awesome-object-pose

This repository is a curated list of papers and open source code for 6D Object Pose Estimation.

Papers

• Segmentation-driven 6D Object Pose Estimation - Yinlin Hu, Joachim Hugonot, Pascal Fua, Mathieu Salzmann.[Paper]
• HybridPose: 6D Object Pose Estimation under Hybrid Representations - Chen Song, Jiaru Song, Qixing Huang. [Paper]
• Single-Stage 6D Object Pose Estimation - Yinlin Hu,Pascal Fua,Wei Wang,Mathieu Salzmann. [Paper]
• SilhoNet: An RGB Method for 6D Object Pose Estimation - Gideon Billings, Matthew Johnson-Roberson. [Paper]
• PVNet: Pixel-wise Voting Network for 6DoF Pose Estimation - Sida Peng, Yuan Liu, Qixing Huang, Xiaowei Zhou, Hujun Bao. [Paper]
• Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimation - He Wang, Srinath Sridhar, Jingwei Huang, Julien Valentin, Shuran Song, Leonidas J. Guibas. [Paper]
• DPOD: 6D Pose Object Detector and Refiner - Sergey Zakharov, Ivan Shugurov, Slobodan Ilic. [Paper]
• Instance- and Category-level 6D Object Pose Estimation - Caner Sahin, Guillermo Garcia-Hernando, Juil Sock, Tae-Kyun Kim. [Paper]
• Vision-based Robotic Grasping from Object Localization, Pose Estimation, Grasp Detection to Motion Planning: A Review - Guoguang Du, Kai Wang, Shiguo Lian. [Paper]
• HomebrewedDB: RGB-D Dataset for 6D Pose Estimation of 3D Objects - Roman Kaskman, Sergey Zakharov, Ivan Shugurov, Slobodan Ilic. [Paper]
• Summary of the 4th International Workshopon Recovering 6D Object Pose - Tomas Hodan, Rigas Kouskouridas, Tae-Kyun Kim, Federico Tombari, Kostas Bekris, Bertram Drost, Thibault Groueix, Krzysztof Walas, Vincent Lepetit, Ales Leonardis, Carsten Steger, Frank Michel, Caner Sahin, Carsten Rother, Jirı Matas. [Paper]
• DeepIM: Deep Iterative Matching for 6D Pose Estimation - Yi Li, Gu Wang, Xiangyang Ji, Yu Xiang, Dieter Fox. [Paper]
• Robust 6D Object Pose Estimation in Cluttered Scenesusing Semantic Segmentation and Pose Regression Networks - Arul Selvam Periyasamy, Max Schwarz, and Sven Behnke. [Paper]
• Category-level 6D Object Pose Recovery in Depth Images - Caner Sahin and Tae-Kyun Kim. [Paper]
• Matching RGB Images to CAD Models for Object Pose Estimation - Georgios Georgakis, Srikrishna Karanam, Ziyan Wu, and Jana Kosecka. [Paper]
• Implicit 3D Orientation Learning for 6D Object Detection from RGB Images - Martin Sundermeyer, Zoltan-Csaba Marton, Maxmilian Durner, Manuel Brucker and Rudolph Triebel. [Paper]
• DenseFusion: 6D Object Pose Estimation by Iterative Dense Fusion - Chen Wang, Danfei Xu, Yuke Zhu, Roberto Martín-Martín, Cewu Lu, Li Fei-Fei, Silvio Savarese. [Paper]
• Real-Time 6D Object Pose Estimation on CPU - Yoshinori Konishi, Kosuke Hattori, Manabu Hashimoto. [Paper]
• Holistic and local patch framework for 6D object pose estimation in RGB-D images - Haoruo Zhang, Qixin Cao. [Paper]
• Estimating 6D Pose From Localizing Designated Surface Keypoints - Zelin Zhao, Gao Peng, Haoyu Wang, Hao-Shu Fang, Chengkun Li, Cewu Lu. [Paper]
• Real-Time Object Pose Estimation with Pose Interpreter Networks- Jimmy Wu, Bolei Zhou, Rebecca Russell, Vincent Kee, Syler Wagner, Mitchell Hebert, Antonio Torralba, David M.S. Johnson. [Paper]
• Segmentation-driven 6D Object Pose Estimation - Yinlin Hu, Joachim Hugonot, Pascal Fua, Mathieu Salzmann. [Paper]
• Robust 6D Object Pose Estimation with Stochastic Congruent Sets - Chaitanya Mitash, Abdeslam Boularias, Kostas E. Bekris. [Paper]
• BOP: Benchmark for 6D Object Pose Estimation - Tomas Hodan, Frank Michel, Eric Brachmann, Wadim Kehl, Anders Glent Buch, Dirk Kraft, Bertram Drost, Joel Vidal, Stephan Ihrke, Xenophon Zabulis, Caner Sahin, Fabian Manhardt, Federico Tombari, Tae-Kyun Kim, Jiri Matas, Carsten Rother. [Paper]
• Deep Object Pose Estimation for Semantic Robotic Grasping of Household Objects - Jonathan Tremblay, Thang To, Balakumar Sundaralingam, Yu Xiang, Dieter Fox, Stan Birchfield. [Paper]
• PoseCNN: Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes - Yu Xiang, Tanner Schmidt, Venkatraman Narayanan and Dieter Fox. [Paper]
• Multi-view 6D Object Pose Estimation and Camera Motion Planning Using RGBD Images - Juil Sock, S. Hamidreza Kasaei, Luís Seabra Lopes, Tae-Kyun Kim. [Paper]
• Global Hypothesis Generation for 6D Object Pose Estimation - Frank Michel, Alexander Kirillov,Eric Brachmann, Alexander Krull, Stefan Gumhold, Bogdan Savchynskyy, Carsten Rother. [Paper]
• BB8: A Scalable, Accurate, Robust to Partial Occlusion Method for Predicting the 3D Poses of Challenging Objects without Using Depth - Mahdi Rad, Vincent Lepetit. [Paper]
• Real-Time Seamless Single Shot 6D Object Pose Prediction - Bugra Tekin, Sudipta N. Sinha, Pascal Fua. [Paper]
• SSD-6D: Making RGB-based 3D detection and 6D pose estimation great again - Wadim Kehl, Fabian Manhardt, Federico Tombari, Slobodan Ilic, Nassir Navab. [Paper]
• Deep Learning of Local RGB-D Patches for 3D Object Detection and 6D Pose Estimation - Wadim Kehl, Fausto Milletari, Federico Tombari, Slobodan Ilic, Nassir Navab. [Paper]
• Deep-6DPose: Recovering 6D Object Pose from a Single RGB Image - Thanh-Toan Do, Ming Cai, Trung Pham, Ian Reid. [[Paper]] (https://arxiv.org/pdf/1802.10367.pdf)
• Learning 6D Object Pose Estimation Using 3D Object Coordinates - Eric Brachmann, Alexander Krull, Frank Michel, Stefan Gumhold, Jamie Shotton, Carsten Rother. [Paper]
• The MOPED framework: Object recognition and pose estimation for manipulation - Alvaro Collet Romea, Manuel Martinez Torres and Siddhartha Srinivasa. [Paper]

Code

• HybridPose
• PoseCNN
• Single Shot Pose Estimation
• SSD-6D
• Dope Object Pose Estimation
• Pose Interpreter Networks
• Tools for Evaluation of 6D Object Pose Estimation
• Augmented Autoencoder
• DeepIM
• DenseFusion
• BetaPose
• PVNet

Datasets

• LINEMOD
• OccludedLINEMOD
• YCB Video Dataset [Dataset] [Code]
• Falling Things [Dataset] [Paper]
• Rutgers 6D Object Pose Estimation [Dataset]

Tutorials

• Real-time pose estimation of a textured object[Link]
• Pose estimation from points[Link]