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The accurate estimation of six degrees-of-freedom (6DoF) object poses is essential for many applications in robotics and augmented reality.
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Ethan Rublee, Vincent Rabaud, Kurt Konolige, and Gary Bradski · 2011
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Stefan Hinterstoisser, Vincent Lepetit, Slobodan Ilic, Stefan Holzer, Gary Bradski, Kurt Konolige, and Nassir Navab · 2013
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Xiaolong Wang and Abhinav Gupta · 2015
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Going further with point pair features
Stefan Hinterstoisser, Vincent Lepetit, Naresh Rajkumar, and Kurt Konolige · 2016
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Unsupervised learning of visual representations by solving jigsaw puzzles
Mehdi Noroozi and Paolo Favaro · 2016
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Context encoders: Feature learning by inpainting
Deepak Pathak, Philipp Krahenbuhl, Jeff Donahue, Trevor Darrell, and Alexei A Efros · 2016
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An implementation of Deep Belief Networks using restricted Boltzmann machines in Clojure
James Christopher Sims · 2016
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Matching networks for one shot learning
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Pose guided rgbd feature learning for 3d object pose estimation
Vassileios Balntas, Andreas Doumanoglou, Caner Sahin, Juil Sock, Rigas Kouskouridas, and Tae-Kyun Kim · 2017
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Unsupervised learning by predicting noise
Piotr Bojanowski and Armand Joulin · 2017
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Model-agnostic meta-learning for fast adaptation of deep networks
Chelsea Finn, Pieter Abbeel, and Sergey Levine · 2017
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Few-shot learning with graph neural networks
Victor Garcia and Joan Bruna · 2017
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Ssd-6d: Making rgb-based 3d detection and 6d pose estimation great again
Wadim Kehl, Fabian Manhardt, Federico Tombari, Slobodan Ilic, and Nassir Navab · 2017
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Feature pyramid networks for object detection
Tsung-Yi Lin, Piotr Dollár, Ross Girshick, Kaiming He, Bharath Hariharan, and Serge Belongie · 2017
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Adversarial variational bayes: Unifying variational autoencoders and generative adversarial networks
Lars Mescheder, Sebastian Nowozin, and Andreas Geiger · 2017
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Tsendsuren Munkhdalai and Hong Yu · 2017
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Optimization as a model for few-shot learning
Sachin Ravi and Hugo Larochelle · 2017
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Prototypical networks for few-shot learning
Jake Snell, Kevin Swersky, and Richard Zemel · 2017
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Posecnn: A convolutional neural network for 6d object pose estimation in cluttered scenes
Yu Xiang, Tanner Schmidt, Venkatraman Narayanan, and Dieter Fox · 2017
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Learning representations and generative models for 3d point clouds
Panos Achlioptas, Olga Diamanti, Ioannis Mitliagkas, and Leonidas Guibas · 2018
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Deep clustering for unsupervised learning of visual features
Mathilde Caron, Piotr Bojanowski, Armand Joulin, and Matthijs Douze · 2018
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Ppfnet: Global context aware local features for robust 3d point matching
Haowen Deng, Tolga Birdal, and Slobodan Ilic · 2018
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Multiresolution tree networks for 3d point cloud processing
Matheus Gadelha, Rui Wang, and Subhransu Maji · 2018
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A papier-mâché approach to learning 3d surface generation
Thibault Groueix, Matthew Fisher, Vladimir G Kim, Bryan C Russell, and Mathieu Aubry · 2018
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Bop: Benchmark for 6d object pose estimation
Tomas Hodan, Frank Michel, Eric Brachmann, Wadim Kehl, Anders GlentBuch, Dirk Kraft, Bertram Drost, Joel Vidal, Stephan Ihrke, Xenophon Zabulis, et al · 2018
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So-net: Self-organizing network for point cloud analysis
Jiaxin Li, Ben M Chen, and Gim Hee Lee · 2018
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Deepim: Deep iterative matching for 6d pose estimation
Yi Li, Gu Wang, Xiangyang Ji, Yu Xiang, and Dieter Fox · 2018
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Geodesc: Learning local descriptors by integrating geometry constraints
Zixin Luo, Tianwei Shen, Lei Zhou, Siyu Zhu, Runze Zhang, Yao Yao, Tian Fang, and Long Quan · 2018
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Neighbourhood consensus networks
Ignacio Rocco, Mircea Cimpoi, Relja Arandjelović, Akihiko Torii, Tomas Pajdla, and Josef Sivic · 2018
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Implicit 3d orientation learning for 6d object detection from rgb images
Martin Sundermeyer, Zoltan-Csaba Marton, Maximilian Durner, Manuel Brucker, and Rudolph Triebel · 2018
Hybridpose: 6d object pose estimation under hybrid representations
Chen Song, Jiaru Song, and Qixing Huang · 2020
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Multi-path learning for object pose estimation across domains
Martin Sundermeyer, Maximilian Durner, En Yen Puang, Zoltan-Csaba Marton, Narunas Vaskevicius, Kai O Arras, and Rudolph Triebel · 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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Edge enhanced implicit orientation learning with geometric prior for 6d pose estimation
Yilin Wen, Hao Pan, Lei Yang, and Wenping Wang · 2020
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Cost volume pyramid based depth inference for multi-view stereo
Jiayu Yang, Wei Mao, Jose M Alvarez, and Miaomiao Liu · 2020
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inerf: Inverting neural radiance fields for pose estimation
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Real-time seamless single shot 6d object pose prediction
Bugra Tekin, Sudipta N Sinha, and Pascal Fua · 2018
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Point-based multi-view stereo network
Rui Chen, Songfang Han, Jing Xu, and Hao Su · 2019
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Fully convolutional geometric features
Christopher Choy, Jaesik Park, and Vladlen Koltun · 2019
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The perfect match: 3d point cloud matching with smoothed densities
Zan Gojcic, Caifa Zhou, Jan D Wegner, and Andreas Wieser · 2019
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Unsupervised multi-task feature learning on point clouds
Kaveh Hassani and Mike Haley · 2019
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Invariant information clustering for unsupervised image classification and segmentation
Xu Ji, Joao F Henriques, and Andrea Vedaldi · 2019
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Lin Yen-Chen, Pete Florence, Jonathan T Barron, Alberto Rodriguez, Phillip Isola, and Tsung-Yi Lin · 2020
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Self-supervised learning for domain adaptation on point clouds
Idan Achituve, Haggai Maron, and Gal Chechik · 2021
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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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Deep vit features as dense visual descriptors
Shir Amir, Yossi Gandelsman, Shai Bagon, and Tali Dekel · 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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Emerging properties in self-supervised vision transformers
Mathilde Caron, Hugo Touvron, Ishan Misra, Hervé Jégou, Julien Mairal, Piotr Bojanowski, and Armand Joulin · 2021
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Fs-net: Fast shape-based network for category-level 6d object pose estimation with decoupled rotation mechanism
Wei Chen, Xi Jia, Hyung Jin Chang, Jinming Duan, Linlin Shen, and Ales Leonardis · 2021
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3dposelite: a compact 3d pose estimation using node embeddings
Meghal Dani, Karan Narain, and Ramya Hebbalaguppe · 2021
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So-pose: Exploiting self-occlusion for direct 6d pose estimation
Yan Di, Fabian Manhardt, Gu Wang, Xiangyang Ji, Nassir Navab, and Federico Tombari · 2021
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Sparse steerable convolutions: An efficient learning of se (3)-equivariant features for estimation and tracking of object poses in 3d space
Jiehong Lin, Hongyang Li, Ke Chen, Jiangbo Lu, and Kui Jia · 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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Zephyr: Zero-shot pose hypothesis rating
Brian Okorn, Qiao Gu, Martial Hebert, and David Held · 2021
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Distinctive 3d local deep descriptors
Fabio Poiesi and Davide Boscaini · 2021
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Loftr: Detector-free local feature matching with transformers
Jiaming Sun, Zehong Shen, Yuang Wang, Hujun Bao, and Xiaowei Zhou · 2021
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Ibrnet: Learning multi-view image-based rendering
Qianqian Wang, Zhicheng Wang, Kyle Genova, Pratul P Srinivasan, Howard Zhou, Jonathan T Barron, Ricardo Martin-Brualla, Noah Snavely, and Thomas Funkhouser · 2021
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Disentangled implicit shape and pose learning for scalable 6d pose estimation
Yilin Wen, Xiangyu Li, Hao Pan, Lei Yang, Zheng Wang, Taku Komura, and Wenping Wang · 2021
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inerf: Inverting neural radiance fields for pose estimation
Lin Yen-Chen, Pete Florence, Jonathan T Barron, Alberto Rodriguez, Phillip Isola, and Tsung-Yi Lin · 2021
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Chenjie Cao, Xinlin Ren, and Yanwei Fu · 2022
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Epro-pnp: Generalized end-to-end probabilistic perspective-n-points for monocular object pose estimation
Hansheng Chen, Pichao Wang, Fan Wang, Wei Tian, Lu Xiong, and Hao Li · 2022
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icaps: Iterative category-level object pose and shape estimation
Xinke Deng, Junyi Geng, Timothy Bretl, Yu Xiang, and Dieter Fox · 2022
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Gpv-pose: Category-level object pose estimation via geometry-guided point-wise voting
Yan Di, Ruida Zhang, Zhiqiang Lou, Fabian Manhardt, Xiangyang Ji, Nassir Navab, and Federico Tombari · 2022
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Zero-shot category-level object pose estimation
Walter Goodwin, Sagar Vaze, Ioannis Havoutis, and Ingmar Posner · 2022
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Fs6d: Few-shot 6d pose estimation of novel objects
Yisheng He, Yao Wang, Haoqiang Fan, Jian Sun, and Qifeng Chen · 2022
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Parallel inversion of neural radiance fields for robust pose estimation
Yunzhi Lin, Thomas Müller, Jonathan Tremblay, Bowen Wen, Stephen Tyree, Alex Evans, Patricio A Vela, and Stan Birchfield · 2022
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Gen6d: Generalizable model-free 6-dof object pose estimation from rgb images
Yuan Liu, Yilin Wen, Sida Peng, Cheng Lin, Xiaoxiao Long, Taku Komura, and Wenping Wang · 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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Regnerf: Regularizing neural radiance fields for view synthesis from sparse inputs
Michael Niemeyer, Jonathan T Barron, Ben Mildenhall, Mehdi SM Sajjadi, Andreas Geiger, and Noha Radwan · 2022
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Focal length and object pose estimation via render and compare
Georgy Ponimatkin, Yann Labbé, Bryan Russell, Mathieu Aubry, and Josef Sivic · 2022
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Zebrapose: Coarse to fine surface encoding for 6dof object pose estimation
Yongzhi Su, Mahdi Saleh, Torben Fetzer, Jason Rambach, Nassir Navab, Benjamin Busam, Didier Stricker, and Federico Tombari · 2022
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Onepose: One-shot object pose estimation without cad models
Jiaming Sun, Zihao Wang, Siyu Zhang, Xingyi He, Hongcheng Zhao, Guofeng Zhang, and Xiaowei Zhou · 2022
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Onepose++: Keypoint-free one-shot object pose estimation without cad models
Xingyi He, Jiaming Sun, Yuang Wang, Di Huang, Hujun Bao, and Xiaowei Zhou · 2023
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