Fetching the paper…
Reading the bibliography…
3D pose estimation from a single 2D image is an important and challenging task in computer vision with applications in autonomous driving, robot manipulation and augmented reality.
Hierarchical mixtures of experts and the em algorithm
Michael I. Jordan and Robert A. Jacobs · 1994
Earlier work this paper cites.
Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-fei · 2009
Earlier work this paper cites.
Convolutional neural networks for joint object detection and pose estimation: A comparative study
Francisco Massa, Mathieu Aubry, and Renaud Marlet · 2014
Earlier work this paper cites.
Beyond PASCAL: A benchmark for 3D object detection in the wild
Roozbeh Mottaghi Yu Xiang and Silvio Savarese · 2014
Earlier work this paper cites.
A novel representation of parts for accurate 3d object detection and tracking in monocular images
Alberto Crivellaro, Mahdi Rad, Yannick Verdie, Kwang Moo Yi, Pascal Fua, and Vincent Lepetit · 2015
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2015
Earlier work this paper cites.
Faster R-CNN: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2015
Earlier work this paper cites.
Render for cnn: Viewpoint estimation in images using cnns trained with rendered 3d model views
Hao Su, Charles R. Qi, Yangyan Li, and Leonidas J. Guibas · 2015
Earlier work this paper cites.
Viewpoints and keypoints
Shubham Tulsiani and Jitendra Malik · 2015
Cited alongside, same era.
A comparative analysis and study of multiview CNN models for joint object categorization and pose estimation
Mohamed Elhoseiny, Tarek El-Gaaly, Amr Bakry, and Ahmed Elgammal · 2016
Cited alongside, same era.
Crafting a multi-task CNN for viewpoint estimation
Francisco Massa, Renaud Marlet, and Mathieu Aubry · 2016
Cited alongside, same era.
Viewpoint estimation for objects with convolutional neural network trained on synthetic images
Yumeng Wang, Shuyang Li, Mengyao Jia, and Wei Liang · 2016
Cited alongside, same era.
Single Image 3D Interpreter Network
Jiajun Wu, Tianfan Xue, Joseph J Lim, Yuandong Tian, Joshua B Tenenbaum, Antonio Torralba, and William T Freeman · 2016
Cited alongside, same era.
Densereg: Fully convolutional dense shape regression in-the-wild
Riza Alp Güler, George Trigeorgis, Epameinondas Antonakos, Patrick Snape, Stefanos Zafeiriou, and Iasonas Kokkinos · 2017
3d bounding box estimation using deep learning and geometry
Arsalan Mousavian, Dragomir Anguelov, John Flynn, and Jana Kosecka · 2017
Later among the works it cites.
Automatic differentiation in pytorch
Adam Paszke, Sam Gross, Soumith Chintala, Gregory Chanan, Edward Yang, Zachary DeVito, Zeming Lin, Alban Desmaison, Luca Antiga, and Adam Lerer · 2017
Later among the works it cites.
6-DoF object pose from semantic keypoints
Georgios Pavlakos, Xiaowei Zhou, Aaron Chan, Konstantinos G Derpanis, and Kostas Daniilidis · 2017
Later among the works it cites.
Bb8: A scalable, accurate, robust to partial occlusion method for predicting the 3d poses of challenging objects without using depth
Mahdi Rad and Vincent Lepetit · 2017
Later among the works it cites.
3d pose estimation and 3d model retrieval for objects in the wild
Alexander Grabner, Peter M. Roth, and Vincent Lepetit · 2018
Closest in time.
Densereg: Fully convolutional dense shape regression in-the-wild
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
3D pose regression using convolutional neural networks
Siddharth Mahendran, Haider Ali, and René Vidal · 2017
Cited alongside, same era.
http://www.pascal-network.org/challenges/VOC/databases.html
The PASCAL Object Recognition Database Collection
Cited in the paper.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun
Cited in the paper.
Identity mappings in deep residual networks
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun
Cited in the paper.
Riza Alp Güler, George Trigeorgis, Epameinondas Antonakos, Patrick Snape, Stefanos Zafeiriou, and Iasonas Kokkinos · 2018
Closest in time.
A unified framework for multi-view multi-class object pose estimation
Chi Li, Jin Bai, and Gregory D. Hager · 2018
Closest in time.