Zhixiong Pi, Qiong Liu, and Ming-Hsuan Yang · 2021
Later among the works it cites.
Cylindrical and asymmetrical 3d convolution networks for lidar segmentation
Xinge Zhu, Hui Zhou, Tai Wang, Fangzhou Hong, Yuexin Ma, Wei Li, Hongsheng Li, and Dahua Lin · 2021
Later among the works it cites.
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
Closest in time.
Torchsparse: Efficient point cloud inference engine
Haotian Tang, Zhijian Liu, Xiuyu Li, Yujun Lin, and Song Han · 2022
Closest in time.
Point transformer v2: Grouped vector attention and partition-based pooling
Xiaoyang Wu, Yixing Lao, Li Jiang, Xihui Liu, and Hengshuang Zhao · 2022
Closest in time.