{"type":"ScholarlyArticle","title":"HVOFusion: Incremental Mesh Reconstruction Using Hybrid Voxel Octree","authors":[{"name":"Shaofan Liu","slug":"shaofan-liu","given":"Shaofan","family":"Liu","affiliation":"Zhejiang University"},{"name":"Junbo Chen","slug":"junbo-chen","given":"Junbo","family":"Chen","affiliation":"Zhejiang University"},{"name":"Jianke Zhu","slug":"jianke-zhu","given":"Jianke","family":"Zhu","affiliation":"Zhejiang University"}],"abstract":"Incremental scene reconstruction is essential to the navigation in robotics. Most of the conventional methods typically make use of either TSDF (truncated signed distance functions) volume or neural networks to implicitly represent the surface. Due to the voxel representation or involving with time-consuming sampling, they have difficulty in balancing speed, memory storage, and surface quality. In this paper, we propose a novel hybrid voxel-octree approach to effectively fuse octree with voxel structures so that we can take advantage of both implicit surface and explicit triangular mesh representation. Such sparse structure preserves triangular faces in the leaf nodes and produces partial meshes sequentially for incremental reconstruction. This storage scheme allows us to naturally optimize the mesh in explicit 3D space to achieve higher surface quality. We iteratively deform the mesh towards the target and recovers vertex colors by optimizing a shading model. Experimental results on several datasets show that our proposed approach is capable of quickly and accurately reconstructing a scene with realistic colors. Code is available at https://github.com/Frankuzi/HVOFusion","doi":"10.24963/ijcai.2024/757","url":"https://ijcai.org/proceedings/2024/757","pdf":"https://ijcai.org/proceedings/2024/0757.pdf","markdown":"https://ijcai.org/proceedings/2024/757.md","bibtex":"https://ijcai.org/proceedings/2024/bibtex/757","volume":{"slug":"2024","title":"Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2024","url":"https://ijcai.org/proceedings/2024/","year":2024,"location":"Jeju, Korea","dates":"3-9 August 2024","editors":"Kate Larson","isbn":"978-1-956792-04-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2024"},"section":"Robotics","track":"Main Track","number":757,"pages":{"first":6850,"last":6858},"keywords":["Computer Vision: CV: Applications","Robotics: ROB: Robotics and vision","Robotics: ROB: Localization, mapping, state estimation","Computer Vision: CV: 3D computer vision"],"videos":[],"references":[{"position":1,"raw":"[Breitenmoser and Siegwart, 2012] Andreas Breitenmoser and Roland Siegwart. Surface reconstruction and path planning for industrial inspection with a climbing robot. In 2012 2nd International Conference on Applied Robotics for the Power Industry (CARPI), pages 22-27. IEEE, 2012.","title":"Surface reconstruction and path planning for industrial inspection with a climbing robot","authors":"Siegwart Breitenmoser, Andreas Breitenmoser, Roland Siegwart","year":"2012","venue":"2nd International Conference on Applied Robotics for the Power Industry (CARPI)","doi":null,"url":null,"internal_url":null},{"position":2,"raw":"[Curless and Levoy, 1996] Brian Curless and Marc Levoy. A volumetric method for building complex models from range images. In Proceedings of the 23rd annual con- ference on Computer graphics and interactive techniques, pages 303-312, 1996.","title":"A volumetric method for building complex models from range images","authors":"Brian Curless, Marc Levoy","year":"1996","venue":"Proceedings of the 23rd annual conference on Computer graphics and interactive techniques","doi":null,"url":null,"internal_url":null},{"position":3,"raw":"[Dai et al., 2017] Angela Dai, Matthias Nießner, Michael Zollhöfer, Shahram Izadi, and Christian Theobalt. Bundle- fusion: Real-time globally consistent 3d reconstruction us- ing on-the-fly surface reintegration. ACM Transactions on Graphics (ToG), 36(4):1, 2017.","title":"Bundlefusion: Real-time globally consistent 3d reconstruction using on-the-fly surface reintegration","authors":"Angela Dai, Matthias Nießner, Michael Zollhöfer, Shahram Izadi, Christian Theobalt","year":"2017","venue":"ACM Transactions on Graphics (ToG)","doi":null,"url":null,"internal_url":null},{"position":4,"raw":"[Engel et al., 2013] Jakob Engel, Jurgen Sturm, and Daniel Cremers. Semi-dense visual odometry for a monocular camera. In Proceedings of the IEEE international confer- ence on computer vision, pages 1449-1456, 2013.","title":"Semi-dense visual odometry for a monocular camera","authors":"Engel","year":"2013","venue":"Proceedings of the IEEE international conference on computer vision","doi":null,"url":null,"internal_url":null},{"position":5,"raw":"[Gao et al., 2020] Jun Gao, Wenzheng Chen, Tommy Xi- ang, Alec Jacobson, Morgan McGuire, and Sanja Fidler. Learning deformable tetrahedral meshes for 3d reconstruc- tion. Advances In Neural Information Processing Systems, 33:9936-9947, 2020.","title":"Learning deformable tetrahedral meshes for 3d reconstruction","authors":"Gao","year":"2020","venue":"Advances In Neural Information Processing Systems","doi":null,"url":null,"internal_url":null},{"position":6,"raw":"[Guédon and Lepetit, 2023] Antoine Guédon and Vincent Lepetit. Sugar: Surface-aligned gaussian splatting for ef- ficient 3d mesh reconstruction and high-quality mesh ren- dering. arXiv preprint arXiv:2311.12775, 2023.","title":"Sugar: Surface-aligned gaussian splatting for efficient 3d mesh reconstruction and high-quality mesh rendering","authors":"Lepetit Guédon, Antoine Guédon, Vincent Lepetit","year":"2023","venue":null,"doi":null,"url":null,"internal_url":null},{"position":7,"raw":"[Häne et al., 2017] Christian Häne, Lionel Heng, Gim Hee Lee, Friedrich Fraundorfer, Paul Furgale, Torsten Sattler, and Marc Pollefeys. 3d visual perception for self-driving cars using a multi-camera system: Calibration, mapping, localization, and obstacle detection. Image and Vision Computing, 68:14-27, 2017.","title":"3d visual perception for self-driving cars using a multi-camera system: Calibration, mapping, localization, and obstacle detection","authors":"Häne","year":"2017","venue":"Image and Vision Computing","doi":null,"url":null,"internal_url":null},{"position":8,"raw":"[Hanocka et al., 2020] Rana Hanocka, Gal Metzer, Raja Giryes, and Daniel Cohen-Or. Point2mesh: A self-prior for deformable meshes. ACM Trans. Graph., 39(4), 2020.","title":"Point2mesh: A self-prior for deformable meshes","authors":"Rana Hanocka, Gal Metzer, Raja Giryes, Daniel Cohen-Or","year":"2020","venue":"ACM Trans. Graph","doi":null,"url":null,"internal_url":null},{"position":9,"raw":"[Izadi et al., 2011] Shahram Izadi, David Kim, Otmar Hilliges, David Molyneaux, Richard Newcombe, Push- meet Kohli, Jamie Shotton, Steve Hodges, Dustin Free- man, Andrew Davison, et al. Kinectfusion: real-time 3d reconstruction and interaction using a moving depth cam- era. In Proceedings of the 24th annual ACM symposium on User interface software and technology, pages 559-568, 2011.","title":"Kinectfusion: real-time 3d reconstruction and interaction using a moving depth camera","authors":"Shahram Izadi, David Kim, Otmar Hilliges, David Molyneaux, Richard Newcombe, Pushmeet Kohli, Jamie Shotton, Steve Hodges, Dustin Freeman, Andrew Davison","year":"2011","venue":"Proceedings of the 24th annual ACM symposium on User interface software and technology","doi":null,"url":null,"internal_url":null},{"position":10,"raw":"[Johari et al., 2023] Mohammad Mahdi Johari, Camilla Carta, and Franc ¸ois Fleuret. Eslam: Efficient dense slam system based on hybrid representation of signed distance fields. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 17408- 17419, 2023.","title":"Eslam: Efficient dense slam system based on hybrid representation of signed distance fields","authors":"Mohammad Mahdi, Johari, Camilla Carta, Franc ¸ois, Fleuret","year":"2023","venue":"Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition","doi":null,"url":null,"internal_url":null},{"position":11,"raw":"[Keetha et al., 2023] Nikhil Keetha, Jay Karhade, Kr- ishna Murthy Jatavallabhula, Gengshan Yang, Sebastian Scherer, Deva Ramanan, and Jonathon Luiten. Splatam: Splat, track & map 3d gaussians for dense rgb-d slam. arXiv preprint arXiv:2312.02126, 2023.","title":"Splatam: Splat, track & map 3d gaussians for dense rgb-d slam","authors":"Nikhil Keetha, Jay Karhade, Krishna Murthy Jatavallabhula, Gengshan Yang, Sebastian Scherer, Deva Ramanan, Jonathon Luiten","year":"2023","venue":null,"doi":null,"url":null,"internal_url":null},{"position":12,"raw":"[Kerbl et al., 2023] Bernhard Kerbl, Georgios Kopanas, Thomas Leimkühler, and George Drettakis. 3d gaus- sian splatting for real-time radiance field rendering. ACM Transactions on Graphics, 42(4), July 2023.","title":"3d gaussian splatting for real-time radiance field rendering","authors":"Bernhard Kerbl, Georgios Kopanas, Thomas Leimkühler, George Drettakis","year":"2023","venue":"ACM Transactions on Graphics","doi":null,"url":null,"internal_url":null},{"position":13,"raw":"[Kim et al., 2010] Hansung Kim, Muhammad Sarim, Takeshi Takai, Jean-Yves Guillemaut, and Adrian Hilton. Dynamic 3d scene reconstruction in outdoor environ- ments. In In Proc. IEEE Symp. on 3D Data Processing and Visualization, 2010.","title":"Dynamic 3d scene reconstruction in outdoor environments","authors":"Hansung Kim, Muhammad Sarim, Takeshi Takai, Jean-Yves Guillemaut, Adrian Hilton","year":"2010","venue":"Proc. IEEE Symp. on 3D Data Processing and Visualization","doi":null,"url":null,"internal_url":null},{"position":14,"raw":"[Liu et al., 2019] Shichen Liu, Tianye Li, Weikai Chen, and Hao Li. Soft rasterizer: A differentiable renderer for image-based 3d reasoning. In Proceedings of the IEEE/CVF International Conference on Computer Vision, pages 7708-7717, 2019.","title":"Soft rasterizer: A differentiable renderer for image-based 3d reasoning","authors":"Liu","year":"2019","venue":"Proceedings of the IEEE/CVF International Conference on Computer Vision","doi":null,"url":null,"internal_url":null},{"position":15,"raw":"[Lorensen and Cline, 1987] William E. Lorensen and Har- vey E. Cline. Marching cubes: A high resolution 3d sur- face construction algorithm. In Proceedings of the 14th Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH '87, page 163-169, New York, NY, USA, 1987. Association for Computing Machinery.","title":"Marching cubes: A high resolution 3d surface construction algorithm","authors":"William E Lorensen, Harvey E Cline","year":"1987","venue":"Proceedings of the 14th Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH '87","doi":null,"url":null,"internal_url":null},{"position":16,"raw":"[Luan et al., 2021] Fujun Luan, Shuang Zhao, Kavita Bala, and Zhao Dong. Unified shape and svbrdf recovery using differentiable monte carlo rendering. In Computer Graph- ics Forum, volume 40, pages 101-113. Wiley Online Li- brary, 2021.","title":"Unified shape and svbrdf recovery using differentiable monte carlo rendering","authors":"Luan","year":"2021","venue":"Computer Graphics Forum","doi":null,"url":null,"internal_url":null},{"position":17,"raw":"[Mildenhall et al., 2021] Ben Mildenhall, Pratul P Srini- vasan, Matthew Tancik, Jonathan T Barron, Ravi Ra- mamoorthi, and Ren Ng. Nerf: Representing scenes as neural radiance fields for view synthesis. Communications of the ACM, 65(1):99-106, 2021.","title":"Nerf: Representing scenes as neural radiance fields for view synthesis","authors":"Ben Mildenhall, P Pratul, Matthew Srinivasan, Jonathan T Tancik, Ravi Barron, Ren Ramamoorthi, Ng","year":"2021","venue":"Communications of the ACM","doi":null,"url":null,"internal_url":null},{"position":18,"raw":"[Ming et al., 2022] Yuhang Ming, Weicai Ye, and Andrew Calway. idf-slam: End-to-end rgb-d slam with neural im- plicit mapping and deep feature tracking. arXiv preprint arXiv:2209.07919, 2022.","title":"idf-slam: End-to-end rgb-d slam with neural implicit mapping and deep feature tracking","authors":"Yuhang Ming, Weicai Ye, Andrew Calway","year":"2022","venue":null,"doi":null,"url":null,"internal_url":null},{"position":19,"raw":"[Munkberg et al., 2022] Jacob Munkberg, Jon Hasselgren, Tianchang Shen, Jun Gao, Wenzheng Chen, Alex Evans, Thomas Müller, and Sanja Fidler. Extracting triangular 3d models, materials, and lighting from images. In Proceed- ings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 8280-8290, 2022.","title":"Extracting triangular 3d models, materials, and lighting from images","authors":"Jacob Munkberg, Jon Hasselgren, Tianchang Shen, Jun Gao, Wenzheng Chen, Alex Evans, Thomas Müller, Sanja Fidler","year":"2022","venue":"Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition","doi":null,"url":null,"internal_url":null},{"position":20,"raw":"[Nießner et al., 2013] Matthias Nießner, Michael Zollhöfer, Shahram Izadi, and Marc Stamminger. Real-time 3d re- construction at scale using voxel hashing. ACM Transac- tions on Graphics (ToG), 32(6):1-11, 2013.","title":"Real-time 3d reconstruction at scale using voxel hashing","authors":"Matthias Nießner, Michael Zollhöfer, Shahram Izadi, Marc Stamminger","year":"2013","venue":"ACM Transactions on Graphics (ToG)","doi":null,"url":null,"internal_url":null},{"position":21,"raw":"[Ortiz et al., 2022] Joseph Ortiz, Alexander Clegg, Jing Dong, Edgar Sucar, David Novotny, Michael Zollhoefer, and Mustafa Mukadam. isdf: Real-time neural signed dis- tance fields for robot perception. In Robotics: Science and Systems, 2022.","title":"isdf: Real-time neural signed distance fields for robot perception","authors":"Joseph Ortiz, Alexander Clegg, Jing Dong, Edgar Sucar, David Novotny, Michael Zollhoefer, Mustafa Mukadam","year":"2022","venue":"Robotics: Science and Systems","doi":null,"url":null,"internal_url":null},{"position":22,"raw":"[Prisacariu et al., 2017] V A Prisacariu, O Kähler, S Golodetz, M Sapienza, T Cavallari, P H S Torr, and D W Murray. InfiniTAM v3: A Framework for Large-Scale 3D Reconstruction with Loop Closure. arXiv pre-print arXiv:1708.00783v1, 2017.","title":"InfiniTAM v3: A Framework for Large-Scale 3D Reconstruction with Loop Closure","authors":"O V A Prisacariu, S Kähler, M Golodetz, T Sapienza, P H S Cavallari, D W Torr, Murray","year":"2017","venue":null,"doi":null,"url":null,"internal_url":null},{"position":23,"raw":"[Ramezani et al., 2020] Milad Ramezani, Yiduo Wang, Marco Camurri, David Wisth, Matias Mattamala, and Maurice Fallon. The newer college dataset: Handheld lidar, inertial and vision with ground truth. In 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 4353-4360, 2020.","title":"The newer college dataset: Handheld lidar, inertial and vision with ground truth","authors":"Milad Ramezani, Yiduo Wang, Marco Camurri, David Wisth, Matias Mattamala, Maurice Fallon","year":"2020","venue":"IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","doi":null,"url":null,"internal_url":null},{"position":24,"raw":"[Reijgwart et al., 2019] Victor Reijgwart, Alexander Mil- lane, Helen Oleynikova, Roland Siegwart, Cesar Cadena, and Juan Nieto. Voxgraph: Globally consistent, volu- metric mapping using signed distance function submaps. IEEE Robotics and Automation Letters, 5(1):227-234, 2019.","title":"Voxgraph: Globally consistent, volumetric mapping using signed distance function submaps","authors":"Victor Reijgwart, Alexander Millane, Helen Oleynikova, Roland Siegwart, Cesar Cadena, Juan Nieto","year":"2019","venue":"IEEE Robotics and Automation Letters","doi":null,"url":null,"internal_url":null},{"position":25,"raw":"[Schonberger and Frahm, 2016] Johannes L Schonberger and Jan-Michael Frahm. Structure-from-motion revisited. In Proceedings of the IEEE conference on computer vision and pattern recognition, pages 4104-4113, 2016.","title":"Structure-from-motion revisited","authors":"Frahm ; Schonberger, L Johannes, Jan-Michael Schonberger, Frahm","year":"2016","venue":"Proceedings of the IEEE conference on computer vision and pattern recognition","doi":null,"url":null,"internal_url":null},{"position":26,"raw":"[Schöps et al., 2019] Thomas Schöps, Torsten Sattler, and Marc Pollefeys. Surfelmeshing: Online surfel-based mesh reconstruction. IEEE transactions on pattern analysis and machine intelligence, 42(10):2494-2507, 2019.","title":"Surfelmeshing: Online surfel-based mesh reconstruction","authors":"Thomas Schöps, Torsten Sattler, Marc Pollefeys","year":"2019","venue":"IEEE transactions on pattern analysis and machine intelligence","doi":null,"url":null,"internal_url":null},{"position":27,"raw":"[Sharf et al., 2006] Andrei Sharf, Thomas Lewiner, Ariel Shamir, Leif Kobbelt, and Daniel Cohen-Or. Competing fronts for coarse-to-fine surface reconstruction. In Com- puter Graphics Forum, volume 25, pages 389-398. Wiley Online Library, 2006.","title":"Competing fronts for coarse-to-fine surface reconstruction","authors":"Andrei Sharf, Thomas Lewiner, Ariel Shamir, Leif Kobbelt, Daniel Cohen-Or","year":"2006","venue":"Computer Graphics Forum","doi":null,"url":null,"internal_url":null},{"position":28,"raw":"[Shen et al., 2021] Tianchang Shen, Jun Gao, Kangxue Yin, Ming-Yu Liu, and Sanja Fidler. Deep marching tetrahedra: a hybrid representation for high-resolution 3d shape syn- thesis. Advances in Neural Information Processing Sys- tems, 34:6087-6101, 2021.","title":"Deep marching tetrahedra: a hybrid representation for high-resolution 3d shape synthesis","authors":"Shen","year":"2021","venue":"Advances in Neural Information Processing Systems","doi":null,"url":null,"internal_url":null},{"position":29,"raw":"[Straub et al., 2019] Julian Straub, Thomas Whelan, Lingni Ma, Yufan Chen, Erik Wijmans, Simon Green, Jakob J. Engel, Raul Mur-Artal, Carl Ren, Shobhit Verma, Anton Clarkson, Mingfei Yan, Brian Budge, Yajie Yan, Xiaqing Pan, June Yon, Yuyang Zou, Kimberly Leon, Nigel Carter, Jesus Briales, Tyler Gillingham, Elias Mueggler, Luis Pesqueira, Manolis Savva, Dhruv Batra, Hauke M. Stras- dat, Renzo De Nardi, Michael Goesele, Steven Lovegrove, and Richard Newcombe. The Replica dataset: A digital replica of indoor spaces. arXiv preprint arXiv:1906.05797, 2019.","title":"The Replica dataset: A digital replica of indoor spaces","authors":"Julian Straub, Thomas Whelan, Lingni Ma, Yufan Chen, Erik Wijmans, Simon Green, Jakob J Engel, Raul Mur-Artal, Carl Ren, Shobhit Verma, Anton Clarkson, Mingfei Yan, Brian Budge, Yajie Yan, Xiaqing Pan, June Yon, Yuyang Zou, Kimberly Leon, Nigel Carter, Jesus Briales, Tyler Gillingham, Elias Mueggler, Luis Pesqueira, Manolis Savva, Dhruv Batra, M Hauke, Renzo Strasdat, Michael De Nardi, Steven Goesele, Richard Lovegrove, Newcombe","year":"2019","venue":null,"doi":null,"url":null,"internal_url":null},{"position":30,"raw":"[Sucar et al., 2021] Edgar Sucar, Shikun Liu, Joseph Ortiz, and Andrew J Davison. imap: Implicit mapping and posi- tioning in real-time. In Proceedings of the IEEE/CVF In- ternational Conference on Computer Vision, pages 6229- 6238, 2021.","title":"imap: Implicit mapping and positioning in real-time","authors":"Edgar Sucar, Shikun Liu, Joseph Ortiz, Andrew J Davison","year":"2021","venue":"Proceedings of the IEEE/CVF International Conference on Computer Vision","doi":null,"url":null,"internal_url":null},{"position":31,"raw":"[Thies et al., 2019] Justus Thies, Michael Zollhöfer, and Matthias Nießner. Deferred neural rendering: Image syn- thesis using neural textures. Acm Transactions on Graph- ics (TOG), 38(4):1-12, 2019.","title":"Deferred neural rendering: Image syn-thesis using neural textures","authors":"Justus Thies, Michael Zollhöfer, Matthias Nießner","year":"2019","venue":"Acm Transactions on Graphics (TOG)","doi":null,"url":null,"internal_url":null},{"position":32,"raw":"[Vizzo et al., 2021] I. Vizzo, X. Chen, N. Chebrolu, J. Behley, and C. Stachniss. Poisson Surface Reconstruc- tion for LiDAR Odometry and Mapping. In Proc. of the IEEE Intl. Conf. on Robotics & Automation (ICRA), 2021.","title":"Poisson Surface Reconstruction for LiDAR Odometry and Mapping","authors":"Vizzo","year":"2021","venue":"Proc. of the IEEE Intl. Conf. on Robotics & Automation (ICRA)","doi":null,"url":null,"internal_url":null},{"position":33,"raw":"[Walker et al., 2023] Thomas Walker, Octave Mariotti, Amir Vaxman, and Hakan Bilen. Explicit neural surfaces: Learning continuous geometry with deformation fields. NeurIPS, 2023.","title":"Explicit neural surfaces: Learning continuous geometry with deformation fields","authors":"Thomas Walker, Octave Mariotti, Amir Vaxman, Hakan Bilen","year":"2023","venue":null,"doi":null,"url":null,"internal_url":null},{"position":34,"raw":"[Wang et al., 2018] Nanyang Wang, Yinda Zhang, Zhuwen Li, Yanwei Fu, Wei Liu, and Yu-Gang Jiang. Pixel2mesh: Generating 3d mesh models from single rgb images. In Proceedings of the European conference on computer vi- sion (ECCV), pages 52-67, 2018.","title":"Pixel2mesh: Generating 3d mesh models from single rgb images","authors":"Wang","year":"2018","venue":"Proceedings of the European conference on computer vision (ECCV)","doi":null,"url":null,"internal_url":null},{"position":35,"raw":"[Wang et al., 2022] Jingwen Wang, Tymoteusz Bleja, and Lourdes Agapito. Go-surf: Neural feature grid optimiza- tion for fast, high-fidelity rgb-d surface reconstruction. In 2022 International Conference on 3D Vision (3DV). IEEE, 2022.","title":"Go-surf: Neural feature grid optimization for fast, high-fidelity rgb-d surface reconstruction","authors":"Jingwen Wang, Tymoteusz Bleja, Lourdes Agapito","year":"2022","venue":"2022 International Conference on 3D Vision (3DV)","doi":null,"url":null,"internal_url":null},{"position":36,"raw":"[Whelan et al., 2012] Thomas Whelan, John B McDonald, Michael Kaess, Maurice Fallon, Hordur Johannsson, and John J Leonard. Kintinuous: Spatially extended kinectfu- sion. In RSS '12 Workshop on RGB-D: Advanced Reason- ing with Depth Cameras, pages 1, 6, 2012.","title":"Kintinuous: Spatially extended kinectfusion","authors":"Thomas Whelan, John B Mcdonald, Michael Kaess, Maurice Fallon, Hordur Johannsson, John J Leonard","year":"2012","venue":"RSS '12 Workshop on RGB-D: Advanced Reasoning with Depth Cameras","doi":null,"url":null,"internal_url":null},{"position":37,"raw":"[Whelan et al., 2015] Thomas Whelan, Michael Kaess, Hor- dur Johannsson, Maurice Fallon, John J Leonard, and John McDonald. Real-time large-scale dense rgb-d slam with volumetric fusion. The International Journal of Robotics Research, 34(4-5):598-626, 2015.","title":"Real-time large-scale dense rgb-d slam with volumetric fusion","authors":"Thomas Whelan, Michael Kaess, Hordur Johannsson, Maurice Fallon, John J Leonard, John Mcdonald","year":"2015","venue":"The International Journal of Robotics Research","doi":null,"url":null,"internal_url":null},{"position":38,"raw":"[Worchel et al., 2022] Markus Worchel, Rodrigo Diaz, Wei- wen Hu, Oliver Schreer, Ingo Feldmann, and Peter Eisert. Multi-view mesh reconstruction with neural deferred shad- ing. In Proceedings of the IEEE/CVF Conference on Com- puter Vision and Pattern Recognition, pages 6187-6197, 2022.","title":"Multi-view mesh reconstruction with neural deferred shading","authors":"Markus Worchel, Rodrigo Diaz, Weiwen Hu, Oliver Schreer, Ingo Feldmann, Peter Eisert","year":"2022","venue":"Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition","doi":null,"url":null,"internal_url":null},{"position":39,"raw":"[Wu et al., 2011] Chenglei Wu, Bennett Wilburn, Yasuyuki Matsushita, and Christian Theobalt. High-quality shape from multi-view stereo and shading under general illumi- nation. In CVPR 2011, pages 969-976. IEEE, 2011.","title":"High-quality shape from multi-view stereo and shading under general illumination","authors":"Wu","year":"2011","venue":"CVPR 2011","doi":null,"url":null,"internal_url":null},{"position":40,"raw":"[Yang et al., 2022] Xingrui Yang, Hai Li, Hongjia Zhai, Yuhang Ming, Yuqian Liu, and Guofeng Zhang. Vox- fusion: Dense tracking and mapping with voxel-based neural implicit representation. In 2022 IEEE International Symposium on Mixed and Augmented Reality (ISMAR), pages 499-507. IEEE, 2022.","title":"Voxfusion: Dense tracking and mapping with voxel-based neural implicit representation","authors":"Yang","year":"2022","venue":"IEEE International Symposium on Mixed and Augmented Reality (ISMAR)","doi":null,"url":null,"internal_url":null},{"position":41,"raw":"[Yeshwanth et al., 2023] Chandan Yeshwanth, Yueh-Cheng Liu, Matthias Nießner, and Angela Dai. Scannet++: A high-fidelity dataset of 3d indoor scenes. In Proceedings of the International Conference on Computer Vision, 2023.","title":"Scannet++: A high-fidelity dataset of 3d indoor scenes","authors":"Chandan Yeshwanth, Yueh-Cheng Liu, Matthias Nießner, Angela Dai","year":"2023","venue":"Proceedings of the International Conference on Computer Vision","doi":null,"url":null,"internal_url":null},{"position":42,"raw":"[Zhu et al., 2022] Zihan Zhu, Songyou Peng, Viktor Lars- son, Weiwei Xu, Hujun Bao, Zhaopeng Cui, Martin R Oswald, and Marc Pollefeys. Nice-slam: Neural im- plicit scalable encoding for slam. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 12786-12796, 2022.","title":"Nice-slam: Neural implicit scalable encoding for slam","authors":"Zihan Zhu, Songyou Peng, Viktor Larsson, Weiwei Xu, Hujun Bao, Zhaopeng Cui, Martin R Oswald, Marc Pollefeys","year":"2022","venue":"Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition","doi":null,"url":null,"internal_url":null}],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}