3D Pictorial Structures Revisited: Multiple Human Pose Estimation
By Vasileios Belagiannis, Sikandar Amin, Mykhaylo Andriluka, Bernt Schiele, Nassir Navab, Slobodan Ilic. 2016
123 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Human-Computer Interaction
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- Luc Van Gool
- Xiaogang Wang
- Jitendra Malik
- Andrew Zisserman
- Bernt Schiele
- Cordelia Schmid
- Ming-Hsuan Yang
- Dacheng Tao
In Human-Computer Interaction
- Juergen Gall
- Jonathan Tompson
- C. Bregler
- Michael J. Black
- George Papandreou
- Zhi Zhang
- Guanghan Ning
- Zhiquan He
Citations in the corpus
- Towards Accurate Multi-person Pose Estimation in the Wild (2017, methodology): “D person detection is used as a first step in several 3D pose estimation works [39, 4, 5].”
- Self-Supervised Learning of 3D Human Pose Using Multi-View Geometry (2019, methodology): “Early work [1, 5, 6, 3, 4] used 2D pose estimations obtained from calibrated cameras to produce 3D pose by triangulation or pictorial structures model.”
- Multi-person Pose Estimation with Local Joint-to-Person Associations (2016, background): “In In contrast to the single person pose estimation, multi-person pose estimation poses a significantly more complex problem, and only a few works have focused in this direction [2,5,11–14,22,24–26].”
- Knowledge-Guided Deep Fractal Neural Networks for Human Pose Estimation (2017, background): “Closely-related tasks include 3D human pose estimation [8] and human pose estimation in videos [9], [10].”
- On Self-Contact and Human Pose (2021, background): “Similar ideas are adopted in [3, 10] where line segments are replaced with cylinders.”