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We introduce a new RGB-D object dataset captured in the wild called WildRGB-D.
Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography
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Bundle adjustment—a modern synthesis
Bill Triggs, Philip F McLauchlan, Richard I Hartley, and Andrew W Fitzgibbon · 2000
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Zhou Wang, Alan C Bovik, Hamid R Sheikh, and Eero P Simoncelli · 2004
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Simultaneous localization and mapping: part i
Hugh Durrant-Whyte and Tim Bailey · 2006
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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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Parsing ikea objects: Fine pose estimation
Joseph J Lim, Hamed Pirsiavash, and Antonio Torralba · 2013
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Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
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Beyond pascal: A benchmark for 3d object detection in the wild
Yu Xiang, Roozbeh Mottaghi, and Silvio Savarese · 2014
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Shapenet: An information-rich 3d model repository
Angel X Chang, Thomas Funkhouser, Leonidas Guibas, Pat Hanrahan, Qixing Huang, Zimo Li, Silvio Savarese, Manolis Savva, Shuran Song, Hao Su, et al · 2015
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Deep residual learning for image recognition, 2015
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2015
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3d shapenets: A deep representation for volumetric shapes
Zhirong Wu, Shuran Song, Aditya Khosla, Fisher Yu, Linguang Zhang, Xiaoou Tang, and Jianxiong Xiao · 2015
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Large-scale data for multiple-view stereopsis
Henrik Aanæs, Rasmus Ramsbøl Jensen, George Vogiatzis, Engin Tola, and Anders Bjorholm Dahl · 2016
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A large dataset of object scans
Sungjoon Choi, Qian-Yi Zhou, Stephen Miller, and Vladlen Koltun · 2016
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Structure-from-motion revisited
Johannes Lutz Schönberger and Jan-Michael Frahm · 2016
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Structure-from-motion revisited
Johannes L Schonberger and Jan-Michael Frahm · 2016
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Learning category-specific deformable 3d models for object reconstruction
Shubham Tulsiani, Abhishek Kar, Joao Carreira, and Jitendra Malik · 2016
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Relative camera pose estimation using convolutional neural networks
Iaroslav Melekhov, Juha Ylioinas, Juho Kannala, and Esa Rahtu · 2017
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Pointnet: Deep learning on point sets for 3d classification and segmentation, 2017
Charles R. Qi, Hao Su, Kaichun Mo, and Leonidas J. Guibas · 2017
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Deepvo: Towards end-to-end visual odometry with deep recurrent convolutional neural networks
Sen Wang, Ronald Clark, Hongkai Wen, and Niki Trigoni · 2017
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The unreasonable effectiveness of deep features as a perceptual metric
Richard Zhang, Phillip Isola, Alexei A Efros, Eli Shechtman, and Oliver Wang · 2018
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Open3D: A modern library for 3D data processing
Qian-Yi Zhou, Jaesik Park, and Vladlen Koltun · 2018
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Bad slam: Bundle adjusted direct rgb-d slam
Thomas Schops, Torsten Sattler, and Marc Pollefeys · 2019
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Normalized object coordinate space for category-level 6d object pose and size estimation
He Wang, Srinath Sridhar, Jingwei Huang, Julien Valentin, Shuran Song, and Leonidas J Guibas · 2019
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Category level object pose estimation via neural analysis-by-synthesis
Xu Chen, Zijian Dong, Jie Song, Andreas Geiger, and Otmar Hilliges · 2020
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6d object pose regression via supervised learning on point clouds
Ge Gao, Mikko Lauri, Yulong Wang, Xiaolin Hu, Jianwei Zhang, and Simone Frintrop · 2020
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Pointrend: Image segmentation as rendering
Alexander Kirillov, Yuxin Wu, Kaiming He, and Ross Girshick · 2020
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Fabian Manhardt, Gu Wang, Benjamin Busam, Manuel Nickel, Sven Meier, Luca Minciullo, Xiangyang Ji, and Nassir Navab · 2020
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Nerf: Representing scenes as neural radiance fields for view synthesis
Ben Mildenhall, Pratul P. Srinivasan, Matthew Tancik, Jonathan T. Barron, Ravi Ramamoorthi, and Ren Ng · 2020
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Shape prior deformation for categorical 6d object pose and size estimation
Meng Tian, Marcelo H Ang, and Gim Hee Lee · 2020
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Category-level 6d object pose estimation in the wild: A semi-supervised learning approach and a new dataset, 2022
Yang Fu and Xiaolong Wang · 2022
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Get3d: A generative model of high quality 3d textured shapes learned from images
Jun Gao, Tianchang Shen, Zian Wang, Wenzheng Chen, Kangxue Yin, Daiqing Li, Or Litany, Zan Gojcic, and Sanja Fidler · 2022
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Towards self-supervised category-level object pose and size estimation
Yisheng He, Haoqiang Fan, Haibin Huang, Qifeng Chen, and Jian Sun · 2022
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Few-view object reconstruction with unknown categories and camera poses
Hanwen Jiang, Zhenyu Jiang, Kristen Grauman, and Yuke Zhu · 2022
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Single-stage keypoint-based category-level object pose estimation from an rgb image
Yunzhi Lin, Jonathan Tremblay, Stephen Tyree, Patricio A Vela, and Stan Birchfield · 2022
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D3vo: Deep depth, deep pose and deep uncertainty for monocular visual odometry
Nan Yang, Lukas von Stumberg, Rui Wang, and Daniel Cremers · 2020
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Blendedmvs: A large-scale dataset for generalized multi-view stereo networks
Yao Yao, Zixin Luo, Shiwei Li, Jingyang Zhang, Yufan Ren, Lei Zhou, Tian Fang, and Long Quan · 2020
Cited alongside, same era.
Objectron: A large scale dataset of object-centric videos in the wild with pose annotations
Adel Ahmadyan, Liangkai Zhang, Artsiom Ablavatski, Jianing Wei, and Matthias Grundmann · 2021
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Mip-nerf: A multiscale representation for anti-aliasing neural radiance fields
Jonathan T Barron, Ben Mildenhall, Matthew Tancik, Peter Hedman, Ricardo Martin-Brualla, and Pratul P Srinivasan · 2021
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3d-future: 3d furniture shape with texture
Huan Fu, Rongfei Jia, Lin Gao, Mingming Gong, Binqiang Zhao, Steve Maybank, and Dacheng Tao · 2021
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Unsupervised learning of 3d object categories from videos in the wild
Philipp Henzler, Jeremy Reizenstein, Patrick Labatut, Roman Shapovalov, Tobias Ritschel, Andrea Vedaldi, and David Novotny · 2021
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Dualposenet: Category-level 6d object pose and size estimation using dual pose network with refined learning of pose consistency
Jiehong Lin, Zewei Wei, Zhihao Li, Songcen Xu, Kui Jia, and Yuanqing Li · 2021
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Nerf in the dark: High dynamic range view synthesis from noisy raw images
Ben Mildenhall, Peter Hedman, Ricardo Martin-Brualla, Pratul P Srinivasan, and Jonathan T Barron · 2022
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Instant neural graphics primitives with a multiresolution hash encoding
Thomas Müller, Alex Evans, Christoph Schied, and Alexander Keller · 2022
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Self-supervised category-level 6d object pose estimation with deep implicit shape representation
Wanli Peng, Jianhang Yan, Hongtao Wen, and Yi Sun · 2022
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The 8-point algorithm as an inductive bias for relative pose prediction by vits
Chris Rockwell, Justin Johnson, and David F Fouhey · 2022
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Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction
Cheng Sun, Min Sun, and Hwann-Tzong Chen · 2022
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Ref-nerf: Structured view-dependent appearance for neural radiance fields
Dor Verbin, Peter Hedman, Ben Mildenhall, Todd Zickler, Jonathan T Barron, and Pratul P Srinivasan · 2022
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Phocal: A multi-modal dataset for category-level object pose estimation with photometrically challenging objects, 2022
Pengyuan Wang, HyunJun Jung, Yitong Li, Siyuan Shen, Rahul Parthasarathy Srikanth, Lorenzo Garattoni, Sven Meier, Nassir Navab, and Benjamin Busam · 2022
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Voxurf: Voxel-based efficient and accurate neural surface reconstruction
Tong Wu, Jiaqi Wang, Xingang Pan, Xudong Xu, Christian Theobalt, Ziwei Liu, and Dahua Lin · 2022
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Cppf: Towards robust category-level 9d pose estimation in the wild
Yang You, Ruoxi Shi, Weiming Wang, and Cewu Lu · 2022
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Sdfstudio: A unified framework for surface reconstruction, 2022
Zehao Yu, Anpei Chen, Bozidar Antic, Songyou Peng, Apratim Bhattacharyya, Michael Niemeyer, Siyu Tang, Torsten Sattler, and Andreas Geiger · 2022
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Segment and track anything, 2023
Yangming Cheng, Liulei Li, Yuanyou Xu, Xiaodi Li, Zongxin Yang, Wenguan Wang, and Yi Yang · 2023
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Housecat6d – a large-scale multi-modal category level 6d object pose dataset with household objects in realistic scenarios, 2023
HyunJun Jung, Shun-Cheng Wu, Patrick Ruhkamp, Guangyao Zhai, Hannah Schieber, Giulia Rizzoli, Pengyuan Wang, Hongcheng Zhao, Lorenzo Garattoni, Sven Meier, Daniel Roth, Nassir Navab, and Benjamin Busam · 2023
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3d gaussian splatting for real-time radiance field rendering
Bernhard Kerbl, Georgios Kopanas, Thomas Leimkühler, and George Drettakis · 2023
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Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alexander C Berg, Wan-Yen Lo, et al · 2023
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Relpose++: Recovering 6d poses from sparse-view observations
Amy Lin, Jason Y Zhang, Deva Ramanan, and Shubham Tulsiani · 2023
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Sparsepose: Sparse-view camera pose regression and refinement
Samarth Sinha, Jason Y Zhang, Andrea Tagliasacchi, Igor Gilitschenski, and David B Lindell · 2023
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Neus2: Fast learning of neural implicit surfaces for multi-view reconstruction, 2023
Yiming Wang, Qin Han, Marc Habermann, Kostas Daniilidis, Christian Theobalt, and Lingjie Liu · 2023
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Omniobject3d: Large-vocabulary 3d object dataset for realistic perception, reconstruction and generation
Tong Wu, Jiarui Zhang, Xiao Fu, Yuxin Wang, Jiawei Ren, Liang Pan, Wayne Wu, Lei Yang, Jiaqi Wang, Chen Qian, et al · 2023
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Track anything: Segment anything meets videos, 2023
Jinyu Yang, Mingqi Gao, Zhe Li, Shang Gao, Fangjing Wang, and Feng Zheng · 2023
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Mvimgnet: A large-scale dataset of multi-view images, 2023
Xianggang Yu, Mutian Xu, Yidan Zhang, Haolin Liu, Chongjie Ye, Yushuang Wu, Zizheng Yan, Chenming Zhu, Zhangyang Xiong, Tianyou Liang, Guanying Chen, Shuguang Cui, and Xiaoguang Han · 2023
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