{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T17:19:36Z","timestamp":1777655976784,"version":"3.51.4"},"publisher-location":"New York, NY, USA","reference-count":76,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,6,17]],"date-time":"2023-06-17T00:00:00Z","timestamp":1686960000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1931531"],"award-info":[{"award-number":["1931531"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["2116962"],"award-info":[{"award-number":["2116962"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["2122155"],"award-info":[{"award-number":["2122155"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["2211018"],"award-info":[{"award-number":["2211018"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1763681"],"award-info":[{"award-number":["1763681"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["2028929"],"award-info":[{"award-number":["2028929"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,6,17]]},"DOI":"10.1145\/3579371.3589113","type":"proceedings-article","created":{"date-parts":[[2023,6,16]],"date-time":"2023-06-16T20:25:28Z","timestamp":1686947128000},"page":"1-14","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":24,"title":["EdgePC: Efficient Deep Learning Analytics for Point Clouds on Edge Devices"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0854-9933","authenticated-orcid":false,"given":"Ziyu","family":"Ying","sequence":"first","affiliation":[{"name":"The Pennsylvania State University, State College, Pennsylvania, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0679-9058","authenticated-orcid":false,"given":"Sandeepa","family":"Bhuyan","sequence":"additional","affiliation":[{"name":"The Pennsylvania State University, State College, Pennsylvania, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-8718-1491","authenticated-orcid":false,"given":"Yan","family":"Kang","sequence":"additional","affiliation":[{"name":"The Pennsylvania State University, State College, Pennsylvania, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-7220-8571","authenticated-orcid":false,"given":"Yingtian","family":"Zhang","sequence":"additional","affiliation":[{"name":"The Pennsylvania State University, State College, Pennsylvania, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9940-9951","authenticated-orcid":false,"given":"Mahmut T.","family":"Kandemir","sequence":"additional","affiliation":[{"name":"The Pennsylvania State University, State College, Pennsylvania, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4746-7578","authenticated-orcid":false,"given":"Chita R.","family":"Das","sequence":"additional","affiliation":[{"name":"The Pennsylvania State University, State College, Pennsylvania, USA"}]}],"member":"320","published-online":{"date-parts":[[2023,6,17]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"Apple Inc. 2022. iPhone 13 Pro. \"https:\/\/www.apple.com\/am\/iphone-13-pro\/\".  Apple Inc. 2022. iPhone 13 Pro. \"https:\/\/www.apple.com\/am\/iphone-13-pro\/\"."},{"key":"e_1_3_2_1_2_1","unstructured":"Alan Walford. 2017. What is Photogrammetry? \"https:\/\/www.photogrammetry.com\/\".  Alan Walford. 2017. What is Photogrammetry? \"https:\/\/www.photogrammetry.com\/\"."},{"key":"e_1_3_2_1_3_1","volume-title":"2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society","author":"Armeni Iro","year":"2016","unstructured":"Iro Armeni , Ozan Sener , Amir R Zamir , Helen Jiang , Ioannis Brilakis , Martin Fischer , and Silvio Savarese . 2016 . 3D Semantic Parsing of Large-Scale Indoor Spaces . In 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society , Los Alamitos, CA, USA, 1534--1543. Iro Armeni, Ozan Sener, Amir R Zamir, Helen Jiang, Ioannis Brilakis, Martin Fischer, and Silvio Savarese. 2016. 3D Semantic Parsing of Large-Scale Indoor Spaces. In 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society, Los Alamitos, CA, USA, 1534--1543."},{"key":"e_1_3_2_1_4_1","first-page":"1","volume-title":"Proc. ACM Meas. Anal. Comput. Syst. 6","author":"Bhuyan Sandeepa","year":"2022","unstructured":"Sandeepa Bhuyan , Shulin Zhao , Ziyu Ying , Mahmut T. Kandemir , and Chita R. Das . 2022. End-to-End Characterization of Game Streaming Applications on Mobile Platforms . Proc. ACM Meas. Anal. Comput. Syst. 6 , 1 ( 2022 ), 25 pages. Sandeepa Bhuyan, Shulin Zhao, Ziyu Ying, Mahmut T. Kandemir, and Chita R. Das. 2022. End-to-End Characterization of Game Streaming Applications on Mobile Platforms. Proc. ACM Meas. Anal. Comput. Syst. 6, 1 (2022), 25 pages."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"crossref","first-page":"1100","DOI":"10.1038\/s41592-020-0946-1","article-title":"Genuage: visualize and analyze multidimensional single-molecule point cloud data in virtual reality","volume":"17","author":"Blanc Thomas","year":"2020","unstructured":"Thomas Blanc , Mohamed El Beheiry , Cl\u00e9ment Caporal , Jean-Baptiste Masson , and Bassam Hajj . 2020 . Genuage: visualize and analyze multidimensional single-molecule point cloud data in virtual reality . Nature Methods 17 , 11 (2020), 1100 -- 1102 . Thomas Blanc, Mohamed El Beheiry, Cl\u00e9ment Caporal, Jean-Baptiste Masson, and Bassam Hajj. 2020. Genuage: visualize and analyze multidimensional single-molecule point cloud data in virtual reality. Nature Methods 17, 11 (2020), 1100--1102.","journal-title":"Nature Methods"},{"key":"e_1_3_2_1_6_1","volume-title":"Proceedings of the Twenty-First Annual Symposium on Parallelism in Algorithms and Architectures. Association for Computing Machinery","author":"Bulu\u00e7 Aydin","unstructured":"Aydin Bulu\u00e7 , Jeremy T. Fineman , Matteo Frigo , John R. Gilbert , and Charles E. Leiserson . 2009. Parallel Sparse Matrix-Vector and Matrix-Transpose-Vector Multiplication Using Compressed Sparse Blocks . In Proceedings of the Twenty-First Annual Symposium on Parallelism in Algorithms and Architectures. Association for Computing Machinery , New York, NY, USA, 233--244. Aydin Bulu\u00e7, Jeremy T. Fineman, Matteo Frigo, John R. Gilbert, and Charles E. Leiserson. 2009. Parallel Sparse Matrix-Vector and Matrix-Transpose-Vector Multiplication Using Compressed Sparse Blocks. In Proceedings of the Twenty-First Annual Symposium on Parallelism in Algorithms and Architectures. Association for Computing Machinery, New York, NY, USA, 233--244."},{"key":"e_1_3_2_1_7_1","unstructured":"ByteBridge. 2021. How 3D Point Cloud Annotation Service Fuels the Field of Automatic Driving? \"https:\/\/medium.com\/nerd-for-tech\/application-of-3d-point-cloud-in-the-field-of-automatic-driving-723ec9544a6c\".  ByteBridge. 2021. How 3D Point Cloud Annotation Service Fuels the Field of Automatic Driving? \"https:\/\/medium.com\/nerd-for-tech\/application-of-3d-point-cloud-in-the-field-of-automatic-driving-723ec9544a6c\"."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1061\/(ASCE)CP.1943-5487.0000842"},{"key":"e_1_3_2_1_9_1","first-page":"68","article-title":"3D Point Cloud Processing and Learning for Autonomous Driving: Impacting Map Creation, Localization, and Perception","volume":"38","author":"Chen Siheng","year":"2020","unstructured":"Siheng Chen , Baoan Liu , Chen Feng , Carlos Vallespi-Gonzalez , and Carl Wellington . 2020 . 3D Point Cloud Processing and Learning for Autonomous Driving: Impacting Map Creation, Localization, and Perception . IEEE Audio and Electroacoustics Newsletter 38 , 1 (2020), 68 -- 86 . Siheng Chen, Baoan Liu, Chen Feng, Carlos Vallespi-Gonzalez, and Carl Wellington. 2020. 3D Point Cloud Processing and Learning for Autonomous Driving: Impacting Map Creation, Localization, and Perception. IEEE Audio and Electroacoustics Newsletter 38, 1 (2020), 68--86.","journal-title":"IEEE Audio and Electroacoustics Newsletter"},{"key":"e_1_3_2_1_10_1","volume-title":"2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society","author":"Chen Xiaozhi","year":"2017","unstructured":"Xiaozhi Chen , Huimin Ma , Ji Wan , Bo Li , and Tian Xia . 2017 . Multi-view 3D Object Detection Network for Autonomous Driving . In 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society , Los Alamitos, CA, USA, 6526--6534. Xiaozhi Chen, Huimin Ma, Ji Wan, Bo Li, and Tian Xia. 2017. Multi-view 3D Object Detection Network for Autonomous Driving. In 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society, Los Alamitos, CA, USA, 6526--6534."},{"key":"e_1_3_2_1_11_1","volume-title":"2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society","author":"Choy Christopher","year":"2019","unstructured":"Christopher Choy , JunYoung Gwak , and Silvio Savarese . 2019 . 4D Spatio-Temporal ConvNets: Minkowski Convolutional Neural Networks . In 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society , Los Alamitos, CA, USA, 3070--3079. Christopher Choy, JunYoung Gwak, and Silvio Savarese. 2019. 4D Spatio-Temporal ConvNets: Minkowski Convolutional Neural Networks. In 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society, Los Alamitos, CA, USA, 3070--3079."},{"key":"e_1_3_2_1_12_1","unstructured":"Michael F Connor. 2007. Simple Thread-Safe Approximate Nearest Neighbor Algorithm. Master's thesis.  Michael F Connor. 2007. Simple Thread-Safe Approximate Nearest Neighbor Algorithm. Master's thesis."},{"key":"e_1_3_2_1_13_1","volume-title":"2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society","author":"Dai Angela","year":"2017","unstructured":"Angela Dai , Angel X Chang , Manolis Savva , Maciej Halber , Thomas Funkhouser , and Matthias Nie\u00dfner . 2017 . Scannet: Richly-annotated 3d reconstructions of indoor scenes . In 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society , Los Alamitos, CA, USA, 2432--2443. Angela Dai, Angel X Chang, Manolis Savva, Maciej Halber, Thomas Funkhouser, and Matthias Nie\u00dfner. 2017. Scannet: Richly-annotated 3d reconstructions of indoor scenes. In 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society, Los Alamitos, CA, USA, 2432--2443."},{"key":"e_1_3_2_1_14_1","unstructured":"DISCOVER three.js. 2022. A Brief Introduction to Texture Mapping. \"https:\/\/discoverthreejs.com\/book\/first-steps\/textures-intro\/\".  DISCOVER three.js. 2022. A Brief Introduction to Texture Mapping. \"https:\/\/discoverthreejs.com\/book\/first-steps\/textures-intro\/\"."},{"key":"e_1_3_2_1_15_1","volume-title":"Pattern classification and scene analysis","author":"Duda Richard O","unstructured":"Richard O Duda , Peter E Hart , and David G Stork . 1973. Pattern classification and scene analysis . Wiley New York . Richard O Duda, Peter E Hart, and David G Stork. 1973. Pattern classification and scene analysis. Wiley New York."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/83.623193"},{"key":"e_1_3_2_1_17_1","volume-title":"Proceedings of the 49th Annual International Symposium on Computer Architecture. Association for Computing Machinery","author":"Feng Yu","year":"2022","unstructured":"Yu Feng , Gunnar Hammonds , Yiming Gan , and Yuhao Zhu . 2022 . Crescent: Taming Memory Irregularities for Accelerating Deep Point Cloud Analytics . In Proceedings of the 49th Annual International Symposium on Computer Architecture. Association for Computing Machinery , New York, NY, USA, 962--977. Yu Feng, Gunnar Hammonds, Yiming Gan, and Yuhao Zhu. 2022. Crescent: Taming Memory Irregularities for Accelerating Deep Point Cloud Analytics. In Proceedings of the 49th Annual International Symposium on Computer Architecture. Association for Computing Machinery, New York, NY, USA, 962--977."},{"key":"e_1_3_2_1_18_1","volume-title":"2020 53rd Annual IEEE\/ACM International Symposium on Microarchitecture (MICRO). IEEE Computer Society","author":"Feng Yu","year":"2020","unstructured":"Yu Feng , Boyuan Tian , Tiancheng Xu , Paul Whatmough , and Yuhao Zhu . 2020 . Mesorasi: Architecture Support for Point Cloud Analytics via Delayed-Aggregation . In 2020 53rd Annual IEEE\/ACM International Symposium on Microarchitecture (MICRO). IEEE Computer Society , Los Alamitos, CA, USA, 1037--1050. Yu Feng, Boyuan Tian, Tiancheng Xu, Paul Whatmough, and Yuhao Zhu. 2020. Mesorasi: Architecture Support for Point Cloud Analytics via Delayed-Aggregation. In 2020 53rd Annual IEEE\/ACM International Symposium on Microarchitecture (MICRO). IEEE Computer Society, Los Alamitos, CA, USA, 1037--1050."},{"key":"e_1_3_2_1_19_1","volume-title":"Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society, USA, 3354--3361","author":"Geiger Andreas","year":"2012","unstructured":"Andreas Geiger , Philip Lenz , and Raquel Urtasun . 2012 . Are We Ready for Autonomous Driving? The KITTI Vision Benchmark Suite . In Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society, USA, 3354--3361 . Andreas Geiger, Philip Lenz, and Raquel Urtasun. 2012. Are We Ready for Autonomous Driving? The KITTI Vision Benchmark Suite. In Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society, USA, 3354--3361."},{"key":"e_1_3_2_1_20_1","volume-title":"2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society","author":"Giancola Silvio","year":"2019","unstructured":"Silvio Giancola , Jesus Zarzar , and Bernard Ghanem . 2019 . Leveraging Shape Completion for 3D Siamese Tracking . In 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society , Los Alamitos, CA, USA, 1359--1368. Silvio Giancola, Jesus Zarzar, and Bernard Ghanem. 2019. Leveraging Shape Completion for 3D Siamese Tracking. In 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society, Los Alamitos, CA, USA, 1359--1368."},{"key":"e_1_3_2_1_21_1","unstructured":"GlobeNewswire Inc. 2022. Straits Research. \"https:\/\/www.globenewswire.com\/en\/news-release\/2022\/09\/14\/2516327\/0\/en\/LIDAR-Market-Size-is-projected-to-reach-USD-6-93-Billion-by-2030-growing-at-a-CAGR-of-19-27-Straits-Research.html\".  GlobeNewswire Inc. 2022. Straits Research. \"https:\/\/www.globenewswire.com\/en\/news-release\/2022\/09\/14\/2516327\/0\/en\/LIDAR-Market-Size-is-projected-to-reach-USD-6-93-Billion-by-2030-growing-at-a-CAGR-of-19-27-Straits-Research.html\"."},{"key":"e_1_3_2_1_22_1","unstructured":"Julian Gross Marcel K\u00f6ster and Antonio Kr\u00fcger. 2019. Fast and Efficient Nearest Neighbor Search for Particle Simulations.. In CGVC. 55--63.  Julian Gross Marcel K\u00f6ster and Antonio Kr\u00fcger. 2019. Fast and Efficient Nearest Neighbor Search for Particle Simulations.. In CGVC. 55--63."},{"key":"e_1_3_2_1_23_1","volume-title":"IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2019","author":"Hashimoto Taisuke","year":"2019","unstructured":"Taisuke Hashimoto and Masaki Saito . 2019 . Normal Estimation for Accurate 3D Mesh Reconstruction with Point Cloud Model Incorporating Spatial Structure . In IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2019 , Long Beach, CA, USA, June 16--20 , 2019. Computer Vision Foundation \/ IEEE, 54--63. Taisuke Hashimoto and Masaki Saito. 2019. Normal Estimation for Accurate 3D Mesh Reconstruction with Point Cloud Model Incorporating Spatial Structure. In IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2019, Long Beach, CA, USA, June 16--20, 2019. Computer Vision Foundation \/ IEEE, 54--63."},{"key":"e_1_3_2_1_24_1","volume-title":"RAPIDNN: In-Memory Deep Neural Network Acceleration Framework. CoRR abs\/1806.05794","author":"Imani Mohsen","year":"2018","unstructured":"Mohsen Imani , Mohammad Samragh , Yeseong Kim , Saransh Gupta , Farinaz Koushanfar , and Tajana Rosing . 2018 . RAPIDNN: In-Memory Deep Neural Network Acceleration Framework. CoRR abs\/1806.05794 (2018). Mohsen Imani, Mohammad Samragh, Yeseong Kim, Saransh Gupta, Farinaz Koushanfar, and Tajana Rosing. 2018. RAPIDNN: In-Memory Deep Neural Network Acceleration Framework. CoRR abs\/1806.05794 (2018)."},{"key":"e_1_3_2_1_25_1","unstructured":"Intel Corporation. 2022. Intel RealSense Depth and Tracking cameras. \"https:\/\/www.intelrealsense.com\/\".  Intel Corporation. 2022. Intel RealSense Depth and Tracking cameras. \"https:\/\/www.intelrealsense.com\/\"."},{"key":"e_1_3_2_1_26_1","volume-title":"Weiler Marcel and Stephan Seitz","author":"Bender Jan","year":"2022","unstructured":"Jan Bender , Weiler Marcel and Stephan Seitz . 2022 . cuNSearch. https:\/\/github.com\/InteractiveComputerGraphics\/cuNSearch. Jan Bender, Weiler Marcel and Stephan Seitz. 2022. cuNSearch. https:\/\/github.com\/InteractiveComputerGraphics\/cuNSearch."},{"key":"e_1_3_2_1_27_1","unstructured":"Jeroen Baert. 2013. Morton encoding\/decoding through bit interleaving: Implementations. \"https:\/\/www.forceflow.be\/2013\/10\/07\/morton-encodingdecoding-through-bit-interleaving-implementations\/\".  Jeroen Baert. 2013. Morton encoding\/decoding through bit interleaving: Implementations. \"https:\/\/www.forceflow.be\/2013\/10\/07\/morton-encodingdecoding-through-bit-interleaving-implementations\/\"."},{"key":"e_1_3_2_1_28_1","volume-title":"A-CNN: Annularly Convolutional Neural Networks on Point Clouds. In 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society","author":"Komarichev Artem","year":"2019","unstructured":"Artem Komarichev , Zichun Zhong , and Jing Hua . 2019 . A-CNN: Annularly Convolutional Neural Networks on Point Clouds. In 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society , Los Alamitos, CA, USA, 7413--7422. Artem Komarichev, Zichun Zhong, and Jing Hua. 2019. A-CNN: Annularly Convolutional Neural Networks on Point Clouds. In 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society, Los Alamitos, CA, USA, 7413--7422."},{"key":"e_1_3_2_1_29_1","volume-title":"Proceedings of the 23rd Annual International Conference on Mobile Computing and Networking. Association for Computing Machinery","author":"Lai Zeqi","year":"2017","unstructured":"Zeqi Lai , Y. Charlie Hu , Yong Cui , Linhui Sun , and Ningwei Dai . 2017 . Furion: Engineering High-Quality Immersive Virtual Reality on Today's Mobile Devices . In Proceedings of the 23rd Annual International Conference on Mobile Computing and Networking. Association for Computing Machinery , New York, NY, USA, 409--421. Zeqi Lai, Y. Charlie Hu, Yong Cui, Linhui Sun, and Ningwei Dai. 2017. Furion: Engineering High-Quality Immersive Virtual Reality on Today's Mobile Devices. In Proceedings of the 23rd Annual International Conference on Mobile Computing and Networking. Association for Computing Machinery, New York, NY, USA, 409--421."},{"key":"e_1_3_2_1_30_1","volume-title":"2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society","author":"Lan Shiyi","year":"2019","unstructured":"Shiyi Lan , Ruichi Yu , Gang Yu , and Larry S Davis . 2019 . Modeling Local Geometric Structure of 3D Point Clouds Using Geo-CNN . In 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society , Los Alamitos, CA, USA, 998--1008. Shiyi Lan, Ruichi Yu, Gang Yu, and Larry S Davis. 2019. Modeling Local Geometric Structure of 3D Point Clouds Using Geo-CNN. In 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society, Los Alamitos, CA, USA, 998--1008."},{"key":"e_1_3_2_1_31_1","volume-title":"Large-Scale Point Cloud Semantic Segmentation with Superpoint Graphs. In 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society","author":"Landrieu Loic","year":"2018","unstructured":"Loic Landrieu and Martin Simonovsky . 2018 . Large-Scale Point Cloud Semantic Segmentation with Superpoint Graphs. In 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society , Los Alamitos, CA, USA, 4558--4567. Loic Landrieu and Martin Simonovsky. 2018. Large-Scale Point Cloud Semantic Segmentation with Superpoint Graphs. In 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society, Los Alamitos, CA, USA, 4558--4567."},{"key":"e_1_3_2_1_32_1","volume-title":"Proceedings of the 26th Annual International Conference on Mobile Computing and Networking. Association for Computing Machinery","author":"Lee Kyungjin","year":"2020","unstructured":"Kyungjin Lee , Juheon Yi , Youngki Lee , Sunghyun Choi , and Young Min Kim . 2020 . GROOT: A Real-Time Streaming System of High-Fidelity Volumetric Videos . In Proceedings of the 26th Annual International Conference on Mobile Computing and Networking. Association for Computing Machinery , New York, NY, USA, 14 pages. Kyungjin Lee, Juheon Yi, Youngki Lee, Sunghyun Choi, and Young Min Kim. 2020. GROOT: A Real-Time Streaming System of High-Fidelity Volumetric Videos. In Proceedings of the 26th Annual International Conference on Mobile Computing and Networking. Association for Computing Machinery, New York, NY, USA, 14 pages."},{"key":"e_1_3_2_1_33_1","volume-title":"2017 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE Press, 1513--1518","author":"Li Bo","year":"2017","unstructured":"Bo Li . 2017 . 3D Fully Convolutional Network for Vehicle Detection in Point Cloud . In 2017 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE Press, 1513--1518 . Bo Li. 2017. 3D Fully Convolutional Network for Vehicle Detection in Point Cloud. In 2017 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE Press, 1513--1518."},{"key":"e_1_3_2_1_34_1","unstructured":"Chen-Hsuan Lin Chen Kong and Simon Lucey. 2018. Learning Efficient Point Cloud Generation for Dense 3D Object Reconstruction. In Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence and Thirtieth Innovative Applications of Artificial Intelligence Conference and Eighth AAAI Symposium on Educational Advances in Artificial Intelligence. AAAI Press 8 pages.  Chen-Hsuan Lin Chen Kong and Simon Lucey. 2018. Learning Efficient Point Cloud Generation for Dense 3D Object Reconstruction. In Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence and Thirtieth Innovative Applications of Artificial Intelligence Conference and Eighth AAAI Symposium on Educational Advances in Artificial Intelligence. AAAI Press 8 pages."},{"key":"e_1_3_2_1_35_1","volume-title":"PointAcc: Efficient Point Cloud Accelerator. In MICRO-54: 54th Annual IEEE\/ACM International Symposium on Microarchitecture. Association for Computing Machinery","author":"Lin Yujun","year":"2021","unstructured":"Yujun Lin , Zhekai Zhang , Haotian Tang , Hanrui Wang , and Song Han . 2021 . PointAcc: Efficient Point Cloud Accelerator. In MICRO-54: 54th Annual IEEE\/ACM International Symposium on Microarchitecture. Association for Computing Machinery , New York, NY, USA, 449--461. Yujun Lin, Zhekai Zhang, Haotian Tang, Hanrui Wang, and Song Han. 2021. PointAcc: Efficient Point Cloud Accelerator. In MICRO-54: 54th Annual IEEE\/ACM International Symposium on Microarchitecture. Association for Computing Machinery, New York, NY, USA, 449--461."},{"key":"e_1_3_2_1_36_1","volume-title":"2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society","author":"Liu Xingyu","year":"2019","unstructured":"Xingyu Liu , Charles R Qi , and Leonidas J Guibas . 2019 . FlowNet3D: Learning Scene Flow in 3D Point Clouds . In 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society , Los Alamitos, CA, USA, 529--537. Xingyu Liu, Charles R Qi, and Leonidas J Guibas. 2019. FlowNet3D: Learning Scene Flow in 3D Point Clouds. In 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society, Los Alamitos, CA, USA, 529--537."},{"key":"e_1_3_2_1_37_1","first-page":"9","article-title":"Microscopic 3D reconstruction based on point cloud data generated using defocused images","volume":"54","author":"Liu Xiangjun","year":"2021","unstructured":"Xiangjun Liu , Wenfeng Zheng , Yuanyuan Mou , Yulin Li , and Lirong Yin . 2021 . Microscopic 3D reconstruction based on point cloud data generated using defocused images . Measurement and Control 54 , 9 -- 10 (2021), 1309--1318. Xiangjun Liu, Wenfeng Zheng, Yuanyuan Mou, Yulin Li, and Lirong Yin. 2021. Microscopic 3D reconstruction based on point cloud data generated using defocused images. Measurement and Control 54, 9--10 (2021), 1309--1318.","journal-title":"Measurement and Control"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1109\/MNET.101.2000364"},{"key":"e_1_3_2_1_39_1","unstructured":"Lixin Xue and Oliver Batchelor. 2022. FRNN. https:\/\/github.com\/lxxue\/FRNN.  Lixin Xue and Oliver Batchelor. 2022. FRNN. https:\/\/github.com\/lxxue\/FRNN."},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2016.2543039"},{"key":"e_1_3_2_1_41_1","unstructured":"Microsoft. 2022. Kinect for Windows. \"https:\/\/learn.microsoft.com\/en-us\/windows\/apps\/design\/devices\/kinect-for-windows\".  Microsoft. 2022. Kinect for Windows. \"https:\/\/learn.microsoft.com\/en-us\/windows\/apps\/design\/devices\/kinect-for-windows\"."},{"key":"e_1_3_2_1_42_1","unstructured":"NVIDIA Corporation. 2019. tegrastats Utility. \"https:\/\/docs.nvidia.com\/drive\/drive_os_5.1.6.1L\/nvvib_docs\/index.html#page\/DRIVE_OS_Linux_SDK_Development_Guide\/Utilities\/util_tegrastats.html\".  NVIDIA Corporation. 2019. tegrastats Utility. \"https:\/\/docs.nvidia.com\/drive\/drive_os_5.1.6.1L\/nvvib_docs\/index.html#page\/DRIVE_OS_Linux_SDK_Development_Guide\/Utilities\/util_tegrastats.html\"."},{"key":"e_1_3_2_1_43_1","unstructured":"NVIDIA Corporation. 2022. Jetson AGX Xavier Series. \"https:\/\/www.nvidia.com\/en-us\/autonomous-machines\/embedded-systems\/jetson-agx-xavier\/\".  NVIDIA Corporation. 2022. Jetson AGX Xavier Series. \"https:\/\/www.nvidia.com\/en-us\/autonomous-machines\/embedded-systems\/jetson-agx-xavier\/\"."},{"key":"e_1_3_2_1_44_1","unstructured":"NVIDIA Corporation. 2022. NVIDIA Tensor Cores. \"https:\/\/www.nvidia.com\/en-us\/data-center\/tensor-cores\/\".  NVIDIA Corporation. 2022. NVIDIA Tensor Cores. \"https:\/\/www.nvidia.com\/en-us\/data-center\/tensor-cores\/\"."},{"key":"e_1_3_2_1_45_1","volume-title":"Five balltree construction algorithms","author":"Omohundro Stephen M","unstructured":"Stephen M Omohundro . 1989. Five balltree construction algorithms . International Computer Science Institute Berkeley . Stephen M Omohundro. 1989. Five balltree construction algorithms. International Computer Science Institute Berkeley."},{"key":"e_1_3_2_1_46_1","volume-title":"2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society","author":"Qi Charles R.","unstructured":"Charles R. Qi , Wei Liu , Chenxia Wu , Hao Su , and Leonidas J. Guibas . 2018. Frustum PointNets for 3D Object Detection from RGB-D Data . In 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society , Los Alamitos, CA, USA, 918--927. Charles R. Qi, Wei Liu, Chenxia Wu, Hao Su, and Leonidas J. Guibas. 2018. Frustum PointNets for 3D Object Detection from RGB-D Data. In 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society, Los Alamitos, CA, USA, 918--927."},{"key":"e_1_3_2_1_47_1","volume-title":"2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society","author":"Qi Charles R","year":"2017","unstructured":"Charles R Qi , Hao Su , Kaichun Mo , and Leonidas J Guibas . 2017 . PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation . In 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society , Los Alamitos, CA, USA, 77--85. Charles R Qi, Hao Su, Kaichun Mo, and Leonidas J Guibas. 2017. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation. In 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society, Los Alamitos, CA, USA, 77--85."},{"key":"e_1_3_2_1_48_1","volume-title":"Proceedings of the 31st International Conference on Neural Information Processing Systems. Curran Associates Inc.","author":"Qi Charles R.","unstructured":"Charles R. Qi , Li Yi , Hao Su , and Leonidas J. Guibas . 2017. PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space . In Proceedings of the 31st International Conference on Neural Information Processing Systems. Curran Associates Inc. , Red Hook, NY, USA, 5105--5114. Charles R. Qi, Li Yi, Hao Su, and Leonidas J. Guibas. 2017. PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space. In Proceedings of the 31st International Conference on Neural Information Processing Systems. Curran Associates Inc., Red Hook, NY, USA, 5105--5114."},{"key":"e_1_3_2_1_49_1","unstructured":"Mayank Raj. 2020. Point Clouds and it's significance in AR! \"https:\/\/medium.com\/arway\/point-clouds-and-its-significance-in-ar-155db2673865\".  Mayank Raj. 2020. Point Clouds and it's significance in AR! \"https:\/\/medium.com\/arway\/point-clouds-and-its-significance-in-ar-155db2673865\"."},{"key":"e_1_3_2_1_50_1","unstructured":"Rama C. Hoetzlein. 2014. Fast Fixed-Radius Nearest Neighbor Search on the GPU. https:\/\/tinyurl.com\/4rcjdu7p.  Rama C. Hoetzlein. 2014. Fast Fixed-Radius Nearest Neighbor Search on the GPU. https:\/\/tinyurl.com\/4rcjdu7p."},{"key":"e_1_3_2_1_51_1","doi-asserted-by":"publisher","DOI":"10.1145\/3485444.3487644"},{"key":"e_1_3_2_1_52_1","unstructured":"Ari Rubinsztejn. 2018. What Is The N-body Problem? \"https:\/\/gereshes.com\/2018\/05\/07\/what-is-the-n-body-problem\/\".  Ari Rubinsztejn. 2018. What Is The N-body Problem? \"https:\/\/gereshes.com\/2018\/05\/07\/what-is-the-n-body-problem\/\"."},{"key":"e_1_3_2_1_53_1","unstructured":"SAMSUNG. 2022. Specifications | Galaxy S20 S20+ and S20 Ultra - Samsung. \"https:\/\/www.samsung.com\/levant\/smartphones\/galaxy-s20\/specs\/\".  SAMSUNG. 2022. Specifications | Galaxy S20 S20+ and S20 Ultra - Samsung. \"https:\/\/www.samsung.com\/levant\/smartphones\/galaxy-s20\/specs\/\"."},{"key":"e_1_3_2_1_54_1","volume-title":"Das","author":"Sarma Anup","year":"2021","unstructured":"Anup Sarma , Sonali Singh , Huaipan Jiang , Ashutosh Pattnaik , Asit K. Mishra , Vijaykrishnan Narayanan , Mahmut T. Kandemir , and Chita R . Das . 2021 . Exploiting Activation based Gradient Output Sparsity to Accelerate Backpropagation in CNNs. CoRR abs\/2109.07710 (2021). Anup Sarma, Sonali Singh, Huaipan Jiang, Ashutosh Pattnaik, Asit K. Mishra, Vijaykrishnan Narayanan, Mahmut T. Kandemir, and Chita R. Das. 2021. Exploiting Activation based Gradient Output Sparsity to Accelerate Backpropagation in CNNs. CoRR abs\/2109.07710 (2021)."},{"key":"e_1_3_2_1_55_1","volume-title":"2013 IEEE International Conference on Robotics and Automation. IEEE, 1130--1137","author":"Schulman John","year":"2013","unstructured":"John Schulman , Alex Lee , Jonathan Ho , and Pieter Abbeel . 2013 . Tracking deformable objects with point clouds . In 2013 IEEE International Conference on Robotics and Automation. IEEE, 1130--1137 . John Schulman, Alex Lee, Jonathan Ho, and Pieter Abbeel. 2013. Tracking deformable objects with point clouds. In 2013 IEEE International Conference on Robotics and Automation. IEEE, 1130--1137."},{"key":"e_1_3_2_1_56_1","volume-title":"2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). IEEE Computer Society","author":"Simon Martin","year":"2019","unstructured":"Martin Simon , Karl Amende , Andrea Kraus , Jens Honer , Timo Samann , Hauke Kaulbersch , Stefan Milz , and Horst Michael Gross . 2019 . Complexer-YOLO: Real-Time 3D Object Detection and Tracking on Semantic Point Clouds . In 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). IEEE Computer Society , Los Alamitos, CA, USA, 1190--1199. Martin Simon, Karl Amende, Andrea Kraus, Jens Honer, Timo Samann, Hauke Kaulbersch, Stefan Milz, and Horst Michael Gross. 2019. Complexer-YOLO: Real-Time 3D Object Detection and Tracking on Semantic Point Clouds. In 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). IEEE Computer Society, Los Alamitos, CA, USA, 1190--1199."},{"key":"e_1_3_2_1_57_1","volume-title":"2022 55th IEEE\/ACM International Symposium on Microarchitecture (MICRO). IEEE Computer Society","author":"Singh Sonali","unstructured":"Sonali Singh , Anup Sarma , Sen Lu , Abhronil Sengupta , Mahmut T. Kandemir , Emre Neftci , Vijaykrishnan Narayanan , and Chita R. Das . 2022. Skipper: Enabling efficient SNN training through activation-checkpointing and time-skipping . In 2022 55th IEEE\/ACM International Symposium on Microarchitecture (MICRO). IEEE Computer Society , Los Alamitos, CA, USA, 565--581. Sonali Singh, Anup Sarma, Sen Lu, Abhronil Sengupta, Mahmut T. Kandemir, Emre Neftci, Vijaykrishnan Narayanan, and Chita R. Das. 2022. Skipper: Enabling efficient SNN training through activation-checkpointing and time-skipping. In 2022 55th IEEE\/ACM International Symposium on Microarchitecture (MICRO). IEEE Computer Society, Los Alamitos, CA, USA, 565--581."},{"key":"e_1_3_2_1_58_1","unstructured":"Stanford University Computer Graphics Laboratory. 1994. The Stanford Models. \"http:\/\/graphics.stanford.edu\/data\/3Dscanrep\/\".  Stanford University Computer Graphics Laboratory. 1994. The Stanford Models. \"http:\/\/graphics.stanford.edu\/data\/3Dscanrep\/\"."},{"key":"e_1_3_2_1_59_1","volume-title":"2021 IEEE\/CVF International Conference on Computer Vision (ICCV). IEEE Computer Society","author":"Sun Jiaming","year":"2021","unstructured":"Jiaming Sun , Yiming Xie , Siyu Zhang , Guofeng Zhang , Hujun Bao , and Xiaowei Zhou . 2021 . You Don't Only Look Once: Constructing Spatial-Temporal Memory for Integrated 3D Object Detection and Tracking . In 2021 IEEE\/CVF International Conference on Computer Vision (ICCV). IEEE Computer Society , Los Alamitos, CA, USA, 3265--3174. Jiaming Sun, Yiming Xie, Siyu Zhang, Guofeng Zhang, Hujun Bao, and Xiaowei Zhou. 2021. You Don't Only Look Once: Constructing Spatial-Temporal Memory for Integrated 3D Object Detection and Tracking. In 2021 IEEE\/CVF International Conference on Computer Vision (ICCV). IEEE Computer Society, Los Alamitos, CA, USA, 3265--3174."},{"key":"e_1_3_2_1_60_1","unstructured":"The PyTorch Foundation. 2022. An open source machine learning framework that accelerates the path from research prototyping to production deployment. \"https:\/\/pytorch.org\/\".  The PyTorch Foundation. 2022. An open source machine learning framework that accelerates the path from research prototyping to production deployment. \"https:\/\/pytorch.org\/\"."},{"key":"e_1_3_2_1_61_1","unstructured":"TruePoint Laser Scanning LLC. 2022. What Is 3D Laser Scanning? \"https:\/\/www.truepointscanning.com\/what-is-3d-laser-scanning\".  TruePoint Laser Scanning LLC. 2022. What Is 3D Laser Scanning? \"https:\/\/www.truepointscanning.com\/what-is-3d-laser-scanning\"."},{"key":"e_1_3_2_1_62_1","unstructured":"VREX. 2022. How to Bring Point Clouds into VR. \"https:\/\/www.vrex.no\/blog\/point-cloud-vr\/\".  VREX. 2022. How to Bring Point Clouds into VR. \"https:\/\/www.vrex.no\/blog\/point-cloud-vr\/\"."},{"key":"e_1_3_2_1_63_1","volume-title":"Pie-net: Parametric inference of point cloud edges. Advances in neural information processing systems 33","author":"Wang Xiaogang","year":"2020","unstructured":"Xiaogang Wang , Yuelang Xu , Kai Xu , Andrea Tagliasacchi , Bin Zhou , Ali Mahdavi-Amiri , and Hao Zhang . 2020 . Pie-net: Parametric inference of point cloud edges. Advances in neural information processing systems 33 (2020), 20167--20178. Xiaogang Wang, Yuelang Xu, Kai Xu, Andrea Tagliasacchi, Bin Zhou, Ali Mahdavi-Amiri, and Hao Zhang. 2020. Pie-net: Parametric inference of point cloud edges. Advances in neural information processing systems 33 (2020), 20167--20178."},{"key":"e_1_3_2_1_64_1","volume-title":"2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society","author":"Wu Wenxuan","year":"2019","unstructured":"Wenxuan Wu , Zhongang Qi , and Li Fuxin . 2019 . PointConv: Deep Convolutional Networks on 3D Point Clouds . In 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society , Los Alamitos, CA, USA, 9613--9622. Wenxuan Wu, Zhongang Qi, and Li Fuxin. 2019. PointConv: Deep Convolutional Networks on 3D Point Clouds. In 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society, Los Alamitos, CA, USA, 9613--9622."},{"key":"e_1_3_2_1_65_1","volume-title":"2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society","author":"Wu Zhirong","year":"2015","unstructured":"Zhirong Wu , Shuran Song , Aditya Khosla , Fisher Yu , Linguang Zhang , Xiaoou Tang , and Jianxiong Xiao . 2015 . 3D ShapeNets: A deep representation for volumetric shapes . In 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society , Los Alamitos, CA, USA , 1912--1920. Zhirong Wu, Shuran Song, Aditya Khosla, Fisher Yu, Linguang Zhang, Xiaoou Tang, and Jianxiong Xiao. 2015. 3D ShapeNets: A deep representation for volumetric shapes. In 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society, Los Alamitos, CA, USA, 1912--1920."},{"key":"e_1_3_2_1_66_1","unstructured":"Zhirong Wu Shuran Song Aditya Khosla Fisher Yu Linguang Zhang Xiaoou Tang and Jianxiong Xiao. 2022. Princeton Model Net. \"https:\/\/modelnet.cs.princeton.edu\/\".  Zhirong Wu Shuran Song Aditya Khosla Fisher Yu Linguang Zhang Xiaoou Tang and Jianxiong Xiao. 2022. Princeton Model Net. \"https:\/\/modelnet.cs.princeton.edu\/\"."},{"key":"e_1_3_2_1_67_1","volume-title":"PointASNL: Robust Point Clouds Processing Using Nonlocal Neural Networks With Adaptive Sampling. In 2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society","author":"Yan Xu","year":"2020","unstructured":"Xu Yan , Chaoda Zheng , Zhen Li , Sheng Wang , and Shuguang Cui . 2020 . PointASNL: Robust Point Clouds Processing Using Nonlocal Neural Networks With Adaptive Sampling. In 2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society , Los Alamitos, CA, USA, 5588--5597. Xu Yan, Chaoda Zheng, Zhen Li, Sheng Wang, and Shuguang Cui. 2020. PointASNL: Robust Point Clouds Processing Using Nonlocal Neural Networks With Adaptive Sampling. In 2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society, Los Alamitos, CA, USA, 5588--5597."},{"key":"e_1_3_2_1_68_1","volume-title":"2022 55th IEEE\/ACM International Symposium on Microarchitecture (MICRO). IEEE Computer Society","author":"Ying Ziyu","unstructured":"Ziyu Ying , Shulin Zhao , Sandeepa Bhuyan , Cyan Subhra Mishra , Mahmut T. Kandemir , and Chita R. Das . 2022. Pushing Point Cloud Compression to the Edge . In 2022 55th IEEE\/ACM International Symposium on Microarchitecture (MICRO). IEEE Computer Society , Los Alamitos, CA, USA, 282--299. Ziyu Ying, Shulin Zhao, Sandeepa Bhuyan, Cyan Subhra Mishra, Mahmut T. Kandemir, and Chita R. Das. 2022. Pushing Point Cloud Compression to the Edge. In 2022 55th IEEE\/ACM International Symposium on Microarchitecture (MICRO). IEEE Computer Society, Los Alamitos, CA, USA, 282--299."},{"key":"e_1_3_2_1_69_1","volume-title":"Exploiting Frame Similarity for Efficient Inference on Edge Devices. In 2022 IEEE 42nd International Conference on Distributed Computing Systems (ICDCS). 1073--1084","author":"Ying Ziyu","unstructured":"Ziyu Ying , Shulin Zhao , Haibo Zhang , Cyan Subhra Mishra , Sandeepa Bhuyan , Mahmut T. Kandemir , Anand Sivasubramaniam , and Chita R. Das . 2022 . Exploiting Frame Similarity for Efficient Inference on Edge Devices. In 2022 IEEE 42nd International Conference on Distributed Computing Systems (ICDCS). 1073--1084 . Ziyu Ying, Shulin Zhao, Haibo Zhang, Cyan Subhra Mishra, Sandeepa Bhuyan, Mahmut T. Kandemir, Anand Sivasubramaniam, and Chita R. Das. 2022. Exploiting Frame Similarity for Efficient Inference on Edge Devices. In 2022 IEEE 42nd International Conference on Distributed Computing Systems (ICDCS). 1073--1084."},{"key":"e_1_3_2_1_70_1","volume-title":"Proceedings of the 26th ACM International Conference on Multimedia. Association for Computing Machinery","author":"You Haoxuan","year":"2018","unstructured":"Haoxuan You , Yifan Feng , Rongrong Ji , and Yue Gao . 2018 . PVNet: A Joint Convolutional Network of Point Cloud and Multi-View for 3D Shape Recognition . In Proceedings of the 26th ACM International Conference on Multimedia. Association for Computing Machinery , New York, NY, USA, 1310--1318. Haoxuan You, Yifan Feng, Rongrong Ji, and Yue Gao. 2018. PVNet: A Joint Convolutional Network of Point Cloud and Multi-View for 3D Shape Recognition. In Proceedings of the 26th ACM International Conference on Multimedia. Association for Computing Machinery, New York, NY, USA, 1310--1318."},{"key":"e_1_3_2_1_71_1","volume-title":"MICRO-54: 54th Annual IEEE\/ACM International Symposium on Microarchitecture","author":"Zhang Jie-Fang","unstructured":"Jie-Fang Zhang and Zhengya Zhang . 2021. Point-X: A Spatial-Locality-Aware Architecture for Energy-Efficient Graph-Based Point-Cloud Deep Learning . In MICRO-54: 54th Annual IEEE\/ACM International Symposium on Microarchitecture . Association for Computing Machinery , New York, NY, USA , 1078--1090. Jie-Fang Zhang and Zhengya Zhang. 2021. Point-X: A Spatial-Locality-Aware Architecture for Energy-Efficient Graph-Based Point-Cloud Deep Learning. In MICRO-54: 54th Annual IEEE\/ACM International Symposium on Microarchitecture. Association for Computing Machinery, New York, NY, USA, 1078--1090."},{"key":"e_1_3_2_1_72_1","doi-asserted-by":"crossref","unstructured":"Muhan Zhang Zhicheng Cui Marion Neumann and Yixin Chen. 2018. An End-to-End Deep Learning Architecture for Graph Classification. In Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence and Thirtieth Innovative Applications of Artificial Intelligence Conference and Eighth AAAI Symposium on Educational Advances in Artificial Intelligence. AAAI Press 8 pages.  Muhan Zhang Zhicheng Cui Marion Neumann and Yixin Chen. 2018. An End-to-End Deep Learning Architecture for Graph Classification. In Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence and Thirtieth Innovative Applications of Artificial Intelligence Conference and Eighth AAAI Symposium on Educational Advances in Artificial Intelligence. AAAI Press 8 pages.","DOI":"10.1609\/aaai.v32i1.11782"},{"key":"e_1_3_2_1_73_1","volume-title":"Ziyu Ying, Mahmut T. Kandemir, Anand Sivasubramaniam, and Chita R. Das.","author":"Zhao Shulin","year":"2020","unstructured":"Shulin Zhao , Haibo Zhang , Sandeepa Bhuyan , Cyan Subhra Mishra , Ziyu Ying, Mahmut T. Kandemir, Anand Sivasubramaniam, and Chita R. Das. 2020 . D\u00e9J\u00e0 View: Spatio- Temporal Compute Reuse for Energy-Efficient 360\u00b0 VR Video Streaming. In Proceedings of the ACM\/IEEE 47th Annual International Symposium on Computer Architecture. IEEE Press , 241--253. Shulin Zhao, Haibo Zhang, Sandeepa Bhuyan, Cyan Subhra Mishra, Ziyu Ying, Mahmut T. Kandemir, Anand Sivasubramaniam, and Chita R. Das. 2020. D\u00e9J\u00e0 View: Spatio-Temporal Compute Reuse for Energy-Efficient 360\u00b0 VR Video Streaming. In Proceedings of the ACM\/IEEE 47th Annual International Symposium on Computer Architecture. IEEE Press, 241--253."},{"key":"e_1_3_2_1_74_1","doi-asserted-by":"publisher","DOI":"10.1145\/3466752.3480056"},{"key":"e_1_3_2_1_75_1","volume-title":"2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society","author":"Zhou Yin","year":"2018","unstructured":"Yin Zhou and Oncel Tuzel . 2018 . VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection . In 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society , Los Alamitos, CA, USA, 4490--4499. Yin Zhou and Oncel Tuzel. 2018. VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection. In 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Computer Society, Los Alamitos, CA, USA, 4490--4499."},{"key":"e_1_3_2_1_76_1","volume-title":"Proceedings of the 27th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming. Association for Computing Machinery","author":"Zhu Yuhao","year":"2022","unstructured":"Yuhao Zhu . 2022 . RTNN: Accelerating Neighbor Search Using Hardware Ray Tracing . In Proceedings of the 27th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming. Association for Computing Machinery , New York, NY, USA, 76--89. Yuhao Zhu. 2022. RTNN: Accelerating Neighbor Search Using Hardware Ray Tracing. In Proceedings of the 27th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming. Association for Computing Machinery, New York, NY, USA, 76--89."}],"event":{"name":"ISCA '23: 50th Annual International Symposium on Computer Architecture","location":"Orlando FL USA","acronym":"ISCA '23","sponsor":["SIGARCH ACM Special Interest Group on Computer Architecture","IEEE"]},"container-title":["Proceedings of the 50th Annual International Symposium on Computer Architecture"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3579371.3589113","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T16:46:40Z","timestamp":1750178800000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3579371.3589113"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6,17]]},"references-count":76,"alternative-id":["10.1145\/3579371.3589113","10.1145\/3579371"],"URL":"https:\/\/doi.org\/10.1145\/3579371.3589113","relation":{},"subject":[],"published":{"date-parts":[[2023,6,17]]},"assertion":[{"value":"2023-06-17","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}